This paper presents an investigation of the impact of saturation effects on the measured signal intensity from each line group, as well as an estimation of the accuracy of the method. The saturation effects observed here would result in a large systematic error if they are not taken into account when using the degenerate four-wave mixing intensity of these water line groups to calculate the flame temperature.It has previously been demonstrated that the ratio of the degenerate four wave mixing signal from two hot water line groups near 3231 cm This method was first proposed by Sun et al.2 The two water line groups in question are located in the 3230–3232 cm–1 range, and their relative intensity changes rapidly with temperature in the range 1000–2000 K, making this a potentially very sensitive method for flame thermometry.Temperature measurements are of high importance in combustion research. Molecular line strengths are sensitive to temperature, so accurate temperature measurements are needed to accurately measure the concentration of molecular species. A variety of laser techniques have been developed for temperature measurements in combustion environments.4, C2H6, HCN, HCl, HF, etc. Quantitative concentration measurements in combustion environments using DFWM and IRPS have been demonstrated using calibration in a room-temperature gas flow with known concentrations.3 This method requires accurate knowledge of the temperature during the measurement. A major advantage of using water line thermometry (WALTHER) to determine the temperature is that the strength of the water line groups can also be measured using IRPS or DFWM. This drastically reduces the time and effort needed to obtain the temperature during the concentration measurement, and makes it easier to ensure that the temperature and concentration measurements are taken under the same conditions. For these reasons, WALTHER was employed for spatially resolved HCN concentration measurements.4The work in our laboratory has been focused on the use of infrared polarization spectroscopy (IRPS) and infrared degenerate four wave mixing (DFWM) for combustion diagnostics of molecular species which otherwise lack available absorption lines in the visible/ultraviolet spectral range. This includes many hydrocarbons and toxic pollutants such as CH2 However, a recent work has raised new questions. Firstly, we have suspected that the mid-infrared dye-pumped laser system, used for IRPS and DFWM measurements, jumps between different longitudinal modes in a way that can vary from scan to scan and thus make the results less reproducible. The dye laser system  has recently been equipped with a dynamic mode operation system (DMO), which vibrates the dye laser cavity to increase the randomness of the longitudinal mode structure. It would be good to investigate how this improves the accuracy and repeatability of the measurements. Secondly, the effects of saturation on the accuracy of the WALTHER method need to be quantified. Finally, we wished to investigate how the on-line approach to WALTHER used in Hot et al.4 perform compared to measuring the line group strength by excitation scans.The effect of saturation was already investigated in Sun et al.4/H2/air flames at different temperatures. The saturation intensity for the different line groups was investigated at different flame temperatures, and the effect of the different degree of saturation on the WALTHER line ratio was thoroughly investigated. In order to calibrate the results, the temperature in the flames was measured using laser Rayleigh scattering (LRS), and this value was used as a reference for the later WALTHER measurements using both the on-line and scanning approach.This paper performs a systematic investigation of the DFWM signal from the two water line groups employed for water line flame thermometry. The repeatability of the excitation scans and the stability of the measured signal intensity were investigated in several laminar CH2 uses the ratio between water line groups II and III to determine the flame temperature. As can be seen in the figure, the relative strength of line groups II and III changes rapidly over this temperature range: line group II has highest intensity at lower temperatures, while the relative strength of line group III increases at higher temperatures. 4/H2/air flames. The scans were recorded at 1520 K (Flame 8), 1681 K (Flame 5) and 1805 K (Flame 1). The flow rates of fuel and air for the different flames are shown in 5 while Sun et al.2 used HITEMP 2000 data. The line labelled as ‘e’ in this article was not included in the HITEMP 2000 database, and therefore was not included in the analysis by Sun et al. The line strength nS of each individual line n scales with the temperature T as6nE is the energy level of the lower state of the transition, Q is the partition function, The individual transition lines that make up line groups II and III are listed in re T as6Sn(T)=Sn.11 Closely spaced transitions in DFWM have been treated analytically12 and by DNS.13 However, the application of these simulation methods is outside the scope of this work.The mathematical model described by Williams et al.1114). The intensity RI of the Rayleigh scattered light is given by14C is a calibration constant, I0 is the laser intensity, N is the number density and Rσ is the Rayleigh cross section. The cross-section varies depending on the angle of observation, where the strongest scattering is located in a direction at a 90° angle to the laser polarization. For this case, the Rayleigh cross section i is defined as14in is the refractive index for molecule i and λ is the wavelength of the laser radiation. For completely accurate cross sections, the depolarization ratio of different molecules also needs to be accounted for. However, at visible laser wavelengths, the effects of the depolarization ratio are usually negligible.16 LRS flame thermometry is achieved by comparing the scattering intensity in the flame with the scattering intensity of a known medium  measured with the same setup. The temperature is calculated from the Rayleigh scattering intensity aI and fI in the air and flame, respectively, as14Laser Rayleigh scattering (LRS) measures the elastic scattering of light from molecules. In LRS, a laser beam is directed through the measurement medium, and a camera is aligned to measure the Rayleigh scattered light from the molecules. The intensity of the scattered light can be used for accurate temperature measurements. LRS has been applied for flame thermometry in a wide variety of alignments and environments  and a single-mode 1064 nm laser beam from a Nd:YAG laser . The laser provides pulse energies up to 6.3 mJ in the 3230–3232 cm–1 spectral range used here, with a linewidth of less than 0.025 cm–1, at a repetition rate of 10 Hz. In addition to what is covered in the previous descriptions,22 the system has been equipped with a dynamic modulation operation (DMO) mode. This randomizes the longitudinal mode distribution of the dye laser output by vibrating the cavity mirrors at 11 Hz, in order to average out effects of mode jumping. This reduces the variability between separate scans. In practice, we did not see much difference with the DMO on/off, which could be because the mode jumping is still within the linewidth of the absorption line. The shot-to-shot variation for the online measurements on line group III is much less compared to the narrower line group II, which supports this assumption.The DFWM pump and probe beams were generated by a pulsed IR dye laser system, which has been described previously.23 The four beams are spaced at the four corners in a square. One of these beams is chosen to be the alignment beam. This beam traces the path the generated signal beam will follow, which enables the alignment of the signal beam path to the detector. During the experiments, the alignment beam is blocked using a beam block. The remaining beams are focused to a common crossing point using the lens L1, 2 inches in diameter with a 500 mm focal length which results in a beamwaist with a 0.22 mm radius. The size of the measurement volume is estimated to be 0.22 × 0.22 × 11 mm3, and the measurement point was aligned at 8 mm height above the burner (HAB). The pump and probe beams are then blocked using an iris, while the signal is let through and collimated using lens L2, which has a focal length of 500 mm. The signal is directed to the upconversion detector, where the signal intensity is reduced using ND filters if necessary. Lens L3 is used to focus the signal beam into the periodically poled lithium niobate (PPLN) crystal of the upconversion detector, to match the beam width of the 1064 nm pump in the detector. To achieve the optimal focal length, L3 consists of two lenses with focal lengths of 1000 mm and 200 mm for an effective focal length of 167 mm. The upconversion detector uses an intracavity system to do sum frequency generation between the IR signal and a 1064 nm pump, for increased sensitivity. The system and its advantages have been described in detail elsewhere.23–25A diagram of the setup used for DFWM is shown in –1 at a scanning speed of 0.025 cm–1s–1 and recording the DFWM signal during the scan. Each measurement point shown in the following figures is the average of the values obtained from five scans. The standard deviation of the values from each set of five scans was used to calculate the uncertainty. The on-line method consisted of tuning the laser to the peak of a water line group and recording the signal for 30 s. The maximum value recorded during this time was used as the DFWM intensity of each line group. The maximum value was used because this provided a more consistent result compared to using the average value. One cause for this could be that the intensity data obtained for each 30 s on-line measurement does not follow a normal distribution. One on-line measurement of each peak was used to obtain the ratio, and six ratio measurements were recorded to evaluate the repeatability and precision. Scanning is generally easier to work with, and is more accurate, due to the difficulty in tuning the laser wavelength precisely to the peak wavelength. The advantage of using the on-line approach is that it allows temporal resolution for processes that change on time-scales shorter than the duration of a scan.The signal from the water lines was recorded in two ways using this setup, either by a scanning measurement or an on-line peak measurement. The first was achieved by scanning the laser wavelength across the range 3230–3231.5 cmf/2.8) camera lens, placed at 90° to the laser beam path and to the laser polarization. The LRS signal along the laser beam path was recorded as the average of 10 images, and a reference LRS signal was recorded in a dry air flow. In addition to this, a background image was also recorded in order to remove background noise. The exposure time of the camera was set to 0.1 s, and the EM gain to 10.The temperature in flames 1–8 was measured using a relatively simple LRS setup. A collimated 457 nm CW laser beam, with a diameter of 2 mm and power 170 mW, was sent through the flame at 8 mm HAB. The Rayleigh scattered light  was detected by an EMCCD camera (Andor Luca R DL-604M-OEM) equipped with a Nikon 2730The flame temperature measured with LRS at 8 mm HAB is shown in τ2. Group II approaches the saturation limit at 1781 K (Flame 2), but for 1542 K (Flame 7) this does not seem to be the case. However, for laser intensities I > 0.2 TWm–2, the intensity dependence has gone from cubic, as it is for low energies, to linear, which reduces the impact of intensity variations from pulse to pulse.To investigate the saturation behaviour of line groups II and III, DFWM excitation scans over the lines were recorded for a range of different pulse energies, in Flame 2 (1781 K) and Flame 7 1542 K), respectively. The average peak value from five excitation scans for each line group is shown in 2 K, resppumpI. The peak ratios might converge to a set ratio when both groups II and III are well into the saturated regime (From To compare WALTHER with other thermometry methods, it is necessary to quantify the uncertainty of the temperature measurement. This was done by calculating the temperature from the measured ratios, using the fitted calibration curves in The measurements presented show that saturation effects have major impact on the value of water line ratio. However, within the investigated temperature range and for a constant pump and probe intensity, the effect is a constant corrective multiplicative factor, at least when the ratio is measured by scanning across the water lines. In this case, it is possible to adjust for the saturation effects by using a calibration measurement. In the case of the on-line measurements, the ratio trend presented here does not match what is expected from calculations, although the values are reproducible. It is possible to calibrate the on-line ratio as a function of temperature, and use this calibration for further temperature measurements. However, when using a calibration measurement it is essential to keep all important parameters constant between the calibration measurement and the actual measurement. As long as the reason for the deviation from the predicted trend is not understood, it is not possible to control the cause of this effect when going from the calibration measurement to the actual measurement. The only difference between the results measured by scanning and with the on-line approach is the operation of the laser, but we have not been able to pinpoint which factor is the cause of the different results. It is possible that this is a result of the inherent instability of the multi-mode laser, and that it could be avoided using a single-mode laser system with better wavelength tuning precision.2O line groups II and III is very sensitive to small temperature changes in the interval 1000–2000 K, making this a very sensitive technique for small temperature changes. Utilizing the absorption of water, which is almost always present in relatively high concentrations in combustion, means there is no need for seeding of other species into the flame. The mid-infrared laser beams are much less sensitive to scattering compared to visible and ultraviolet wavelengths, making this a viable technique for temperature measurements in sooty flames and other high-scattering environments. In addition, mid-IR DFWM is a promising candidate for quantitative concentration measurements of molecules in combustion environments,4 and in those types of measurements this technique can be applied with the same setup without needing any extra complex instrumentation, apart from some type of calibration measurement.Despite the need to understand and calibrate the saturation behavior, the WALTHER method has several advantages. The intensity ratio of the H–1 spectral range can provide accurate temperature measurements when combined with the appropriate calibration measurements. The on-line approach needs to be further investigated as it does not seem to provide completely reliable results. However, if the practical challenges of the on-line approach can be identified and addressed, it would become a useful tool for studying time-varying combustion phenomena.In conclusion, measuring the water line ratio using scanning over a less than 1 cm


The Ryu–Takayanagi formula provides the entanglement entropy of quantum field theory as an area of the minimal surface (Ryu–Takayanagi surface) in a corresponding gravity theory. There are some attempts to understand the formula as a flow rather than as a surface. In this paper, we consider null rays emitted from the AdS boundary and construct a flow representing the causal holographic information. We present a sufficient and necessary condition that the causal information surface coincides with Ryu–Takayanagi surface. In particular, we show that, in spherical symmetric static spacetimes with a negative cosmological constant, wave fronts of null geodesics from a point on the AdS boundary become extremal surfaces and therefore they can be regarded as the Ryu–Takayanagi surfaces. In addition, from the viewpoint of flow, we propose a wave optical formula to calculate the causal holographic information. A in CFT can calculated as the area of the minimal bulk surface A (RT surface):It is well known that the entanglement entropy (EE) of conformal field theory (CFT) can calculate in a corresponding gravity theory by the Ryu–Takayanagi (RT) formula ,2 in AdSdary CFT  or MERA dary CFT , subregidary CFT .A. The property that the maximal total flux of A is equal to the area of the RT surface is proved by the max-flow min-cut theorem [From this point of view, it is better to regard the RT formula as a flow proposed by the paper . The aut theorem . The bit theorem .A defined as follows. Let us consider the bulk domain of influence of the boundary domain of dependence of a region A. Then, the causal information surface A. That is, As a similar concept of holographic EE, a causal holographic information χA  was defiussed in .When does the equality  surface ,12, we aIf The structure of this paper is as follows. In In this section, before going to discuss the general situation, we demonstrate that wave fronts of null rays are the RT surface in the BTZ spacetime.M is the mass of the black hole and r, and it isr (see We derive the equation of the RT surface in the BTZ spacetime (4)ds2=−of r see . Note thC and we prepare an arc The entanglement entropy of CFT on the AdS boundary for an arc tituting  into 5)|θ|≤θℓ isituting (AreaMℓ=2ℓituting (AreaMℓ=2ℓdS/(2GN)  and AdS/FT on S1 ,16 afterd denotes spatial dimension and We consider null rays emitted from a point on the AdS boundary and their wave fronts. Our purpose is to find out the relation between wave fronts of null rays and the RT surface. We consider null rays in the spherically symmetric static spacetimet and In a static spacetime, a wave front of null rays emitted from a point source is defined as a l ray iskμ=: θ(r)=1Mlo: θ(r)=1MloNote that Equation (20) of the wave front is the same as Equation (6) of the RT surface by identifying In this section, based on the observation in the previous section for the BTZ spacetime, we show the following proposition for spherically symmetric static spacetimes with a cosmological constant (no matter fields).Proposition 1.Wave fronts of shear free null congruence are extremal surfaces in static spacetime when the affine parameter of null rays goes to infinity.Corollary 1.In static spacetimes with a negative cosmological constant, wave fronts of null rays emitted from the AdS boundary are extremal surfaces if and only if the shear of the null congruence vanishes.We adopt the metric  with cooH of a wave front of null rays on a constant time slice is defined byH of a wave front is proportional to the expansion of the null geodesic congruence. The expansion We prove the proposition by using the fact that the extremal surface is a surface with zero mean curvature. The mean curvature equationdΘdλ=−Θ2dAsymptotically AdS spacetimes are peculiar because they have the timelike boundary. We consider the pure AdS spacetime of which metric function is given by We can see that the condition for Based on the idea presented in the previous section, we can understand null rays as a natural flow characterizing the EE of the dual CFT if a and S are real functions. In the eikonal limit, they obeyFor the massless scalar field S can be written as a is independent of A on the AdS boundary, isThe Equation  is the Hk˜i=ω2f,f−1/2Dia2Because Equation  equals becomes spherical because the boundary of the region is a wave front on the AdS boundary. However, by superposing point sources, it is possible to construct an extremal surface homologous to a region with arbitrary shapes on the AdS boundary by considering the envelope of wave fronts from each point sources. Thus, the method presented in this paper may be applicable to the plateaux problem ,21 with


In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direction. It solves the problem that existing sensors can only detect in the normal direction to ensure accuracy when the degree of freedom (DOF) of surgical instruments is limited. The proposed senor can distinguish samples with different stiffness and recognize lump from normal tissue effectively when the contact angle varies within . These are achieved by establishing a new detection model and sensor optimization. It deduces the influence of contact angle on stiffness detection by sensor parameters design and optimization. The detection performance of the sensor is confirmed by simulation and experiment. Five samples with different stiffness  are used. Through blind recognition test in simulation, the recognition rate is 100% when the contact angle is randomly selected within 30°, 94.1% within 45°, which is 38.7% higher than the unoptimized sensor. Through blind classification test and automatic k-means clustering in experiment, the correct rate is 92% when the contact angle is randomly selected within 45°. We can get the proposed sensor can easily recognize samples with different stiffness with high accuracy which has broad application prospects in the medical field. With the development of medical treatment and the advancement of robot technology, robot-assisted minimally invasive interventional surgery (RMIS) is becoming popular. It has the advantages of small trauma, quick recovery and high accuracy. Compared with traditional surgery, doctors cannot touch tissue directly in RMIS, which may cause misdiagnosis or wrong resection. Since the lumps are often harder than the surrounding normal tissues, doctors can usually directly distinguish the lump by the difference in stiffness felt. ,2 In ordThere are many kinds of tactile sensors that can be used to detect force and stiffness. C. H. Chuang  designs So far, most tactile sensors in literature can detect the stiffness of tissue only when the contact is in the normal direction. However, most MIS procedures are performed in a confined space such as the transurethral resection of bladder tumor (TURBt) and uterine fibroid embolization (UFE). The limited degree of freedom (DOF) of the instrument causes the tactile sensor to become unable to be placed in the normal direction to contact the tissue surface, which may lead to lump undetectable. The method of achieving stiffness detection and lump identification under multiple constraints is particularly important. However, the use of existing tactile sensors is mostly limited by the contact angle between the probe and normal direction of tissue surface. The stiffness palpation method proposed in  can distThis paper proposes a piezoelectric tactile sensor that can not only detect the stiffness when the probe is normal to the tissue surface, but also when there is a contact angle relative to the normal direction. The detection model with a contact angle is proposed in α, a stiffness detection method is proposed. Based on that, parameters of the sensor are designed and optimized to minimalize the influence of angle change on detection.A piezoelectric sensor is preliminarily designed, and the sensing principle explains how the sensor works. In order to know the relationship between stiffness and contact angle α, as shown in This paper proposes a piezoelectric bimorph tactile sensor, and the structure is shown in Due to the inverse piezoelectric effect, applying an AC voltage in the polarization direction of the PZT Zx=rxAfter the sensor touches the tested tissue, the impedance of the system changes. The resonance frequency of the system shifts due to the change which can be measured.The frequency shift after the sensor touches the tissue can be expressed as ,19:(2)Δff and the characteristics of the tested tissue:Substituting Equation (1) into (2) finally obtains the relationship between the frequency shift ΔThe contact between the probe of the sensor and the tested tissue can be expressed as static contact and dynamic contact. Static contact means that a small force makes the probe contact the tissue at a certain indentation depth; dynamic contact means that an AC voltage is applied to the sensor which causes a small vibration between probe and tissue. However, for measuring the stiffness of object with a large anisotropy factor and Poisson’s ratio, the contact between the sensor and tissue can be approximated by static contact . BiologiNF, the sensor has a normal relative displacement Δ to the surface of the tissue, which is called indentation depth. Since the probe is spherical with a radius of R, the contour of the contact part can be approximated as a circle with a diameter of 2a, a≤ R. From the geometric relationship of contact, we can get:As shown in α, the probe produces a displacement of Δ in this direction. The contour of the contact part can still be approximately circular, with a diameter of 2a’, as shown in When the sensor’s DOF is limited, it cannot detect tissue in the normal direction but at angle α (α < 90°), the smaller the contact area S.It can be seen from Equation (6) that if the depth Δ is maintained at a constant value, the larger the angle Substituting Equation (6) into (3):α, the larger the angle α, the smaller the frequency shift Δf. However, the change of Δf can be reduced.It can be seen from the Equation (7) that the stiffness of the tested tissue is proportional to the frequency shift. When the sensor presses the tissue at a contact angle f is not only related to the stiffness and the angle during detection, but also related to the parameters of the sensor itself: the length L of PZT and the radius R of the probe. Through the design and optimization of these two items, the influence of α on Δf can be reduced. In order to prevent the slip phenomenon, we only discuss the angle in the range of α ∈ . Taking the angle α in Equation (7) as the independent variable, the schematic image of Δf-α function is shown in The sensor’s Δf0°and Δf45° is close to 0 (D1 is close to 0), to ensure that the angle change has the smallest impact on the detection result. (2) When tissues with different stiffness are tested, the difference between Δif and Δjf should be larger than D1 to ensure that they can be reliably distinguished, as shown in D2 in i and j represent samples with different stiffness. Stiffness of sample i is larger than sample j.To optimize the performance of the sensor, two goals of sensor parameters optimization are: (1) As shown in D1 ≥ 0, get R ≥ 0.42Δ. In Equation (9), select the extreme case  for discussion, set α = 0°, x(i)E = 1.2x(j)E, the solution is R < 2.5Δ. In order to ensure the contact surface is approximately circular, control R≥ Δ. Therefore, take R = Δ. For the L, two sets of parameters are selected for comparison in simulation.Solve Equation (8) In order to test the sensor performance on distinguishing different stiffness samples with arbitrary contact angle, effect of optimization and blind recognition ability, simulation is designed.L = 35 mm is preliminarily chosen, and probe tip radius and indentation depth R = Δ = 0.5 mm are selected. The materials of sensor are shown in A model of the sensor and the tested samples was established, and the model was simulated in Ansys Workbench. Sensor structure is shown in Five samples with different stiffness are set, including the normal tissue with the smallest stiffness (sample 1) and lumps  , and theα is set to 0°, 15°, 30° and 45°, respectively. The contact with the sample is set as frictional contact, and the friction coefficient is 0.1 ,  and  to detect the stiffness value of each point of each sample. The stiffness value of each sample at the boundary of the interval is used as the recognition range of the sample surface point. That is, when sample 1 is tested, if the stiffness value of a certain point is within the recognition range of sample 1, this point will be judged as sample 1. If it is also in the range of sample 2 at the same time, it may be misjudged as sample 2. The boundaries of the stiffness range of the five samples are obtained by simulation. The results of normal detection and random angle detection are shown in In order to prove the ability of the optimized sensor to recognize samples with different stiffness when the contact angle is from 0° to 45°, five samples (the same as mentioned before) are used as the tested objects, comparing the blind recognition effect of the optimized sensor , far better than the recognition rate before optimization.Based on simulation, an experiment is designed, a piezoelectric sensor is fabricated. Five soft silica gel samples with different stiffness are made. The stiffness of samples consistent with the simulation. The actual stiffness measured by the 00-type hardness tester is shown in As shown in α) to facilitate analysis.The resonance frequency of the un-load sensor is 137.6 Hz, which is approximately the same as the simulation result. It can be seen from In order to prove the sensor’s ability to blindly recognize samples with different stiffness, the labels of the five samples are torn off and the order was disturbed. The proposed sensor is used to randomly detect a sample with a contact angle within 45°. Each random detection process includes randomly selecting a sample of unknown stiffness, randomly selecting a point on this sample (the sample stiffness is uniform), and testing the stiffness of this point at a random contact angle. After each test is completed, each sample is shuffled for the next test, repeating 50 times. These 50 stiffness test results (expressed in frequency shift) are imported into k-means clustering algorithm for automatic classification. The classification result is shown in From In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in RMIS is proposed, whose detection principle is based on the resonant frequency change of the system after making contact with the tissue. The stiffness can be detected without causing damage to the tissue. The outstanding feature of the sensor is that it can detect the stiffness and distinguish different stiffness samples not only in the normal direction, but also when there is a contact angle between probe and normal direction of tissue surface, solving the problem that when the DOF of surgical instruments is limited, the sensor cannot detect in normal direction. For the traditional tactile sensor, when it deviates from the normal direction, the stiffness cannot be detected, or the accuracy is greatly reduced. The proposed sensor solves this problem well.Through theoretical analysis, the principle of sensing and the stiffness detection method with a contact angle are obtained. The sensor system’s resonance frequency shift is proportional to the stiffness of the tested tissue and is negatively related to the contact angle. The parameters of the sensor are optimized to minimalize the influence of angle on stiffness. In order to test the optimized sensor performance, a simulation and an experiment are designed. Normal tissue sample and lump samples are set. When the angle changes from 0° to 45°, samples with different stiffness can be clearly distinguished. The sample recognition rate of the optimized sensor is 100% when the contact angle is selected randomly within 30°  in simulation, 94.1% within 45° (92% in experiment), which is 38.7% higher than the unoptimized sensor. It can be seen that the proposed sensor is hardly affected by angle when detecting stiffness. Additionally, it has abilities to distinguish different stiffness, distinguish lump from normal tissue, and recognize different stiffness samples with high precision. It signifies that the stiffness detection is no longer restricted by space and DOF, and that the sensor can detect tumors in any posture with high accuracy.Although the sensor has been well verified in this study, there are still some areas that need to be improved. The proposed sensor is sensitive within the stiffness range of samples used in tests, but the sensitivity can be further analyzed with a larger stiffness range with continuous values. For the contact angle aspect, subsequent study will focus on effectively compensating the influence of the contact angle on the sensor’s detection to obtain more accurate stiffness results. For sensor products, an isolation coating will be used for insulation and protection. Additionally, to further test the performance of the sensor, the sensor will be attached to the end of the surgical robot and a porcine bladder will be used. At the same time, the sensor will be further studied how to be more compact to meet the needs of more minimally invasive surgery.For the proposed piezoelectric sensor, we establish a new detection model with contact angle to optimize the sensor’s parameters. It makes the sensor insensitive to angle during detection, so as to meet the requirement of detecting stiffness in any posture. At the same time, the accuracy of stiffness identification is verified, proving that it has the potential to be used in interventional surgery with limited space.


Some of the anatomical and functional basis of cognitive impairment in multiple sclerosis (MS) currently remains unknown. In particular, there is scarce knowledge about modulations in induced EEG (nonphase activity) for diverse frequency bands related to attentional deficits in this pathology. The present study analyzes phase and nonphase alpha and gamma modulations in 26 remitting-relapsing multiple sclerosis patients during their participation in the attention network test compared with twenty-six healthy controls (HCs) matched in sociodemographic variables. Behavioral results showed that the MS group exhibited general slowing, suggesting impairment in alerting and orienting networks, as has been previously described in other studies. Time–frequency analysis of EEG revealed that the gamma band was related to the spatial translation of the attentional focus, and the alpha band seemed to be related to the expectancy mechanisms and cognitive processing of the target. Moreover, phase and nonphase modulations differed in their psychophysiological roles and were affected differently in the MS and HC groups. In summary, nonphase modulations can unveil hidden cognitive mechanisms for phase analysis and complete our knowledge of the neural basis of cognitive impairment in multiple sclerosis pathology. The onset of MS occurs over a wide age range (mainly between 20 and 40 years), and MS predominantly affects women. Approximately 40–70% of patients with the disease show diverse cognitive deficits3. Therefore, different neuropsychological profiles can be found during clinical assessments. Attention, processing speed and memory are the cognitive domains most frequently affected7. To understand the neural basis of these cognitive alterations in MS, different cognitive paradigms and techniques have been used10.Multiple sclerosis (MS) is a chronic degenerative neurological disease of unknown etiology that causes mainly neurological damage including demyelination and inflammation of the central nervous system (CNS)14.One of the cognitive paradigms that has often been used to evaluate attention is the “Attention Network Test” (ANT). The ANT was developed to assess three attentional networks  and has been performed with different versions and for diverse pathologies15, it did not begin to be applied in patients with multiple sclerosis until 201016. These authors found an alteration in patients’ alerting network with respect to healthy controls (HCs). The authors suggested that the deficit could be due to lower response readiness or a reduced ability of patients to maintain alertness after presentation of the cue. Other authors have confirmed the alteration in the alerting network in patients with multiple sclerosis even in early stages of the disease17. Moreover, a study18 found deficits in the alerting and orienting networks in patients based not only on behavioral responses but also on specific psychophysiological variables .Although the ANT was developed in 200120. Time–frequency EEG methods such as temporal spectral evolution (TSE) can overcome this limit21. TSE shows EEG time–frequency information that includes both phase (evoked) and nonphase (induced) activity related to stimulus presentation (for a detailed description of the TSE method23).One way to improve our knowledge of the neural basis of cognitive impairment in MS pathology is to analyze the frequency domain of the EEG signal. In its origins, the EEG signal was largely studied using fast Fourier transformation (FFT), but this approach has the disadvantage of renouncing the high EEG time resolution24. However, some authors have argued that it may not exclusively reflect an idling status but can also play an active role in inhibitory control and timing of sensory processing25. Along this line, some authors have suggested that an increase in alpha activity in regions irrelevant to the task may reflect inhibition processes26. Specifically, for attentional visual processing, some studies have observed higher alpha activity in those regions of the occipital cortex where unattended locations are retinotopically represented29.Through TSE and other time–frequency techniques, numerous studies have related frequency bands of EEG to specific cognitive mechanisms. In the case of the alpha band, originally, it was identified as an indicator of a neural area at rest30. Low alpha bands may be related to a general attention, while upper alpha bands are proposed to be linked to more specific processes such as semantic processing32. In fact, the topographical distribution of low alpha bands is usually larger and less specific than that of upper alpha bands, which tends to be more localized in scalp regions34.For decades, it has been suggested that there are two types of alpha bands, namely, low alpha (8–10.5 Hz) and upper alpha (10.5–13 Hz) bands, with different psychophysiological meanings36. The functional roles assigned to this band are more than the visual grouping, as has been reviewed by some authors37. In particular, this neural activity has been related to arousal or attention in humans40. One of the reasons that this band is suitable for attentional mechanisms is its fine temporal tuning for neuronal firing (10–30 ms time precision)41. Some studies have described the specific involvement of the gamma band in visual attentional tasks42. In the study by Gruber et al.41, the authors displayed colored rectangles in the left or right half of the screen, and a cue indicated to the subjects in which visual hemifield they had to shift their attention to detect target stimuli. These authors found an increase in the gamma activity (35–51 Hz) when the attended stimuli were rotating. In the study by Fries et al.42, neurons from cortical area V4 in macaque monkeys exhibited an increase in the gamma band (35–90 Hz) when the experimental subjects were attending to relevant stimuli and ignoring distracters.Another neurophysiological correlate that has been linked to cognitive functioning is the gamma band43. A more recent study44 showed that the alpha band is related to attentional mechanisms and processing speed; a smaller decrease in the resting-state alpha band in specific experimental conditions was associated with a poorer behavioral performance.With regard to these spectral bands and their relation to cognitive impairment in MS, some studies have described a higher decrement of the alpha band in MS patients reflecting a recruitment of more cognitive resources to perform the task45, a neurophysiological correlate of compensatory mechanisms or cortical excitatory states representative of some phases during the MS course45, or gray matter dysfunction, possibly mediated by GABAergic changes46.With regard to the gamma band, a few studies have described alterations in this band in MS patients related to diverse phenomena, such as alterations in cognitive processing in a visual attention task49. Authors have described a decrease in the alpha band after the warning signal  and an increase in the gamma content at 200 ms after target onset related to the orienting network47. However, this study did not consider if the modulation was in phase or nonphase to the onset of the stimuli47. In the last years, neuroscientists have focused on this difference and found that both domains (evoked and induced) could represent diverse processes in cognition52.Finally, there is scarce knowledge about the meaning of the spectral modulations observed during the execution of the ANTConsidering all these premises, the main goal of the present study was to analyze the modulations in the alpha and gamma bands  related to attentional impairment in an MS group assessed by the ANT. Our hypothesis was that behavioral data would show a general slowing in the MS group compared to the healthy group that would be corroborated by the neuropsychological assessment. Alpha and gamma modulations related to attentional mechanisms would show alterations in the MS group during the execution of the ANT. An open question in the present study was which components of the alpha and gamma modulations  would be related to attentional impairment.p < 0.001; η2 = 0.438]. In addition, the cue factor revealed differences between cues, with the no cue (NC) condition showing larger reaction times followed by the central cue (CC) condition and finally the spatial cue (SC) condition, which was the fastest  (Table p < 0.001).The HCs obtained a significantly shorter reaction time than the MS group , and patients were faster than HCs. This value does not indicate that MS patients were faster than HC subjects in this condition; it shows that MS patients were relatively faster for this condition than in all conditions in the MS group in the same comparison for HCs.After applying the correction of Fernández-Duque and BlackWith regard to precision, there were no significant differences between groups or other factors because of a similar high percentage of accuracy for all conditions in both experimental groups Table .54, indicating a moderate attentional impairment in our sample of MS patients (SDMT score = 44 ± 13.82). Last, Beck depression scores (BDI-II) indicated that there were not severe signs of depression in the MS group (BDI-II score = 7.44 ± 6.3).In terms of the number of hits on the PASAT-3s and the overall hit rate on the symbol digit modality test (SDMT), the latter showed a value of 2 SD under the cutoff scores defined by SepulcreThe evoked gamma activity showed no differences in latency after presentation of an SC between both groups Fig. .There wep < 0.001, ƞ2: 0.666). However, a post hoc comparison showed no significant differences between the levels of this main factor. Nevertheless, a post hoc comparison for the following interaction “cue × anterior–posterior location and medial–lateral location” showed that the SC was higher in amplitude than theNC and CC conditions for all derivations   that was caused by a higher amplitude of the gamma modulation in the MS group than in the HC group  = 4.51, ,50 = 4.5p = 0.002, ƞ2: 0.204)  = 6.42, 00 = 6.42,100 = 6.p < 0.009, ƞ2: 0.068). Post hoc comparisons showed that all derivations were higher in amplitude for the NC and CC conditions than for the SC condition .With regard to the induced activity, latency did not show differences for cue or group factors. For the amplitude variable, ANOVA showed that the “cue × anterior–posterior × lateral-medial” interaction was statistically significant  = 1.80, p = 0.015, ƞ2: 0.177), with MS patients exhibiting a higher amplitude than the healthy group  = 6.24, ,50 = 6.2p = 0.010; η2 = 0.237] and upper alpha bands   = 6.3649; p = 0.014; η2 = 0.773]. A post-hoc Bonferroni comparison showed that the SC condition reached the maximum amplitude later than the CC condition   = 4.5503; p = 0.037; η2 = 0.125]  = 87.305; p < 0.001; η2 = 0.644] . However, in the SC condition, there were no differences between groups in the latency in the low alpha or upper alpha bands  = 81.212; .204 = 81With regard to the amplitude variable for induced modulation, no differences in topographical distribution were found for the group factor or its interaction with other location factors in either low alpha or upper alpha bands or in any time interval analyzed (0–350 ms and 350–700 ms)  and for both groups, it was possible to conclude that the potential contribution of the evoked activity over induced activity could be discarded in all bands, as has been described in previous studiesThe behavioral results suggested an attentional impairment in the MS group. A general slowing was observed (approximately 100 ms) for MS patients in all cue conditions. Moreover, the delay in reaction times was not caused by a speed-accuracy tradeoff between experimental conditions for the patient group compared with the HC group. In addition, the neuropsychological assessment revealed an attentional impairment that was not caused by severe signs of depression (low scores on the BDI).58. With regard to the neural networks, the slower reaction times in the NC and CC conditions suggest that alerting mechanisms (phasic or tonic) could be impaired, as has been suggested by other studies18. Moreover, a longer reaction time in the SC condition also indicates that the orienting mechanism could also be affected, as previously described18.A delay in the reaction time for attentional tasks in MS patients has been described in previous studiesHowever, it seems unreasonable that such a common delay in all cue conditions (100 ms) could be due to multiple and diverse impairments such as the phasic and tonic alerting or orientation mechanisms. It is not possible with the current results to discard that a common mechanism operating in all conditions could be the reason for the general slowing in the MS sample.53. A statistical t test group comparison in all cue conditions  showed that the NC condition was responded to faster in the internal comparisons for MS patients than the same comparison in the HC group. This result suggests that MS patients try to be more ready for uncued targets that are more demanding in terms of response time. This approach could be a strategic compensation from MS patients to reduce the average reaction time for all the experimental conditions. However, a more intricate interpretation is suggested from neurophysiological measures, which will be described in the following paragraphs.A relevant result to better understand the attention impairment in the MS group comes from the data after the correction of Fernandez-Duque and BlackRegarding the induced activity, the gamma band seems to be related to the translation of the attentional focus towards the cued visual spatial locations. The only condition in the expectancy interval that showed an increase in the gamma amplitude was the SC condition during which subjects were required to move their attentional focus to specific spatial regions indicated by cues . On the other hand, during the NC or CC conditions, the attentional focus is maintained around a fixation point; therefore, no increase in the gamma activity is observed.In the case of the induced gamma response for target stimuli, the NC and CC conditions need an orienting response provoked by the onset of the stimuli and consequently a shifting of the attention focus towards it. This shift is translated as an increase in the amplitude of the gamma activity as it occurred in the SC condition for the cue onset. In the case of the target preceded by the SC condition, a small increase in the gamma response could represent a lower need to readjust the attentional focus precisely over the central arrow to avoid competition from distractor stimuli.47. Gamma band activity has been associated with an attentional mechanism involved in optimal performance in cognitive tasks.These results are in accordance with those of a previous study that showed that the orientation mechanism modulates gamma activity (without a specific definition of evoked or induced activity) in the first 200 ms after the onset of the target61. However, there have been diverse studies that have not found latency delays in behavioral or EEG parameters in MS patients during the execution of cognitive tasks62.With regard to the group variable, a first consideration is that the peak latencies of the evoked or induced gamma activities were not different between both groups. It is well known that MS pathology usually implies delays in the timing of cognitive processes caused by the demyelination processAt the same time, the amplitude for induced gamma activity was higher for MS subjects than for the HC group. It is counterintuitive that the MS group exhibited a higher amplitude than and a similar latency to the HC group. However, if the functional meaning of the induced gamma modulation represents the translation of the attentional focus in the visual field, a possible interpretation is that the ability of the patients to adequately keep this focus in an appropriate location  is impaired, and constant reorienting processes are needed with a consequent increase in the gamma amplitude. In this case, the gamma band reflects a compensatory mechanism rather than an impaired one.64.A corollary of this interpretation is that MS patients probably need to increase their engagement of alerting and orienting mechanisms to improve their reaction in each trial to relocate their attentional focus as fast as possible. The maintenance of this strategy to compensate for the deficit is probably the cause of cognitive fatigue observed in some cases among MS patients during sustained attention tasksFinally, it is necessary to comment about the difference between evoked and induced gamma activity. Notably, evoked gamma modulation was mainly present for the target stimuli, and induced activity was linked to both stimuli (cue and target). It could be suggested that evoked activity is only related to the relevant stimuli that require a motor response; in contrast, induced activity does not depend on that feature. Unfortunately, the present experiment does not allow further assessment of this issue, and future studies are necessary to disentangle the precise functional role of both gamma modulations in this respect.66 due to the demyelination was not observed in our data. However, other studies did not find differences in early visual ERP latency between HCs and patients with MS67.With regard to evoked activity that may mainly represent the alpha content of the early ERPs (P1 and N1), there was no difference between groups for the latency parameter. Therefore, it could be suggested that the described slowing in the latency of early ERPsin MS patients68 and N1-P2 complex70among MS patients. Our results are in agreement with these studies in terms of both the cue and target early evoked responses. This decrement in the amplitude could reflect that a lower number of neurons were synchronized to elicit the evoked response but at the same time preserved their connectivity, which maintained the appropriate latency. Other authors have interpreted similar results as an impaired mechanism of synchrony in the neural generators of the early visual processing in MS group71.On the other hand, with regard to the amplitude parameter, previous studies have found lower amplitudes in the P1 component25. This reduction of alpha synchronization observed in our study could also be in accordance with the findings of previous studies in which a decreased alpha band was linked to anticipatory attention (orienting network) with respect to the arrival of the target in a cue paradigm26.With regard to the induced alpha activity, a clear negative trend was observed in the CC and SC conditions in the expectancy interval. It has been suggested that the onset of alpha desynchronization starting at approximately 300 ms is a sign that the influence of the alpha band on cortical activity was disappearing and that other task-relevant processes/bands took place47. These authors indicated that this desynchronization could be related to the abrupt onset of the cue that engages an alerting response. However, in our study, the cue factor results from ANOVA indicated that the CC condition reached its highest value before the SC condition. We suggest that the reason for this difference may be the different information content involved in the two cues. The CC condition provides timing information, while the SC condition adds spatial information to the timing expectancy. The more information is added, the more latency is necessary to reach the maximum desynchronization. Previous studies have demonstrated in the time domain of EEG [contingent negative variation (CNV)] that the more spatial and timing information was given in the cue, the higher the amplitude of the CNV72. However, the CNV trend is maintained until the target stimuli are presented (at least in a one-second SOA), but induced alpha modulation reaches maximum negativity and starts recovering to the baseline level before the target appears. This last modulation seems to be more related to a specific mechanism in a determined time interval than to a sustained preparatory state for incoming stimuli.In the particular case of alpha modulations during the ANT, a study found a decrease in alpha activity (not distinguished between phase or nonphase) related to the alerting network from 200 to 450 ms after the onset of the cue26or maintaining attentional focus73.This difference between the CC and SC conditions observed in both alpha bands (low and upper) could indicate that both general  and specific (orienting) attentional mechanisms are recruited in the expectancy interval. In particular, some authors have suggested that the decrease in the upper alpha band may be related to anticipatory attention18, which supports that evoked activity and induced activities, can be disentangled and represent different cognitive mechanisms. Moreover, phase analyses showed that single trial-induced phases displayed random values that were not concentrated in the evoked phase values  or was due to a reduced number of neurons operating as it was suggested for the cue processing. Further research is needed to clarify the precise factors involved in the decrement of early evoked activity in MS pathology.In the target response interval, alpha-evoked activity showed no differences in the latencies of the responses for the target in all cue conditions . On the other hand, the amplitude showed a reduction in the MS group suggesting an impaired processing of the target stimuli. Some studies have reported that the early components (P1/N1) in a cueing paradigm are enhanced for the target stimuli as the result of sensory preparationWith regard to the induced activity, different modulations were found for target stimuli depending on the preceding cue. In the NC and CC conditions, there was no difference in the amplitude between experimental groups. However, an increase in the latency of the maximum negativity for both cue conditions was observed in the MS group. It seems that patients performed a first alpha desynchronization in the first valley (0–350 ms) but not well enough in terms of efficient cognitive processing (lower amplitude) and rebounded with a second valley that reached a better level of alpha desynchronization.43.Moreover, the SC condition did not show a statistically significant delay for MS patients, with a slightly higher amplitude in the first than in the second valley. However, the presence of a second valley can be observed in the SC condition for MS patients compared with controls, suggesting that a rebound could be present in some trials. These rebounds in the decrease in the alpha modulation could reflect an effort from MS patients to compensate for cognitive impairment, as has been suggested in previous studies18 that suggested an impairment in the alerting and orienting networks in MS patients. However, diverse neurophysiological parameters suggest a more complex interpretation of the causes for cognitive impairment in this MS sample.In summary, the current behavioral results supported previous studies73. First, this hypothesis could explain why the evoked activity for cue and target stimuli is reduced considering that MS patients are not placing their attentional focus precisely in the relevant locations for the experiment. Second, an increased induced gamma modulation in MS patients could reflect a higher need of reorienting in both cue and target presentations. However, the latency of the gamma peak was not delayed in the MS group, which suggests that the relocation of the spatial attentional focus is not enough to justify the delay in behavioral responses.Our hypothesis after the analysis of the current experiment is that MS patients exhibited an impairment to maintain attentional focus during the experiment, as has been suggested in previous studies79. Our conclusion is that MS patients have difficulties in maintaining an appropriate “spatial-object” attentional focus. As it has been pointed out in a study with ADHD children80, an impaired attentional performance is not caused necessarily by the orienting process itself but by the difficulty in maintaining the relevant information demanded for the task  during the preparation interval and until the target processing stage. The maintenance of an attentional focus to perform the ANT could also be related to working memory mechanisms83. Considering this link between the two processes, diverse studies have described working memory impairments in cognitive tasks in patients with MS85.This last evidence leads us to consider that the impairment in the maintenance of attentional focus not only involves its spatial properties but also involves its object properties. Multiple studies have analyzed the interaction between both determinants of the stimuli  and described its neural sourcesThe correlate for the difficulty in the processing of object properties of the target could be represented by the rebounds in the induced alpha modulation. However, this impaired mechanism is a consequence of the poor maintenance of the spatial-object attentional focus in MS patients. The precise neurophysiological parameter for the specific impairment in the maintenance of the spatial-object attentional focus has not been found in the present experiment and future studies are needed for its identification.In any case, the study of the nonphase activity in EEG signals has exhibited hidden cognitive mechanisms (compensatory and impaired) for the traditional “evoked studies” that can complete our knowledge of the neural basis of cognitive impairment in MS patients and other pathologies.85. To be eligible for inclusion in the study, patients were required to be under an EDSS of 6  and avoid exclusion conditions: clinical relapses in the last month; presence of comorbid neurodegenerative or psychiatric disorders; severe signs of depression; history of substance abuse; head trauma; vascular diseases and seizures; significant upper limb impairment; or visual acuity or field deficits.Twenty-six patients with a relapsing–remitting MS (RRMS) form were recruited in the Multiple Sclerosis Unit of Hospital Universitario Virgen Macarena . The definitive diagnosis was made by a neurologist, according to McDonald's criteriaThe MS sample was formed by 16 women and 10 men, with an age range of 29–45 years ; one of the patients was left-handed. An HC group was selected with sociodemographic variables matched to those off the MS group ; one of the HCs was left-handed. All the healthy subjects were declared to be free of neurological conditions.This study was carried out in compliance with the Helsinki Declaration. All participants signed informed consent before their inclusion, and the protocol was approved by the Ethics Committee of the University of Seville .87 and the Symbol Digit Modality Test (SDMT)89. Cognitive impairment was identified using the normative scores developed by Sepulcre54. The Beck Depression Inventory (BDI-II)91 was used to assess symptoms of depression.Neuropsychological and depression assessments of the patients were performed by well-trained psychologists blinded to the study goals. The attention and speed of information processing were evaluated through the Paced Auditory Serial Addition Test, 3s (PASAT-3s)11  and presented on an LCD screen. An adaptation of the ANT was used for this study11 Fig. A.Both cuIn the target response interval, the participant had to respond to stimuli formed by 5 arrows pointing to the left or right side. The presented stimuli could be congruent (C) when the central arrow (target) was oriented in the same direction as the flankers or incongruent (I) when the flanker arrows pointed to the opposite direction of the central arrow. The target stimulus was presented at a total visual angle of 3.28 on the X-axis and 0.41 on the Y-axis and 0.86 above or below the fixation cross. Congruent and incongruent stimuli were presented in equal proportions. Furthermore, half of the targets pointed to the right and half to the left. The subject was required to respond according to the direction of the central arrow by pressing the left button with the left thumb when the central arrow pointed to the left or by pressing the right button with the right thumb when the central arrow pointed to the right.11 to adapt it for MS patients. The cue duration was 150 ms, and the target stimulation presentation lasted 350 ms. The time between the end of the cue and onset of the target was 1000 ms. Participants had 1000 ms to respond from the onset of the target stimulus. The duration between the end of one trial and the next one was variable . The experiment was divided into two blocks of 144 tests each, for 288 in total. A pause between blocks was proportionate to avoid fatigue in participants. The duration of this pause was defined by the need of the participant but usually did not last for more than two minutes. The total duration of the experimental procedure with an average pause block of two minutes was approximately of 15 min. The presentation of the trials (cue and target pairs) was set in a pseudorandom order.The timing for the presentation of stimuli was modified from the original ones53. No network effects were calculated because diverse studies have concluded that thesevalues can induce erroneous interpretations of the data92.Reaction times and precision percentages were calculated for all conditions. All participants were instructed to respond as quickly and accurately as possible. To analyze differences between groups in specific conditions, a potential general slowing for reaction time in MS patients was corrected following the recommendations of Fernandez-Duque and Black93and amplified with BrainAmp amplifiers   was also applied to all conditions.EEG data were recorded from 58 electrodes (Ag/AgCl) in standard locations of a 10–10 system52.In the case of the induced activity, a temporal spectral evolution (TSE) was calculated with the following steps: identical bandpass filtering in previously defined low and upper alpha and gamma bands performed over EEG epochs, rectifying the signal and finally averaging for all stimuli conditions. After this analysis, a subtraction of evoked activity from the TSE was subsequently performed to calculate the induced response (nonphase activity)51  were averaged independently, filtered for low (8–10.5 Hz) and upper (10.5–13 Hz) alpha and gamma bands (30–45 Hz)  and rectifiedsee Fig. .Figure 695, latency was defined at the electrode with the maximum amplitude observed in a grand average of all experimental conditions and performed for each group. Following these criteria, the evoked gamma activity in the expectancy interval was almost nonexistent in all cue conditions, and induced activity was mainly present in the SC condition and for the interval of 210–225 ms. In the case of the target stimuli, the peaks of the evoked and induced gamma activity occurred in the interval of 175 to 245 ms. Once the intervals were set, calculations of gamma peak latencies were made for each participant. Moreover, the mean amplitude value was exported for the entire intervals defined previously in a matrix of 3 × 7 electrodes that covered the posterior area of the scalp where gamma activity was prominent . Individual values were calculated for each subject of both experimental groups. Amplitude studies were performed as for the evoked activity but in two different time intervals .96. To do so, the trials were filtered in the desired bands , and the Hilbert transform was applied to calculate instantaneous phase.Because of a potential contribution of evoked over induced activity could occur , the induced modulation was checked to ensure that it was truly nonphase locked activity for all bands studied . To achieve this goal, the evoked response was estimated through averaging over trials and then subtracted from each of the individual trialsThe phases of gamma activity were measured at the interval of 210–225 ms  and 175–245 ms  in single trials, which corresponds to the estimated grand average peak interval of the induced response. In the case of the alpha bands, phase calculations were performed in 0–350 ms for low and upper alpha subbands following the same protocol described for the gamma band. Last, the phases of the evoked responses  were calculated by following the same protocol performed for the induced activities and in the same time intervals.A previous exploratory analysis of the data revealed that there were no differences by the “congruency” variable or in its interaction with the experimental group for alpha or gamma modulations. For this reason and to facilitate the following analyses, we collapsed congruent and incongruent values for each cue condition.p > 0.05), all variables were checked for normality. Parametric (ANOVA) or nonparametric tests  were performed to study possible differences in behavioral and neurophysiological variables where appropriate.By means of the Shapiro–Wilk test . The accuracy of the subjects' responses was analyzed applying the Kruskal–Wallis test with the same factors as for the reaction time ANOVA.The analysis of the reaction times was carried out with a two-factor ANOVA: group factor (levels: HC and MS patients) and a cue factor . After correction suggested by Fernández-Duque and BlackTo analyze the latency of evoked and induced gamma activities in the expectancy interval, we performed two independents ANOVAs to compare both experimental groups only for the SC condition. For the amplitude variable, we performed two ANOVAs (evoked and induced) with the following factors and levels: group factor (levels: HC and MS patients); cue factor ; anterior–posterior location factor ; and medial–lateral location factor .In the target response interval, evoked and induced gamma latencies were analyzed separately by ANOVAs including all cue conditions  and for both experimental groups. The amplitude variable was studied with the same factors as described for the expectancy interval.In the case of the analysis of alpha activity (both subbands), in the expectancy interval, evoked and induced latencies were analyzed separately. The two ANOVAs performed had two main factors: “group” (levels: HC and MS patients) and “cue” (levels: CC and SC). The NC condition was not introduced because of a null response of evoked and induced activity due to the absence of cue stimulation. With regard to topographic study, the evoked amplitude was analyzed with an ANOVA with the following factors: group (levels: HC and MS patients); cue factor ; anterior–posterior factor ; and lateral-medial factor . In the case of induced activity, two independent ANOVAs were performed for each time interval  with the previously described factors for evoked activity.In the target response interval, evoked and induced latencies were analyzed separately with the same ANOVA factors as in the expectancy interval, but in this case, all the cues were included in the cue factor . On the other hand, amplitude analysis of evoked and induced modulations was performed with the same factors for the ANOVAs in the expectancy interval but with fewer levels for the anterior–posterior factor  (matrix 3 × 7).p < 0.05. A post hoc analysis of all the possible comparisons was carried out using Bonferroni correction.In all the analyses described above, sphericity was corrected with Greenhouse–Geisser, and a statistically significant result was considered from Supplementary information 1.Supplementary information 2.


The 168 m-thick Shiant Isles Main Sill is a composite body, dominated by an early, 24 m-thick, picrite sill formed by the intrusion of a highly olivine-phyric magma, and a later 135 m-thick intrusion of olivine-phyric magma that split the earlier picrite into a 22 m-thick lower part and a 2 m-thick upper part, forming the picrodolerite/crinanite unit (PCU). The high crystal load in the early picrite prevented effective settling of the olivine crystals, which retain their initial stratigraphic distribution. In contrast, the position of the most evolved rocks of the PCU at a level ~80% of its total height point to significant accumulation of crystals on the floor, as evident by the high olivine mode at the base of the PCU. Crystal accumulation on the PCU floor occurred in two stages. During the first, most of the crystal load settled to the floor to form a modally and size-sorted accumulation dominated by olivine, leaving only the very smallest olivine grains still in suspension. The second stage is recorded by the coarsening-upwards of individual olivine grains in the picrodolerite, and their amalgamation into clusters which become both larger and better sintered with increasing stratigraphic height. Large clusters of olivine are present at the roof, forming a foreshortened mirror image of the coarsening-upwards component of the floor accumulation. The coarsening-upwards sequence records the growth of olivine crystals while in suspension in a convecting magma, and their aggregation into clusters, followed by settling over a prolonged period (with limited trapping at the roof). As olivine was progressively lost from the convecting magma, crystal accumulation on the (contemporaneous) floor of the PCU was increasingly dominated by plagioclase, most likely forming clusters and aggregates with augite and olivine, both of which form large poikilitic grains in the crinanite. While the PCU is unusual in being underlain by an earlier, still hot, intrusion that would have enhanced any driving force for convection, we conclude from comparison with microstructures in other sills that convection is likely in tabular bodies >100 m thickness. The processes involved in creating layered intrusions have recently been the subject of some dispute , termed the Lower Picrite, and the immediately overlying 135 m-thick picrodolerite/crinanite unit (or PCU)—the third and largest magma batch. We used a sub-set of 64 samples from the suite collected by Fergus Gibb and Michael Henderson, now held by the British Geological Survey. Gibb and Henderson  developeDihedral angles at augite–plagioclase–plagioclase junctions were measured in 23 samples from the PCU using a 4-axis universal stage mounted on a J Swift monocular microscope, with a UM32 Leitz long- working-distance objective and a ×10 eyepiece. We report the median values of populations of up to 100 individual measurements of true 3-D dihedral angles in each sample. The 95% confidence intervals about the median were calculated according to the method of Stickels and Hücke .Grain intersections for olivine were obtained from photomicrographs by drawing by hand around the outlines of olivine grains, taking care to distinguish between individual grains within polycrystalline olivine clusters by comparing the photomicrographs with observations using an optical microscope. The scanned line drawings were analysed using ImageJ to calculate the area of each intersected grain. These area values were converted to the equivalent diameter of a circular grain intersection (the Heywood diameter). The size of olivine clusters was determined in the same way. Although the shape of the clusters is highly irregular, these area values were also converted to their Heywood diameters.A measure of the effect of overgrowth of olivine phenocrysts by crystallisation of the interstitial liquid in the crystal mush was made by comparing the actual perimeter of each grain intersection (as measured using ImageJ) with the circumference of a circle with the same area. For perfectly circular grain intersections the ratio of these two values is 1, whereas the ratio for more irregularly shaped grains (i.e. those for which there has been extensive post-accumulation overgrowth) is >1.For simplicity, we report the average size of individual grains and clusters. While the true, 3D, distribution of olivine grain sizes can be obtained from stereological correction of the distribution of 2D grain intersections  diameter, and the choice of which to use depends on the problem under consideration  are generally too altered for detailed microstructural work. In the 18 PCU samples in which the olivine mode was sufficiently low to permit the distinction between different clusters of olivine grains, the Heywood diameters of both individual grains and clusters were obtained. In Table To assess the original size of the olivine grains, the sizes observed in the fully solidified rock were corrected to account for post-accumulation overgrowth of the original phenocrysts during solidification of the interstitial liquid. For this correction  degree of bias because many olivine grains in the Shiant Isles Main Sill form clusters. Those grains in the centres of the clusters were unlikely to have been in contact with interstitial liquid and therefore did not grow post-accumulation. If clustering occurred before overgrowth, all the overgrowth will therefore occur on the outermost grains while those in the centre of clusters will remain the same size. A bias might therefore be introduced if the clustering were not fully random, with large and small grains distributed irregularly within each cluster. We have not considered the magnitude of this effect in the present contribution.The composite sill is dominated by plagioclase, augite, olivine and oxides. Mineral compositional data are presented by Gibb and Henderson , 2006, aGenerally, the later intrusions of composite bodies are emplaced within a pre-existing, partially solidified magma body. The chill zone against the country rocks should therefore only be formed from the first batch of magma. This is certainly the case for the lower boundary of the sill, for which picrite magma is chilled against the country rock  = ϕsed + 0.1(100 − ϕsed), where X is the actual olivine mode in the rock .The compilation of olivine grain size data in the Lower Picrite given in Table 4,3) in the Lower Picrite are shown in Fig. The corrected average olivine grain sizes  with minor analcime, apatite and zeolite  = X − 0.55 L where X is the olivine mode in the fully solidified rock and L is the percentage of olivine that crystallised from the interstitial liquid. For the remainder of the picrodolerite, we assumed first that the amount of olivine crystallised by the interstitial liquid decreased linearly with stratigraphic height to 6 vol.% at the top of the picrodolerite, and that the accumulated pile contained 60 vol.% interstitial liquid.We determined average olivine grain size in the PCU, correcting the results to account for overgrowth during crystallisation of the interstitial liquid in the original accumulation. For the 5 samples in the lowest 10 m of the picrodolerite, we assumed the interstitial liquid crystallised 9 vol.% of olivine and that both olivine and plagioclase accumulated together to form a crystal pile containing 55 vol.% liquid . The original olivine mode, ϕThe average olivine grain size decreases upwards  Table ; Fig. 6aThe average cluster size is similar to that of the average size of individual olivine grains in the lower part of the picrodolerite. Between 38.43 m and 42.40 m stratigraphic height, cluster size increases, coinciding with a morphological transition from clusters formed of loose groups of rounded grains  , the stratigraphically highest sample in which olivine clusters are found is S81/31, at 78.85 m stratigraphic height. This is within the crinanite as defined by Gibb and Henderson , but we While most of the plagioclase in the PCU forms small, randomly oriented grains, plagioclase also forms scattered stellate clusters of large elongate grains Fig. a, b, somThe clusters are not abundant, with a maximum of 2 intersected by any one thin-section. They form two types, the first comprises only plagioclase while the second contains coarse euhedral/subhedral olivines . Commonly associated with the stellate clusters are apparently isolated grains of unusually large plagioclase, commonly containing fluid inclusions and/or distinct breaks in compositional zoning Fig. c. In ourThe stratigraphic distribution of the stellate plagioclase is thus similar to that of the olivine phenocrysts, with a lower zone rich in clusters overlain by a cluster-free zone followed by an uppermost cluster-bearing zone. However, the stellate cluster distribution is offset to higher levels at the base, and to lower levels at the top, of the PCU.The PCU can be subdivided into four distinct regions Fig. . The lowAn issue which must be resolved before a full discussion of the new observations is whether the Shiant Isles Main Sill is a composite intrusion, as advocated by the work of Gibb and Henderson, or whether the stratigraphic heterogeneities are a result of the inflation of the sill by a single batch of magma of progressively changing composition followed by in situ fractionation processes, as suggested by Latypov .cpp  is ~55 m, of which 82% is found at the base. The position of the most evolved bulk compositions in the PCU at 125–130 m stratigraphic height  in the basal 10 m of the picrodolerite therefore suggest that the incoming magma carried a load of 3 vol.% olivine, not the 10 vol.% suggested by Gibb and Henderson .− 3, viscosity 10 Pas, flowing in a 130 m planar-sided conduit, will only be sufficiently low for laminar flow (i.e. below ~103) for flow velocities <0.03 m s− 1. Such low flow rates are unlikely for such a large, laterally extensive intrusion [see, for example, Kavanagh et al. , for aspect ratios up to 4 the reduction in settling velocity is of order 10%  or at the floor itself.If we now consider the olivine in the remainder of the picrodolerite, a further argument against it being part of the incoming crystal load can be constructed by considering the particular case of the olivine at the roof of the PCU. Although Gibb and Henderson  suggesteClusters grown in situ would necessarily have formed by what is variously termed secondary nucleation , and then remained constant during the crystallisation of the crinanite: this is implausible. The hypothesis is also inconsistent with the asymmetry of cluster distribution at the base and top of the PCU (since clusters grown at the roof would have required the same time to form as those on the floor even though they are much closer to the boundary of the sill). The compositional zoning in the clustered olivines Fig.  is also A solution to this conundrum can be obtained, if we consider the possibility that the magma in the PCU convected during olivine growth and accumulation. To assess the likely consequences, we develop the original Martin and Nokes  theory fIf we assume the particle concentration is always sufficiently low to prevent particle interactions, it is well understood that Stokes’ settling in a static  magma leads to the settling of individual crystals at a constant rate. Each size class is deposited at a constant rate, until all the grains of that size class have fallen out of suspension, leading to the abrupt and complete disappearance of progressively smaller size classes upwards in the accumulation. This is not the case for settling from a convecting magma.N crystals per unit volume in a magma chamber of height h, with a roughly uniform concentration everywhere, including at the base of the convecting zone where it transitions to the stagnant boundary layer. In this stagnant layer, the crystals sediment at the Stokes velocity u, so that the concentration falls according to the relation h/u.Following Martin and Nokes, we ignore the possibility of re-entrainment of previously settled material and assume no grain growth of the suspended particles. The theory posits that there are ρ, and the fluid viscosity, η, are constant. We follow Martin and Nokes , the shape of the size distribution remaining in the bulk magma does not change for the sample distribution shown here, but is progressively shifted to smaller grain sizes.Comparison of frequency distributions for grain intersection size (reported as Heywood diameter) demonstrates that the proportion of large grains present in each of the five samples forming the fining-upwards sequence progressively decreases through the sequence Fig. . This prExperimental work demonstrates that a significant particle load can act to damp convection in a system cooled from above, with olivine concentrations as low as 0.5 wt% damping convection in a basaltic system  volume fraction of the settled olivine and spinel decreases to ~25 vol.% at the top of the fining-upwards sequence. While a combination of strong grain cohesion, high liquid viscosity, and the presence of elongate and irregular loose clusters might make it possible to create a random loose packing at such low volume fractions  of the carrier liquid. The relatively high plagioclase:augite ratio in the lower 10 m of the picrodolerite  layer. Assuming a constant solid fraction in the random loose packing, the volume fraction of plagioclase at the top of this modally graded accumulated layer was ~20 vol.% .It is clear that olivine was on the liquidus during the solidification of the PCU. Plagioclase was also on the liquidus and grew as suspended crystals in the magma, either from seeds that didn’t settle during the immediate post-emplacement phase, or from seeds entrained from the floor or roof mushy layers by the convecting magma. It will have formed clusters either by synneusis Vance  or by auThe PCU parental liquid lay close to the 5 kbar olivine–plagioclase–augite ternary eutectic  had escaped the convecting magma by the time the top of the accumulating crystal pile had reached ~ 79 m stratigraphic height. However, the presence of rare clusters of olivine in the vicinity of the Sandwich Horizon shows that the magma from which the crinanite crystallised was saturated with olivine, and was likely to contain many small crystals of olivine in addition to the rare large clusters that remained suspended for  the entire solidification history. Following Gibb and Henderson , we suggThe original crystal cargo of the incoming magma contained large individual crystals and stellate clusters of plagioclase, and these are distributed through the PCU in a manner consistent with our model of settling from a convecting magma. The relatively low density of plagioclase means that the stellate clusters would remain suspended for longer than olivine aggregates of a similar size. They would then start to settle in appreciable numbers later than the olivine, thus accounting for their stratigraphically higher distribution in the upper part of the picrodolerite. It is surprising that they are not abundant in the upper part of the crinanite, since one might expect them to be easily trapped in the upper solidification front, but this might be an artefact of sampling.If we assume all olivine above ~33 m stratigraphic height crystallised on an olivine + plagioclase ± augite cotectic and that all the olivine either settled to the floor or became trapped at the roof until the bulk magma became too crystal-rich to permit crystal segregation, the olivine in the upper 46 m of the picrodolerite and in the upper 10 m of the PCU must have crystallised broadly contemporaneously with much of the plagioclase found between 33 m stratigraphic height and the top of the PCU at 158 m. The 11 vol.% of olivine (corrected for overgrowth) in the upper 46 m of the picrodolerite, together with the 10 vol.% in the upper 10 m of the PCU, and the 6 vol.% olivine in the intervening 68 m of crinanite, suggests that the overall olivine mode crystallising from the incoming carrier liquid that formed the PCU, once it had lost its crystal cargo, was ~8 vol.%, consistent with the calculated mode of olivine that crystallised from the liquid PdolPL1  all large olivine clusters had escaped the convection (at which point the height of the remaining bulk magma was ~70 m) crystal accumulation on the floor was dominated by plagioclase, most likely forming clusters and aggregates with augite and olivine, both of which form large poikilitic grains in the crinanite. The strong asymmetry of the PCU, in which the last horizon to solidify occurs considerably above the mid-point of the intrusion, suggests that significant crystal accumulation occurred on the floor throughout the solidification history.The combination of a stratigraphically gradual reduction in the mass of settled olivines, a coarsening-upwards of the settled olivines, an upwards increase in the extent of clustering of olivine and the extent to which the clusters are sintered, and the presence of large clusters and grains at the roof strongly support crystallisation during convection in the picrodolerite/crinanite unit of the Shiant Isles Main Sill. A preliminary analysis suggests that the spatial variation of grain size in a polydisperse settled accumulation can also be used to distinguish between settling from static or convecting magma. These results point the way towards a resolution of the question of whether crystallisation in any igneous body was dominated by growth of grains suspended in a convecting magma instead of occurring predominantly in marginal solidification fronts.


This project set out to develop an app for infants under one year of age that responds in real time to language-like infant utterances with attractive images on an iPad screen. Language-like vocalisations were defined as voiced utterances which were not high pitched squeals, nor shouts. The app, BabblePlay, was intended for use in psycholinguistic research to investigate the possible causal relationship between early canonical babble and early onset of word production. It is also designed for a clinical setting, (1) to illustrate the importance of feedback as a way to encourage infant vocalisations, and (2) to provide consonant production practice for infant populations that do not vocalise enough or who vocalise in an atypical way, specifically, autistic infants (once they have begun to produce consonants). This paper describes the development and testing of BabblePlay, which responds to an infant’s vocalisations with colourful moving shapes on the screen that are analogous to some features of the infant’s vocalization including loudness and duration. Validation testing showed high correlation between the app and two human judges in identifying vocalisations in 200 min of BabblePlay recordings, and a feasibility study conducted with 60 infants indicates that they can learn the contingency between their vocalisations and the appearance of shapes on the screen in one five minute BabblePlay session. BabblePlay meets the specification of being a simple and easy-to-use app. It has been shown to be a promising tool for research on infant language development that could lead to its use in home and professional environments to demonstrate the importance of immediate reward for vocal utterances to increase vocalisations in infants. VisiBabble used an acoustic analysis approach to identify syllable-like utterances using five of the acoustic landmarks identified by Stevens in phoneme recognition The systems discussed above are all designed as desktop computer activities and have mainly been targeted at older children with delayed speech and language development. With the rapidly growing popularity of mobile devices and in particular electronic tablets, there is a new opportunity to revisit the possibilities of producing an accessible, easy to use tool that encourages vocalizations in infants. There is an acknowledged increase in the engagement of younger infants (under 1 year) with these technologies  and no app currently exists, as far as we know, which requires or allows the infant to initiate the interaction. Producing an app which responds to the vocalisation of the infant empowers them to be in control of the game and learn the contingency between the behavior and the visual response.Infants at risk for ASD and children diagnosed with ASD have atypical babble as regards rhythm parents or researchers with a picture of the language environment of the infant. They do not include a visual interface which can provide the infants with feedback on their own vocalisations on-line. As such, BabblePlay and LENA complement each other, in terms of the information they provide, when they provide it and who can make use of it.The approach taken in this project is quite different from that taken by the creators of LENA . The purposes of the app are twofold: firstly it is intended as a tool for research, whereby the causal relationship between increased consonant production and early language acquisition can be investigated. Secondly, the app is designed to be used directly by families with their infants as a means to promote vocal development. In particular, it can be used to demonstrate to families the importance for infants of receiving feedback on their early vocalisations.1.11)We introduce a new app, BabblePlay, specifically developed to encourage vocal utterances. The app is designed so that infants under a year old can control it, by using their voice to initiate the appearance of moving images on the screen.2)We demonstrate that the app is in good agreement with humans in detecting an infant’s vocalisations as distinct from bangs and other non-harmonic environmental sounds, high pitched squeals and unvoiced utterances.This paper provides the following contributions:We show, using data collected from a feasibility study reported elsewhere, that infants can learn the contingency between their voiced utterance and the app’s response.2This section first presents the background literature which informed the design of the interface to be suitable for the target user and the system aims, followed by a breakdown of the resulting technical specifications of BabblePlay.2.1The target audience of this project in the first instance is typically developing infants between 5 and 10 months old. Future developments will target infant populations at risk of language delay for whom more practice with speech-like vocalisations would be beneficial, e.g., infants at risk for ASD.Canonical babbling typically develops between 6 and 8 months Studies on contingency learning in infants showed that long latencies between the infant’s action  and a resultant visual display led to less effective learning: Millar 2.22.2.1The fundamental frequency range for infants has been identified as between 30 Hz and 2500 Hz 2.2.2Coloured and patterned moving objects with different types of movement were chosen as visual responses to be attractive to the target age group see .Fig. 1Ba2.2.3The app should perform in real-time, or with as short a delay as possible between the infant vocalisation and the visual response. Based on the research on contingency learning discussed in 2.2.4In order to prevent the app from being used as a ‘babysitter’ and replacing real-life interaction between family members, BabblePlay must automatically shut itself off after 5 min.3The audio processing algorithm was originally written in Matlab (2015a) and then implemented as an app which was written in Xcode (10.1) for iOS 8.0.3.1The acoustic signal is received by the integral microphone of the iPad (Audio in) which is processed at 16 kHz sample rate. A 30 s mono channel circular buffer is populated with a 5 ms input latency. A 100 ms buffer then iterates at 50 Hz . This buffer is then divided into 22 blocks of 256 samples with an overlap of 75% which is equal to a hop size of 64 samples/4 ms see .Fig. 2A Features of fundamental frequency (pitch) and amplitude (volume) are extracted from each block. Pitch is calculated using the Yin algorithm 3.2Once initialised, animations appear see , which a3.3In order to facilitate the use of the app for research, a mono audio file (16 kHz sampling frequency) is created of the vocalisations of the infant  as well as a count of the number of vocalizations that the app has identified (i.e. the number of animations that were initiated in that session). The .wav file generated at the end of each session is automatically attached to an email which also contains a record of the timestamped animation initiations. This email is sent to the project research account to allow quantitative analysis. The email is only sent once the ‘send’ button is pressed. Families can choose to delete an email if they do not want the sound file to be listened to by the research team. In such a case, the team is notified (in the next email) that a previous recording has taken place, but that the files were not saved. Families who register an infant on the app can opt in to taking part in the research. If they choose to take part, personal data is sent to the research team including the date of birth of the infant and, optionally, postcode and parental education, alongside audio recordings and vocalisation counts from the app. The baby is identified by a code. If families do not opt into the research no files are sent to the research team.4https://www.york.ac.uk/babbleplay/). In order to generalise across the infant population, controlled testing was needed to test the app’s validity, or its ability to identify the target vocalisations it is intended to detect and respond to, and to ensure that infants could learn to control the app.Initial, informal, piloting with one typically developing six month old infant produced very promising results, with researchers observing that the infant quickly understood the contingency between vocalising and images appearing on the screen  were recorded by BabblePlay in two 5-minute-long trials. In both trials a caregiver and up to two experimenters were with the infants, but the adults avoided interacting with them and did not vocalise. In the solo-play trial the infant played with non-responsive toys and was recorded by BabblePlay in the background, with its screen hidden from the infant. In the experimental trial the infant interacted with BabblePlay  or with a non-responsive video (control group: n = 30).4.2The study produced a dataset for each trial that contained sound files and timestamped counts of the vocalisations which initiated a responses by the app: voiced utterances that do not constitute cries, high pitched squeals or vocal fry. Two human judges were instructed to listen to one third of the sound files, those produced by the last ten infants seen in each group. That amounted to 40 5-minute recording sessions, totalling 200 min of audio. The judges counted infant vocalisations that adhered to the target criteria. Because humans may count a string of syllables as several vocalisations while the app might count them as a single vocalisation, or vice versa, we did not expect the numbers produced by the app and the humans to be the same, but rather, we expected their rankings of some infants as high vocalisers and others as low vocalisers to show positive correlation. The results see  show tha4.3The infants in the experimental group significantly increased their vocalisations throughout the app trial, such that on average only about a third (0.36) of their vocalisations were produced in the first half of the trial and almost two-thirds (0.64) in the second half. In contrast, the control group did not increase their vocalisations in this way, but produced half (0.52) of their vocalisations, on average, in the first half of the trial and half (0.48) in the second. This indicates that infants in the experimental group were indeed learning the contingency between their vocalisations and the animations appearing on the screen, and were motivated to vocalise more as the trial progressed, whereas the control group were not . However, as long as a child has begun to produce canonical babble, then we expect any increase in volubility to be accompanied by an increase in consonant production . The intention is to further develop the app to include the representation of more features of the vocalisations in the visual feedback (e.g. pitch), and to distinguish between types of vocalisations . Our long-term aim is to build an app that responds differentially to different consonant sounds. This presents a significant technological challenge which will be approached by utilising a combination of techniques including implementing Steven’s Landmark’s approach together with neural networks.6This paper describes the development and validation of an iOS app, BabblePlay, which provides a visual reward for vocal utterances made by an infant in real time, ignoring high pitched screeches, very low-pitched vocalisations and environmental noises. There was good agreement between the number of vocalizations identified by the app and two human judges in 40 BabblePlay recordings. The results of a feasibility study with 60 typically developing infants indicate that the target population can learn the contingency between their vocalisations and images appearing on the screen in a single 5-minute BabblePlay session. This project illustrates the potential for utilising electronic tablet-based games for infants under one year of age, both as a tool for research into infant language development, and for use in the home or in professional environments to demonstrate the impact of immediate feedback for increasing vocalizations in young infants.Wellcome trust, and an EPSRC Impact Accelerator Award.This work was supported by a C2D2 grant part funded by The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.