Like in solid cancers, the process of dissemination is a critical feature of disease progression in the blood cancer multiple myeloma. At diagnosis, myeloma patients have cancer that has spread throughout the bone marrow, with patients with more disseminatory myeloma having worse outcomes for their disease. In this review, we discuss the current understanding of the mechanisms that underpin the dissemination process in multiple myeloma. Furthermore, we discuss the potential for the use of therapies that target the dissemination process as a novel means of improving outcomes for multiple myeloma patients.Multiple myeloma (MM) is a plasma cell (PC) malignancy characterised by the presence of MM PCs at multiple sites throughout the bone marrow. Increased numbers of peripheral blood MM PCs are associated with rapid disease progression, shorter time to relapse and are a feature of advanced disease. In this review, the current understanding of the process of MM PC dissemination and the extrinsic and intrinsic factors potentially driving it are addressed through analysis of patient-derived MM PCs and MM cell lines as well as mouse models of homing and dissemination. In addition, we discuss how patient cytogenetic subgroups that present with highly disseminated disease, such as t, t and t, suggest that intrinsic properties of MM PC influence their ability to disseminate. Finally, we discuss the possibility of using therapeutic targeting of tumour dissemination to slow disease progression and prevent overt relapse. Multiple myeloma (MM) is an incurable haematological malignancy characterised by the uncontrolled proliferation of clonal malignant plasma cells (PCs) in the bone marrow (BM) . WorldwiDuring initial disease development, malignant clonal PCs establish themselves in BM niches that support their growth . MigratiMGUS and smouldering MM are largely asymptomatic precursor diseases characterised by the presence of clonal PCs in the BM in the absence of evidence of end organ damage that is characteristic of MM and, notably, in a lack of multiple MRI-detectable tumours . StudiesIn this review, we will discuss the current understanding of the mechanisms that underpin MM PC dissemination. Furthermore, we will discuss how this knowledge could be used to develop novel therapeutic strategies to delay disease progression and treat high-risk MM patients.Similar to the process of solid tumour metastasis, the dissemination of MM PCs is associated with a loss of their adherence to cells of the BM microenvironment that favours MM PC retention, allowing the cells to exit the niche. The tumour cells must then undergo trans-endothelial migration, mediated by chemoattractants and adhesive interactions, and intravasate (move from the BM into the bloodstream) where they are carried to a secondary site. In order to home to new BM sites, the tumour cells must arrest on the BM endothelium and extravasate (move out of the blood and into tissues), following chemotactic factors produced by BM cells. The final stage of MM PC dissemination is associated with the colonisation of new BM sites which supports tumour cell growth. The following sections will describe the molecular mechanisms that are involved in MM PC dissemination, focusing on both the intrinsic properties of the MM PCs that support their dissemination, as well as the extrinsic stimuli that drive this process.BM mesenchymal stromal cells (BMSCs) are a critical component in the BM niche that supports the growth of MM PCs. Adhesion of MM PCs to BMSCs, and extracellular matrix (ECM) components that are secreted by these cells, is a crucial mechanism by which MM PCs are maintained within the niche . BindingThe adhesion of MM PCs to BMSCs and ECM can be enhanced by exogenous secreted factors which induce rapid cytoskeletal remodelling and conformational changes in integrins, thereby increasing adhesion ,27,28. TIn order to be released from the BM and enter into the circulation, MM PCs must overcome the aforementioned adhesive interactions that act as a strong BM retention signal . While tRelease from the BM niche may also be facilitated by signals from the micro-environment . The BM In order to undergo haematogenous dissemination, following release from the BM stromal niche the MM PCs need to migrate towards the vasculature, and then invade and traverse through the basement membrane and the endothelium to enter the blood stream . MM PCs BM endothelial cells (BMECs) are sources of secreted factors that are known chemoattractants for MM PCs, which may encourage dissemination from the primary tumour site towards the vasculature . ConditiOnce in the blood stream, MM PCs travel in the circulation until they reach a distant site where, in response to local chemoattractant factors, they adhere to the endothelial layer and then extravasate and migrate to a new BM site .MM PC adhesion to BMECs is a critical process which enables subsequent extravasation from the vasculature. In the trafficking of lymphocytes, initial reversible adhesive interactions lead to loose “tethering” of the cells to the endothelium, following which the lymphocyte rolls along the endothelium, allowing it to respond to local chemokines which provide the stimulus for extravasation and homing into the BM  , t and t, and the incidence of elevated circulating PCs or PCL  occurs in approximately 10% of newly diagnosed MM patients ,113,131.onal p53 . There ional p53 , althougmination . In suppmination . AlthougOne of the defining features of symptomatic MM is the presence of MM tumours at multiple sites in the BM . In overThese studies suggest that therapies which target key processes involved in MM PC dissemination may be useful to delay disease progression or as a maintenance therapy to extend progression-free survival following frontline therapy. To this end, studies suggest that therapeutic targeting adhesion molecules or chemokine receptors may be able to inhibit the ability of MM cells to egress from or to home to the BM. For example, selective blocking of adhesion molecules involved in the adhesion to endothelium, such as integrins and N-cadherin, have been shown to inhibit homing and thereby decrease subsequent tumour burden following intravenous injection of tumour cells in mouse models of MM ,65. AddiAn alternative approach could be to therapeutically target hypoxic MM cells before they disseminate. Evofosfamide (TH-302), a DNA alkylator designed to be selectively activated under hypoxic conditions, has been shown to cause apoptosis of MM cell lines when cultured under hypoxia in vitro and to inhibit MM tumour development in vivo ,139. In In conclusion, this review has highlighted the current understanding of the processes involved in MM dissemination. Some key outstanding questions include: Are there environmental factors other than hypoxia that drive dissemination/mobilisation? Is underlying subclonal heterogeneity leading to mobilisation of specific individual subclones during dissemination? What are the features of the BM microenvironment that support the homing and subsequent growth of MM PCs at specific niches? A greater understanding the process of MM PC dissemination may allow the identification of novel therapeutic targets that could improve outcomes for MM patients, especially for the prevention of disease progression and relapse in high-risk patients.


The intentionally simplistic approach to optimised testing strategies presented here could be used beyond the assessment of biocides and plant protection products to gain efficiencies in the safety assessment of other chemical groups, saving animals and making regulatory testing more time- and cost-efficient.This paper outlines a new concept to optimise testing strategies for improving the efficiency of chemical testing for hazard-based risk management. While chemical classification based on standard checklists of information triggers risk management measures, the link is not one-to-one. Toxicity testing may be performed with no impact on the safe use of chemicals . Each hazard class and category is not assigned a unique pictogram and for the purpose of this proof-of-concept study, the level of concern for a chemical for the population and the environment is simplistically considered to be reflected by the hazard pictograms. Using active substances in biocides and plant protection products as a dataset, three testing strategies were built with the boundary condition that an optimal approach must indicate a given level of concern while requiring less testing (strategy B), prioritising new approach methodologies (strategy C) or combining the two considerations (strategy D). The implementation of the strategies B and D reduced the number of tests performed by 6.0% and 8.8%, respectively, while strategy C relied the least on  Although testing is not explicitly requested for the purpose of classification and labelling, it is conducted under other regulatory programmes, which often indirectly leads to risk management based on classification and labelling.In the European Union (EU), the manufacture, import, distribution, use and disposal of chemicals is regulated by a complex interplay of more than 40 pieces of legislation . HoweverTraditionally, both the hazard-based and risk-based regulatory approaches are established on toxicity and ecotoxicity data that involve animal testing. While this historical precedent is often seen as a barrier for the uptake of non-animal methods , there ae.g. when the substance is also subject to an authorisation scheme such as under the Biocidal Products Regulation (BPR) or the Plant Protection Products Regulation (PPR), or because there is a specific concern flagged for the use of the substance.The CLP Regulation is based on the GHS  and its The more than 40 EU legal acts on the authorisation and use of substances and mixtures all refer to the classification criteria as defined in the CLP Regulation. The resulting hazard-based classifications have legal consequences on the subsequent risk management . For exaSpecific testing strategies apply to gather, or generate, data to meet the classification criteria addressing the different hazard classes and categories. According to the current testing strategy for biocides and plant protection products, active substances must undergo toxicity evaluation for each of the hazard classes independently  , there iThe aim of this paper is to (1) provide an overview of the hazard classes distribution of a selected, extensive dataset and describe the current testing strategy, (2) illustrate how different testing strategies can be optimised with the boundary condition of indicating the same level of concern, and (3) discuss the results obtained with regards to their applicability beyond the dataset.This study introduces a new concept and is intended as a thought-starter for developing more efficient, but equally effective, classification and labelling of chemicals as the basis for hazard-based risk management. Ultimately, optimised testing strategies have the potential to significantly reduce the use of experimental animals, and make regulatory testing more time- and cost-efficient.22.1Active substances in biocidal products and plant protection products were selected as the dataset to establish new testing strategies. Under the current EU legal framework, data are required for most toxicity endpoints for their harmonised classification. Consequently, the resulting CLP classification based on complete datasets evaluated by expert panels can be considered robust. The following definitions are used: a hazard class refers to the nature of the hazard , a hazard category refers to the hazard severity within a hazard class, and hazard statements are assigned to a hazard class and category to describe the nature, and, where appropriate, the degree of the hazards .A retrospective analysis of hazard classification and labelling of all active substances in biocides and plant protection products in the EU was conducted. All approved biocidal active substances were retrieved from the ECHA database . The Claggplot2 package.Data analysis was conducted using R Studio (version 3.6.1). To map the hazard classes of the active substances in the dataset, plots were drawn using the 2.2i.e. parallel testing for all hazard classes) is named testing strategy A.Information on the hazards identified using the classification criteria of the CLP Regulation is communicated through specific labels  with the aim to protect human health and the environment . For thei.e. B, C, or D), a two-step optimisation was carried out .Irrespective of the testing strategy developed , skin corrosion/irritation (GHS05 and GHS07), serious eye damage/eye irritation (GHS05 and GHS07) and specific target organ toxicity – single exposure (GHS07 and GHS08). Skin sensitisation is the only hazard class which triggers GHS07 alone. Consequently, GHS07 was ranked as the last pictogram in the optimised testing strategies.For the first step, the pictograms were ranked based on two conditions. Article 26 of the CLP Regulation  states ttegories . This isin chemico, in vitro and in silico approaches were identified (Table 2 in Supplementary Information). The exact number of animals used for each hazard class could not be quantified because of the multiple OECD TGs available for each hazard class and the unknown number of animals used for each OECD TG. The report of the European Commission on the use of animals for scientific purposes .For the second step, the hazard classes triggering each pictogram were ordered according to the goal of each testing strategy. Testing strategy B minimises the number of tests performed. Active substances in the dataset classified for each hazard category (or group of categories) were counted for each pictogram. The most prevalent hazard classes for each pictogram were prioritised to limit the number of tests performed: once a pictogram is triggered, further testing is not necessary. Testing strategy C prioritises the use of NAMs over animal testing. All available OECD TGs were listed and attributed to each hazard class according to the BPR, the PPR and specific integrated approaches to testing and assessment when relevant. The OECD TGs relying on purposes  and the Testing strategy D combines testing strategies B and C to find a compromise between reducing the number of tests performed and using experimental animals.33.13.23.2.1skin sensitisation can be performed. Pictograms GHS05 and GHS06 are ranked at the same level, but both are placed before pictogram GHS08 because classification for specific target organ toxicity – single exposure relies on human data and animal experiments from acute toxicity studies and skin corrosion/irritation studies , GHS07 is ranked last for all testing strategies in view of the precedence rules of the CLP Regulation  and beca studies . The finspecific target organ toxicity – repeated exposure ranks first for GHS08 because it is the most prevalent  differs for each testing strategy . In linerevalent . This meubstance , on in vrst tier  and on din chemico, in vitro, in silico, or in vivo) to evaluate each hazard class. For instance, specific target organ toxicity – repeated exposure is ranked first in the GHS08 group  even though it relies on animal testing. On the other hand, prioritising hazard classes for which new approach methodologies are available (testing strategy C) does not efficiently reduce the number of tests performed. In this dataset, few active substances are classified for aspiration toxicity and mutagenicity: evaluating them first does not significantly reduce the number of tests to be performed.Despite reducing the number of tests performed, testing strategy B does not necessarily limit the use of experimental animals because it does not take into account the method type  and the number of animal tests required (testing strategy C) was also considered (testing strategy D).aquatic toxicity - chronic should come first because it is more prevalent than aquatic toxicity – acute . Because of the interdependence of the routes of exposure for acute toxicity, these hazard classes were not ranked. Indeed, according to BPR and PPR, while acute toxicity – oral should always be reported, testing for acute toxicity – dermal and inhalation depends on the exposure scenario and waivers exist. Overall, the implementation of optimised testing strategies B and D reduces the number of tests performed on the full dataset from 21,045 to 19,185 (in the case of B) and to 19,778 (in the case of D), representing a decrease of 8.8 % and 6.0 % respectively (1860 and 1267 fewer tests) (Table 4 in Supplementary Information).The number of substances tested for each hazard class and each testing strategy was counted to quantitatively evaluate and compare the three alternatives . AccordiSince testing strategies B, C and D were built with the boundary condition that they must indicate the same levels of concern, the distribution and the frequency of the pictograms triggered across the dataset remain the same.4Current approaches to regulatory testing are generally based on standard checklists of information requirements which underpin both hazard-based and risk-based approaches to risk management. In the case of biocides and plant protection products, most of the tests conducted for the purpose of hazard classification also support risk assessment. In this paper, we focus specifically on the hazard-based approach. While the classification of a chemical triggers risk management measures, the relationship between hazard classification and risk management is not a one-to-one relationship. This has the consequence that many tests will have no impact on the subsequent risk management. In other words, more information on a chemical does not necessarily result in more protection. Therefore, testing strategies can be optimised by understanding when additional data do not influence the measures for chemical safety. The idea of waiving specific toxicity studies on a case-by-case basis is not uncommon in regulatory practice but could be made more systematic and efficient.This study defines and evaluates three optimised testing strategies for improving the efficiency of classification and labelling while indicating the same levels of concern in a given dataset. Testing strategy B reduces the number of tests performed by 8.8 % (1860 tests). Testing strategy C prioritises the use of NAMs, thereby saving animals. Testing strategy D is a compromise between B and C (reduction in number of tests by 6.0 %).The proposed ranking of the pictograms in the optimised testing strategies is based on precedence rules and depends solely on the conditions set in the CLP Regulation . Similarly, the order of the hazard classes in testing strategy C depends on the method type and is independent of the dataset. In contrast, the order of the hazard classes in testing strategies B and D originates from the distribution of hazard classes in the dataset .Other criteria than the overall number of tests performed and the use of experimental animals could have been chosen to develop the optimised testing strategies. For example, the cost of the assays performed for each hazard class, their duration, and complexity or criteria related to the animals such as the severity of the tests required or the species involved could have been selected. A rigorous estimation of the number of animals used for toxicity testing of chemicals would be a challenge, subject to several uncertainties. Considerably more work would therefore be needed to provide quantitative evidence of the animal reduction benefit of new approach methodologies and optimised testing strategies.in vivo. Based on this hypothesis, quantitative structure-activity relationship (QSAR) models and read-across are applied in a regulatory context to predict physical or chemical properties of compounds and their specific hazards , such strategies have proved useful to gain efficiencies for regulatory decision making on chemicals by taking advantage of existing information. Data gaps can be identified after the gathering and evaluation of all existing information and the relevant data necessary to fill the gaps can be obtained while prioritising non-testing and  testing . SimilarOptimised testing strategies can also be used to identify where the development and the implementation of NAMs would have most impact. The availability of non-animal tests for early hazard classes will significantly reduce the use of experimental animals, and will potentially make regulatory testing more time- and cost-efficient.specific target organ toxicity – single exposure, resulting from a single exposure to a chemical, and carcinogenicity, related to exposure at lower doses but over a longer period, trigger the same pictogram GHS08. In reality, pictograms are not the only descriptors reflecting the level of concern for the population and the environment. However, the intention here is not to propose a re-design of the GHS, but rather to emphasise that additional information on chemical properties does not necessarily translate into a higher level of protection. This means that efficiencies can be gained in the testing needed to indicate a given level of concern, at least within a hazard-based risk management approach. We did not investigate how efficiencies could be gained in the risk-based approach, but other studies have shown that not all of the toxicity tests routinely conducted are actually used to derive the point of departure for risk assessment (This proof-of-concept study is intentionally based on a simplistic approach using pictograms as a starting point for optimising testing strategies. The GHS labelling system is hazard-based, and as such the same pictogram can group together endpoints with different exposure scenarios. For example, sessment .The dataset used in this study can be considered robust because data are required for most toxicity endpoints and are evaluated by expert panels for the harmonised authorisation of active substances in biocides and plant protection products. However, due to the severe restrictions on active substances with carcinogenic, mutagenic, and reprotoxic properties, the dataset used in this study contains few CMRs.Although the optimised testing strategies developed here are based on specific datasets, it is also recognised that no single testing strategy is applicable to all contexts of use. Important considerations for defining testing strategies include, for example, the exposure scenario of interest, the need to address specific health or environmental concerns, the availability of hazard information, regulatory options for generating new data, as well as economic and animal welfare considerations. Nevertheless, the concept of optimised testing strategies has the potential to be applied to other chemical groups, including chemicals regulated under REACH to support waiving of additional testing to fulfil data requirements. Even though this work was based on data from European sources, testing strategies could be elaborated similarly in jurisdictions of any country based on the GHS. In general, there is a need to improve efficiencies in the assessment process, irrespective of the decision-making context. This work is thus intended as a proof-of-concept and thought-starter for developing more efficient, but equally effective, safety assessment approaches.The scientific output expressed does not imply a policy position of the European Commission.The authors report no declarations of interest.


A number of resources, every year, being spent to tackle early detection of cardiac abnormalities which is one of the leading causes of deaths all over the Globe. The challenges for healthcare systems includes early detection, portability and mobility of patients. This paper presents a categorical review of smartphone-based systems that can detect cardiac abnormalities by the analysis of Electrocardiogram (ECG) and Photoplethysmography (PPG) and the limitation and challenges of these system. The ECG based systems can monitor, record and forward signals for analysis and an alarm can be triggered in case of abnormality, however the limitation of smart phone’s processing capabilities, lack of storage and speed of network are major challenges. The systems based on PPG signals are non-invasive and provides mobility and portability. This study aims to critically review the existing systems, their limitation, challenges and possible improvements to serve as a reference for researchers and developers. Cardiovascular diseases (CVDs) and other heart abnormalities are some of the leading causes of death around the globe. These cardiac abnormalities caused 29.6% of total deaths worldwide in 2010 . AnotherOnline resources  reveals Analysis of ECG using smartphoneRecording Visualization systemsAnalysis of ECG on serverAnalysis of ECG on smartphone2.Analysis of PPG using smartphoneWe have divided this review into two significant parts where the first one describes the smartphone-based systems that detect heart diseases and abnormalities by analysis of ECG, whereas the second group measure cardiac parameters and detect abnormalities by the analysis of PPG. The first group is further divided into three subcategories.The first subcategory of ECG based systems consist of those early and lately systems that focus on the recording of ECG signals using built-in sensors of a smartphone or other wearable sensors. After the recording, data is sent to the smartphone using wireless transmission technologies such as infrared, Bluetooth, or other radio transmission techniques. These digitized ECG signals are then visualized on PDAs or smartphone screens for analysis. The patient can view the signals and send them to the medical professional/cardiologist for analysis. Unfortunately, the major drawback of these systems i.e., abnormality detection, is still a manual task. It is a time-consuming procedure that is not tolerable in the case of heart diseases. To make the abnormalities detection automatic, researchers have developed systems that fall in the second subcategory. These systems are developed as a client-server infrastructure where smartphone acts as a client. It receives signals from sensors and transmits them to a server via Wi-Fi, GSM, 3G, or 4G. These servers are programmed with ECG analysis algorithms which detect an abnormality and send back the report/alert to patient and doctors. Though these systems make the analysis automatic, a significant drawback is the lack of real-time feedback in case of abnormality detection. Additionally, the traffic on the transmission medium, high cost, and optimum performance of the network and server are always necessary for the system to work. These all problems are addressed in final and third subcategory where ECG signals acquisition, processing, abnormality detection, and generation of alert is performed on the smartphone. This type of system provides continuous analysis, in-time detection of abnormalities, real-time feedback in the form of an alert to patient, caretaker, and doctor.A general representation of these systems is presented in Fig. Electrocardiography is the golden standard to record and measure the electrical activities of the heart for a period of using electrodes. The graph of these voltages and time for which they are recorded referred to as Electrocardiogram (ECG). ECG provides a pattern of depolarization and repolarization of heart muscles during each heartbeat . The firTraditionally, cardiologists analyze the graph of ECG and detect abnormality with the reference of amplitudes and frequencies of these waveform points. In this digital era , the acqThe era of advanced digital smartphones played a vital role in the development of a complete and automate diagnosis system with the help of seamless integration with low-power, integrated, lightweight, and wearable sensors , 35. ThiThe smartphone is responsible for receiving signals from wearable sensors and transmit them to a server for analysis. Whenever an abnormality on heart function is detected, sever generates an alert/alarm and sent it back to the smartphone. Some scientific works of this group also implement an alarm mechanism that forward alerts to the caretaker of patient and doctor/ambulance along with the location of the patient. Figure Smartphone Based Processing of ECG This section reviews the systems that continuously monitor cardiac health using a smartphone. These systems can be invasive or non-invasive. The non-invasive diagnosing and follow-up of heart diseases need dependable arterial function measurements from ECG . BiomediHeart Rate (HR) is an essential and informative cardiac parameter that can early diagnose many upcoming abnormalities . The anaA smartphone-based system integrated with web application process ECG signals using the Pan-Tompkins algorithm on the smartphone. The HR of the patient and other arrhythmias are detected using the R-R interval of the ECG waveform. The mobile application performs the alerting function in case of abnormality detection. It sends messages to the patient, a relative of patient, doctor, nearby hospital within the range of 5 KM and also provides the best route for an ambulance using Google services using mobile cellular network . Figure Another Hand-Held Device (HHD) based system receives ECG signals from sensors using RF-Radio transmitter and process them. If an abnormal cardiac condition is encountered, the patient will be informed via a clinical alarm station (CAS) . FurtherTraditionally, ECG sensors are attached to the chest of the subject to record ECG. It is necessary to introduce such design, which contains more likely the accessories we wear in our everyday life such as jewelry and watches. To tackle this problem, a continuous cardiac monitoring system was designed in the design of a necklace connected wirelessly to a smartphone . This syPhotoplethysmography (PPG) is a non-invasive technique that has many clinical applications such as to measure changes in blood volume, monitoring of Blood Pressure (BP), cardiac output, oxygen saturation, Heart Rate , and manBlood Pressure (BP) is another physiological parameter along HRV which can be used to predict cardiac abnormalities. These non-invasive smartphones based systems also work in this field and estimate BP, along with many other physiological parameters. A smartphone-based system was developed to estimate BP from PPG signals using Artificial Neural Network (ANN) . The sigPPG signals captured using Nexus 5 Android phones were processed according to this model, and implementation of K-means clustering and ANN proved that it increases the BP estimation accuracy. The smartphone-based systems which record video PPG signals using standard camera can also have very noisy signals. Finite State Machine (FSM) based approach was presented, which estimates the quality of signal before the calculation of heart rate and reject the input if the video segments are too noisy for fair output calculation . AlgoritThe first section of the paper reviews the smartphonebased systems which digitalized the whole procedure. They can record ECG using wearable sensors and display it on the screen of a smartphone or any other PDA. The cardiologist can analyze these signals and diagnose abnormalities. Few of them provide telemedicine facilities for interaction between doctor and patient. The main limitation of these systems is that the diagnosis or abnormality detection process is still manual. What if the cardiologist is not available, then the systems are not effective at all. This problem was addressed by automating the detection of abnormalities using ECG processing algorithms. The signals are transmitted to a server where the abnormality is detected by analysis. Though the procedure is automated, it required much time and the optimal performance of transmission technologies. The time is a more crucial factor in the case of heart diseases, so there should be such a mechanism that alerts the patient in minimum time. So, the systems presented in section 1.3 came into existence and addressed many of these problems. The ECG acquisition, processing, and alert generation are performed locally on the smartphone. The pros and cons of these systems are presented here.The enhanced sensors, processing capabilities, and wireless transmission of data encourage researchers to develop smartphone-based healthcare systems. The mobility of the patient is a major concern of these days’ healthcare systems, which is achieved by smartphonebased cardiac monitoring systems. These smartphones based system provides ambulatory monitoring and real-time abnormality detection. It is an effective way to minimize causalities by early detection of abnormality. The patient can walk around freely in their homes and workplaces while being monitored continuously. Additionally, alarm/alert systems enable patients, caretakers, and doctors to address the abnormality immediately. The developing countries, which have medical facilities at a very distance, can take more benefit from these systems. People have to travel a lot for a cardiac check-up, which can be eliminated or minimized using smartphone-based monitoring systems. The aged and older people who cannot visit the hospital conveniently can now be monitored from their own homes. Telemedicine can provide healthcare knowledge from a distance using smartphones. A comparative analysis of these three types of ECG analysis systems is presented in Table These systems minimize the resources  which have been spent on the detection of cardiac abnormalities. Tough the advantages and benefits of these systems are very prominent, but some issues need to be addressed. The design of wearable sensors should be in such a way which can easily be integrated with our daily life routines. People should not feel odd or visually different from others while wearing these sensors. It can be achieved by developing sensors in the design of our dressing accessories. The development of the ECG monitoring device in the form of a necklace  and smarImplementation of complex ECG analysis algorithms on smartphonesThough smartphones nowadays have improved processors, they are still inadequate for the implementation of complex ECG analysis algorithms. These algorithms used to run in high processors of laptops and PCs. The implementation of these algorithms in a smartphone can improve the analysis, and the number of abnormalities is detected.Flexible and Adaptive style of wearable sensorsThe design of wearable sensors should be in such a way which do not look odd and can be used in our daily life routines at homes and workplaces.Short range of wireless transmission technologiesMost of these systems use Bluetooth for wireless transmission of signals from wearable sensors to a smartphone. The limited range of transmission can affect the mobility of patients. Improvement in the range of wireless transmission technologies can increase the mobility of patients.Accuracy of DiagnosisThe accuracy of cardiac parameters and abnormalities detection is still an open issue for researchers. Most of these systems calculate Heart Rate and decide based on it. Other heart diseases which can be detected by the analysis of other points of ECG  should also be included.Following are some major issues suggested by reviewing these systems.The enhanced features of the smartphone, such as robust sensors, wireless communication technologies, high-speed processors, and a growing number of usage, made use of smartphones very vital in cardiac health monitoring. A categorical review of smartphone-based systems for real-time cardiac monitoring and abnormality detection is presented in this paper. The primary focal point was the analysis of ECG for heart abnormality detection using wearable sensors and smartphones. Review of ECG based system is divided into three sub-categories named as 1) Recording visualization systems 2) Server-based processing of ECG 3) Smartphone-based processing of ECG. The systems reviewed in the first group can record ECG signals and show them on the screen of a smartphone or any other PDA. The second group review those systems which perform analysis of ECG signals by transmitting them to a processing server at a medical facility. Furthermore, finally, local processing and heart abnormality detection are performed in smartphone-based processing systems, which are reviewed in the third group. Additionally, PPG based non-invasive systems are presented in section two, which can perform real-time monitoring and estimation of cardiac parameters by placing the index finger of the subject on the camera of a smartphone. These systems provide ambulatory, continuous, and real-time heart monitoring and abnormality detection with portability and mobility of patients. Different types of noises and artifact occurred during signal acquisition can affect the accuracy of diagnosis. Telemedicine implemented in these smartphone-based systems provides distance based monitoring and guidelines for patients, especially in less developed rural areas. The short-range of wireless communication technologies such as Bluetooth, implementation of complex ECG analysis algorithms in smartphones, flexible and adaptive design of wearable sensors, fewer abnormalities/disease detection, and security of data are significant issues that need to be addressed. The concept of tele-medicine for distance- based monitoring and alarm generation in case of abnormality detection makes possible the in-time de- tection and treatment of abnormalities to minimize casualties. This study aims to serve as a reference for researchers and developers to provide knowledge of the limitations of existing systems and future im- provements.


The correct range is 100 ms to 1000 ms post-stimulus. The response window definition for one analysis, namely the decoding analysis on individual trials, however, was performed using the incorrect definition of the response window. This analysis was re-run using the same response window definition as in the analysis with the averaged firing rates across trials of a stimulus, which resulted in minimal changes to


This work focuses on the combination of two complementary non-destructive techniques to analyse the final deformation and internal damage induced in aramid composite plates subjected to ballistic impact. The first analysis device, a 3D scanner, allows digitalising the surface of the tested specimen. Comparing with the initial geometry, the permanent residual deformation (PBFD) can be obtained according to the impact characteristics. This is a significant parameter in armours and shielding design. The second inspection technique is based on computed tomography (CT). It allows analysing the internal state of the impacted sample, being able to detect possible delamination and fibre failure through the specimen thickness. The proposed methodology has been validated with two projectile geometries at different impact velocities, being the reaction force history on the specimen determined with piezoelectric sensors. Different loading states and induced damages were observed according to the projectile type and impact velocity. In order to validate the use of the 3D scanner, a correlation between impact velocity and damage induced in terms of permanent back face deformation has been realised for both projectiles studied. In addition, a comparison of the results obtained through this measurement method and those obtained in similar works, has been performed in the same range of impact energy. The results showed that CT is needed to analyse the internal damage of the aramid sample; however, this is a highly expensive and time-consuming method. The use of 3D scanner and piezoelectric sensors is perfectly complementary with CT and could be relevant to develop numerical models or design armours. The current combat helmets are made of polymeric material reinforced with high ballistic resistance fibres, as aramid and high molecular density polyethene fibres. The main feature of the helmet is to minimise the brain injury that may affect the wearer due to blast or ballistic impact. Concerning the ballistic threats classification, combat helmets could be divided into perforating and non-perforating threats. Perforating threats are presented in war scenarios such as metalcore ammunition and long-range bullets . These pIn this case of non-perforating ammunition impact on a combat helmet, the higher part of the kinetic energy of the projectile is absorbed into delamination of the helmet, causing less non-penetrating deformation in the human body. Therefore, the damage extension is one of the most influential parameters for designers and is important for testing and evaluation agencies .Damage analysis has been widely analysed in composite materials such as carbon or glass fibres ,7,8,9,10Micro-tomography is a relatively novel technique with high potential for detection of defects and damage in a wide variety of materials. In composite material with non-appreciable defects in a visual inspection, the use of micro-tomography makes it possible to detect and place on 3D the presence of defects with reasonable accuracy, placing it above other inspection techniques such as ultrasonic. Vasudavan et al.  studied Aramid plates have been usually studied by merely visual inspection  or by cuIn this work, a new methodology based on different complementary sensors to measure the damage in the aramid fibre composite is presented. Three devices have been used for this purpose: pressure sensors to measure the energy absorbed by the sample during impact, 3D surface scanner and computed tomography. This procedure allows obtaining the total energy absorbed by impacted aramid samples, and the internal and surface damage for possible control by the evaluation agencies according to different projectile geometry and impact velocity. The damage resulting from tests with two different impactors will be analysed to show the effectiveness of the method. The critical gap that leads this work is the need for non-destructive techniques, such as micro-tomography, for aramid composites, since the damage inspection is mainly based on the destructive test. 3D Scan, rarely used in this field up to date, also allows comparing a damaged sample with an undamaged plate to observe, deformations and defects.After reviewing the literature that the authors have been able to access, such a detailed study of postmortem damage in aramid has not been found. Here, a new methodology has been proposed that combines the use of micro-tomography, which has been seen to be increasingly used in the detection of internal failures in composite material since its medical conception, and the 3D scanner that allows obtaining digital models of the specimen failure and can compare them with other models or specimens without damaging. On the other hand, the use of force sensors to quantify the temporal evolution of the resisting force during the impact process allows mechanical parameters, such as the force itself, deflection or stiffness, to be related to the presence of material failures.This methodology is extensible to other personal protection elements such as combat helmets and not only to quantify the local failure around the impact zone but also to analyse global deformations in the helmet and its subsequent influence on its ballistic performance under later threats.Aramid fibres are a class of resistant and thermostable synthetic fibres. They are widely used in aerospace and military applications, fabrics for bulletproof vests and ballistic composites, bicycle pneumatic tyres and as a substitute for asbestos. The chain molecules of aramid fibres are mostly oriented along the axis of the fibres, which makes it possible to benefit from this chemical bond strength. Among others, these composites present high mechanical strength/weight ratio, structural stiffness (Young’s high modulus and low elongation at break), high tenacity, high cut resistance and low thermal conductivity.2 with an areal density  of 8.86 kg/m2. This material has been used in different analyses in other works [Aramid composite plates have been manufactured through hand-made stacking of single plain wave woven fabrics of K129 aramid fibres, embedded in Polyvinyl Butyral Phenolic matrix (PVB) and then using hot-pressing; subsequently, the composite was cured. This thermoforming technique allows obtaining a low resin content on composite, close to 18%. Thanks to this procedure, a lightweight composite combined with high strength due to high fibre content (approximately 82%) has been obtained. Specimen test was squared 130 × 130 mmer works ,26,27,28Aramid composite material used in this work is shown in As it is mentioned above , aramid Table 1The experimental setup has been used in several ballistic studies with different materials ,31,32,33y ±1 m/s ,31,32,332. This structure is close enough to the cannon muzzle to ensure the normality of the impact and placed in the centre of the plate.The plate fixation device is a rigid structure that allows the secure placement of the specimen. Two steel frames fasten the sample in the perimeter, allowing an effective impact area of 100 × 100 mmFour piezoelectric force sensors (9011A Kistler) are used to measure the global force induced by the projectile on the target during impact. These sensors are fixed over the plate holder  and alloThe structural support has been designed by Kistler and presents a high stiffness and yield stress  have been manufactured of maraging steel with heat treatment to increase their hardness close to 600 HV. Therefore, the local and global failure modes in the aramid composite plate depend on the projectile nose. The diameter of the projectile is 12.8 mm which is slightly smaller than the diameter of the barrel, to avoid the use of the sabot. The dimensions of the two projectiles are shown in Computerised micro-tomography (CT-scan or CT) is a powerful technique which consists of X-Ray scanning axial images of high quality and precision. An X-ray beam is projected on the sample to be analysed, and part of the radiation that has not been absorbed by the object is collected by detectors like a spectrum. A data acquisition system transforms the data obtained by the sensors into digital images. From this, a grayscale voxel image that depends on the number of electrons that has been absorbed by the object is obtained. Greyscale is limited by white colour, associated with undamaged material, and black colour, due to a change in density because of the presence of air as a result of breaks or defects. A scheme of a CT process is shown in In this work, the internal damage of aramid plates after impact has been analysed using the CT-scan technique. Images were obtained by an X-ray micro-tomography device  with a minimum X-ray beam power of 160 kW which is possible to scan with a precision of 50 μm. Each plate takes around 4 h of scanning, requiring later image post-processing (AVIZO and X-Act 2.0 software was used). Tomography on aramid composites is a technique that has been rarely used, so it is a promising process of damage measurement with a wide range of applications in this material ,24. Some3 and up to 0.05 mm resolution). The minimum scan time for single image capture is 2 s. The equipment has two HP high definition cameras for stereoscopic image capturing combined with a structured light projector . It projects a beam of black/white line patterns on the object (structured light) with different orientations. The object to scan is positioned on an automatic 360° rotating platform while the cameras capture the light reflected on the object. The images of the object taken during the process need to be aligned for the final shape representation.The surface damage and the local and global deformation measurements of the tested plate have been obtained using an HP brand scanner  according to the cases where the maximum damage is reached, enabling the observation of the different damage modes attributed to the different projectile nose shapes.Using the laser beams sensor, it is possible to quantify the impact velocity for each test, as was mentioned in In The most remarkable part of this figure is the first peak  correlation with experimental values, as can be seen in The results for the impact range considered have been adjusted to a linear trend for every nose-shape. The correlation coefficients  are RThe failure mechanisms and the morphology of the penetration process have been analysed through computed tomography, described in These modes of damage are generally found in all composite materials regardless of the type of reinforcement, highlighting, according to the impact velocity, a projectile’s geometry, boundary conditions and material. However, the experimental tests carried out in this work in impact energy regime show that there is no complete perforation of the specimen; therefore, no fibre failure on the rear part of the composite is found. These damage modes are commonly observed and are very similar to those studied by other authors . Unlike According to Min et al. , the regMoreover, conical projectile leads to higher layer breakage compared to the blunt-shaped projectile, Thus, due to the morphology of the failure mechanisms described above, the conical projectile shows a better penetration capability than the blunt projectile. This observation is perfectly matched with the impact force analysis  and the Qualitatively, this technique allows expanding the knowledge about the failure mode of composite materials, since it can be different depending on the composition of the composite under the same loading action .The permanent deformation of the backside of the specimen (PBFD) after impact is measured using the 3D scanner. This technique provides the displacement field at any point of the surface of the plate. The 3D scanner allows analysing any virtual cut section of the specimen through the thickness. In particular, virtual sections by the dotted line (through thickness plane) sketched in Comparing differences in deflection due to the projectile, these are according to the internal damage observed in the previous section. A conical projectile localises impact in a smaller zone, leading to more significant failure of layers and enhanced penetration into the composite see  with a hA correlation between the permanent back face deformation and the impact velocity for both tip-shapes are shown in In the author’s opinion, this correlation for PBFD as a function of the impact velocity in conjunction with the resistance force versus impact velocity as presented in Although there are other works in the literature about ballistic impact testing on aramid composites, there is a wide variety of impact range , types of aramid and specimen dimensions that complicate comparisons with the present results. However, within the limited literature for the blunt projectile, the results have been compared with the work developed by Van Hoof , see FigAfter this analysis and the content presented in This study has demonstrated the application of different non-destructive image technologies to analyse the final deformation and damage induced in aramid composite plates subjected to ballistic impact. The obtained results, combining computerised tomography (CT) and 3D Scan, revealed a robust methodology for evaluating  defects, damages, deformation in aramid composites, where the use of non-destructive techniques for damage evaluation are not widely dispersed. There is an overall good correlation among both methods used. The setup based on piezoelectric sensors to measure the dynamic force allows relating the impact force to permanent back faced deformation. All three technologies can be used to analyse damage or defects in aramid composite materials. However, the only one to estimate the complete damage is the tomography and eventually the 3D scanner if full perforation occurs . The technique of inspection by force measurement is more complex since a large number of measures are required to obtain the maximum force to relate it to the failure. The main advantages of the use of tomography found in this work are the accuracy of resolution and the ability to obtain internal damage; however, it is a highly expensive and time-consuming method. The 3D scanner technology allows obtaining details of the external geometry  in a short time, being appropriate for industrial applications. Regarding the differences found between the projectiles used, the CT analysis revealed the greater penetration power of the conical projectile than the blunt projectile for the range of impact velocities used. Note that all the projectiles were made of hard steel and therefore were undeformable. Moreover, the conical projectile produced a greater deformation of the rear face of the plate (PFBD) than the blunt projectile.This study demonstrates that the advances in computing and sensorisation to analyse the internal damage and external deformation in aramid composites, where typical ultrasonic inspection is not applicable, may have an excellent use for the industry of personal protection such as combat helmets.


Natural exploration of textures involves active sensing, i.e., voluntary movements of tactile sensors  across a target surface. Somatosensory input during moving tactile sensors varies according to both the movement and the surface texture. Combining motor and sensory information, the brain is capable of extracting textural features of the explored surface. Despite the ecological relevance of active sensing, psychophysical studies on active touch are largely missing. One reason for the lack of informative studies investigating active touch is the considerable challenge of assembling an appropriate experimental setup. A possible solution might be in the realm of virtual tactile reality that provides tactile finger stimulation depending on the position of the hand and the simulated texture of a target surface. In addition to rigorous behavioral studies, the investigation of the neuronal mechanisms of active tactile sensing in humans is highly warranted, requiring neurophysiological experiments using electroencephalography (EEG), magnetoencephalography (MEG) and/or functional magnetic resonance imaging (fMRI). However, current neuroimaging techniques impose specific requirements on the tactile stimulus delivery equipment in terms of compatibility with the neurophysiological methods being used. Here, we present a user-friendly, MEG compatible, tactile virtual reality simulator. The simulator consists of a piezo-electric tactile stimulator capable of independently protruding 16 plastic pistons of 1 mm diameter arranged in a 4 × 4 matrix. The stimulator delivers a spatial pattern of tactile stimuli to the tip of a finger depending on the position of the finger moving across a 2-dimensional plane. In order to demonstrate the functionality of the tactile virtual reality, we determined participants’ detection thresholds in active and passive touch conditions. Thresholds in both conditions were higher than reported in the literature. It could well be that the processing of the piston-related stimulation was masked by the sensory input generated by placing the finger on the scanning probe. More so, the thresholds for both the active and passive tasks did not differ significantly. In further studies, the noise introduced by the stimulator in neuromagnetic recordings was quantified and somatosensory evoked fields for active and passive touch were recorded. Due to the compatibility of the stimulator with neuroimaging techniques such as MEG, and based on the feasibility to record somatosensory-related neuromagnetic brain activity the apparatus has immense potential for the exploration of the neural underpinnings of active tactile perception. Tactile texture perception is typically an active process; i.e., animals voluntarily move specific body parts  across a surface to generate dynamically changing tactile stimuli. In other words, active tactile sensing is a confluence of two processes: (a) precisely controlled movements of the sensory surface; and (b) the perception of the emergent tactile stimuli. Despite the ecological relevance of the active component of tactile sensing, in research and in clinical tests predominantly passive sensing is assessed during which tactile stimuli are delivered to a stationary finger. Whereas passive touch experiments are relatively easier to implement, and high-precision controlled stimulation is possible, recent studies in humans suggest an intricate link between motor processing and the somatosensory system  or fMRI] require equipment that is compatible with the testing environment, and does not generate electrical noise that might corrupt or interfere with the recorded neurophysiological signals. In other words, there is a need for a tool that goes beyond psychophysical experiments and overcomes the limitations of compatibility in neurophysiological and neuroimaging experiments. To that end, we developed a tactile virtual reality setup compatible with MEG and that could be used for psychophysical experiments as well.Typically, the manual presentation of different textures by the experimenter is slow and the possibility of unintended experimenter bias is high. Therefore, an automated and bias-free presentation of stimulus surfaces for efficient estimation of vibrotactile thresholds is always preferable. The novel tactile virtual reality setup presented here motivates two primary goals—(a) naturalistic finger sensing on textured surfaces ; and (b) computer-controlled equipment to present the textured target stimuli efficiently .2  and passive (no movement) conditions. In Experiment 2, we conducted a series of noise measurements to test the compatibility of the touchpad and the piezo-electric scanning probe in the MEG environment. In Experiment 3, we compared the evoked responses elicited by the stimulation of the scanning probe at the fingertip when the participant actively moved the scanning probe across the touchpad against the same stimulation but without the hand movement. In Experiment 4, neuromagnetic steady-state responses were recorded while actively scanning the texture of a grating-like surface. We emphasize here that the purpose of the current study is to demonstrate the effectiveness of the tactile virtual reality setup rather than to investigate active tactile perception in humans, The custom-built  virtual tactile reality consists of five parts : stimulavia standard “high speed” serial USB ports that guarantee reduced response latencies.The position of the scanning probe on the touchpad determines the spatial pattern of the tactile stimulation to be delivered to the fingertip see  through 2, consists of a set of two refreshable piezo-electric 4 × 2 Braille elements, thus creating a 4 × 4 configuration of 16 pistons. The distance between the adjacent pistons is 2.5 mm. Individually each piston protrudes by graded activation of the piezoelectric crystals in the range of 0–1 mm with a resolution of 0.01 mm. The piezoelectric elements are operated at a sampling rate of 1.2 kHz. The tips of the non-activated pistons remain flush with the top surface of the scanning probe. The protrusion of the individual piston and a group of pistons is controlled by the stimulation computer connected to the piezo-control unit.The stimulation patch  perceptually feel the same when that stimulus is presented passively to them? Evidence for altered processing of somatosensory stimuli during active movement in contrast to passive perception comes from studies that reported an elevation of detection thresholds during active perception  we delivered corresponding task-dependent tactile stimulus to their index finger. We asked the participants to find the location of the just noticeable stimulus by moving the scanning probe across the touchpad. Threshold intensities obtained in the active condition were compared against that in the passive condition; during the passive condition the hand was stationary and the piston protrusion (elicited by the participant’s scanning behavior) recorded in the active condition was replayed. Participants reported the perception of stimuli by key presses.Sixteen participants participated in the study . All participants, except one, were right-handed—determined by the Edinburgh Handedness Inventory , the participants received the corresponding tactile stimulus on their index finger of their dominant hand. The virtual textures served as templates for the stimulation see  such thaParticipants sat upright on a chair facing the touchpad in a well-lit room. They held the scanning probe in their dominant hand such that the glabrous part of the distal phalanx of their index finger covered the tactile stimulation patch . Each paIn the active condition, participants moved the scanning probe horizontally across the touchpad; the position of the scanning probe on the touchpad was recorded for online stimulus presentation and offline data analysis. In each trial, a different virtual texture pattern with random inter-ridge distances (between 7.5 mm and 12.5 mm) was chosen. Moreover, the gradient of amplitude change (high to low amplitudes or vice versa) from the left to the right side of the touchpad was randomized across trials. The trial by trial randomization of the gradient of change and the spacing of stripes ensured that the participants could not memorize a location or use a predetermined position on the touchpad as a response.via head-phones to the participants for the whole duration of the trial to mask any auditory cues generated by the piezoelectric stimulator. During any trial, if the touchpad lost contact with the scanning probe, a series of low-frequency tones alerted the participants. A series of high-frequency tones were presented when the touchpad detected more than one contact . In both cases, the tones continued until the participant rectified the situation. Participants were instructed to move the scanning probe across the virtual surface from left to right and back in a self-paced manner to find the location at which they felt that the tactile stimulus was just detectable. Participants reported their response, i.e., perception of the just noticeable elevation of the surface stripes, by pressing the “space-bar” on the keyboard of the stimulation control computer with the non-dominant hand. Participants were asked to double-check before reporting their perception, by scanning the underlying virtual surface back and forth, and respond only when they were sure. From the position of the scanning probe, we inferred the corresponding stimulus intensity that we later used to determine their threshold. Pressing the “space-bar” marked the end of the trial, which also turned off the white noise. Note that during a single trial a considerable number of stimuli (~50–100) with different amplitudes were applied depending on how the scanning probe was moved. Depending on the movement speed the stimulation frequency varied between ~2 Hz and 20 Hz. Scanning probe position, stimulation amplitude and status of the space-bar were recorded at a sampling rate of 100 Hz. After responding the participants returned to the “home position.” Participants were encouraged to take short breaks whenever they needed during inter-trial intervals. We recorded four blocks of 20 trials each, resulting in a total of 80 trials for each participant. Each block lasted for approximately 15 min including rest periods.Each trial started when the participant brought the scanning probe to the “home position” at the left margin of the touchpad. Participants initiated the trial by pressing the “Enter” button on the computer keyboard with their non-dominant hand. This keypress also started the presentation of auditory white noise delivered In the passive condition (implemented on another day), participants’ tactile detection threshold was determined using a more standardized approach during which the finger rested on the stimulation area of the scanning probe which was placed at the home position on the left side of the touchpad; the hand remained stationary during the trial. The tactile stimulation for active and passive conditions was delivered to the same fingertip. We replayed exactly the temporal pattern of stimulation that was recorded during the active touch condition. In other words, when participants moved their hand holding the scanning probe back and forth in the active condition the stimulus intensity decreased and increased accordingly. In the passive condition, the same sequence of intensities with the same timing as in the active condition was replayed. During the passive condition, the participants reported the perception of stimuli by pressing the space-bar on the keyboard of the computer controlling the experiment. The status of the space-bar signal was registered together with the position of the scanning probe and the stimulation pattern. Since stimuli were presented in a rapid sequence like in the active condition (~2–20 Hz) the spacebar was kept pressed within a trial as long as the stimuli were above threshold. To indicate that they did not feel any stimulation, participants released the space-bar immediately. The stimulation ended when the whole stimulation sequence recorded during the active sensing condition had been replayed. Like in the active condition, we presented auditory white noise during the entire trial. Similarly, participants were free to take a short break after each block. The number of trials and blocks in the passive condition was identical to that of the active condition.In order to estimate the sensory detection threshold in the active touch condition, we concatenated all four blocks. In each trial, the stimulation intensity of the last virtual ridge that was crossed by the participant before indicating that the just noticeable height or amplitude had been reached, was taken as the threshold value in that trial. Finally, for each subject, we computed the mean threshold by averaging the threshold values across trials. We estimated the scanning speed by calculating the first derivative of the position of the scanning probe on the touchpad in time.To estimate the threshold in the passive touch condition, we analyzed the recordings of the time course of the piston protrusion and the status of the space-bar that was continuously recorded at a sampling rate of 100 Hz. Note that the stimulation rate ranged between 2 and 20 Hz. First, we counted in the recordings the number of time points during which the piston was activated, separately for each of the presented piston protrusions. Next, we computed again separately for each piston protrusion the percentage of these time points during which participants also kept the space-bar pressed . Finally, in order to obtain a psychometric function, we fitted a cumulative normal distribution to the percentage of perceived samples expressed as a function of the piston protrusion. We considered the piston protrusion which was perceived during 50% of its presentation  as the participant’s threshold.t-test for dependent variables .Thresholds for active and passive sensation were compared by a SD: ±0.02) and 0.08 mm (SD: ±0.04), respectively. We performed a paired-samples t-test between the two conditions and found no statistical difference . The correlation between the speed and active threshold was −0.432 (p = 0.095).The obtained thresholds for the active and passive conditions were 0.07 mm  encode low-frequency vibrations in the range of 5–50 Hz, and the Pacinian corpuscles (connected to the Rapidly Adapting Type 2 afferents) encode high-frequency vibrations that range beyond 50 Hz . Magnetic fields were recorded using 275 first-order hardware gradiometer with a baseline of 5 cm placed around the curvature of the MEG helmet and a set of 9 magnetometers and 18 1st order gradiometers served as reference channels for noise cancelation. Effects of 3rd order software gradiometers and power line notch-filters are also reported. Noise measurements were done without recording a participant’s brain activity. The sampling rate of the recording was 11.719 kHz, and the anti-aliasing lowpass filter was set at 2.93 kHz. While the scanning probe with the in-built piezo stimulator and the touchpad were inside the shielded room , the other parts of the apparatus were placed outside, about 5 m away from the MEG sensors. We tested whether changes of pressure of the scanning probe onto the touchpad creates artifacts in the MEG recording. To this end, in the switched-on condition, a pneumatically membrane was periodically pressing on the touchpad with a frequency of 1 Hz introducing a well-defined extra touchpad current flow on the touchpad. The position of the membrane was chosen such that the pistons of the piezo-stimulators inserted in the scanning probe, The noise level in the switched-on condition was compared to that in the empty shielded room when the stimulator was switched off and the scanning probe and the touchpad were relocated to outside the shielded room. In total 100 s of data were acquired, which were segmented in epochs of 2 s. For each channel, the offset of the magnetic activity was removed by subtracting the mean activity across the whole epoch. Power spectra for both, the switched-on and the empty room conditions were calculated using a multi-taper Fourier analysis based on discrete prolate spheroidal sequences (Slepian sequences) as tapers implemented in field trip . Varying the pressure on the touchpad with a frequency of 1 Hz also caused an increase in noise activity in this frequency. Furthermore, some increase of noise power was observed at multiples of the power-line frequency of 50 Hz.The artifacts at the operating frequency of this apparatus at 600 Hz and its harmonics at 1,200 Hz, 1,800 Hz, 2,400 Hz, etc., appear at frequency ranges that are usually not considered in neuroimaging experiments. In most neuromagnetic studies, the frequency of the brain responses of interest is below 150 Hz and thus the apparatus does not introduce major artifacts. Yet, strict care needs to be taken that these frequencies do not interact with auxiliary functions of the MEG system like the oscillatory signals used for continuous head localization. Artifacts due to local changes of pressure on the resistive touchpad and thus changes in the total touchpad current are less critical under normal operation because the total current is unchanged when moving the scanning probe across the touchpad with a defined force. In addition, artifacts due to the current flow in the touchpad can effectively be suppressed using 3rd order gradiometers. Furthermore, some increase of noise power was observed at multiples of the power-line frequency of 50 Hz. Since most MEG studies investigate frequencies below 150 Hz and since the neuromagnetic brain signals at the power line frequency and its harmonics are contaminated anyway, our device does not impose any additional or critical limitations for the study of brain magnetic activity related to active touch.To illustrate the potential and the feasibility of using the tactile virtual reality for neuroimaging studies we conducted an experiment on a single participant . The participant performed a distance discrimination task during which he was requested to indicate whether the distance between two ridges was smaller or larger than in the previous trial. This task required the integration of phasic sensory and persistent motor information and was therefore ideal to study active touch and compare it to a passive perception task. Here, we demonstrate the possibility of recording neuromagnetic signals without any interference from the equipment. We provide a glimpse of how the setup can contribute to the investigation of sensorimotor interaction by presenting somatosensory evoked neuromagnetic responses. Contrasting the magnetic activity obtained during active touch to the activity evoked by passive stimulation revealed differences in activation dynamics between both conditions. For reasons of article length, we do not emphasize the results of the behavioral aspect of the task and refrain from the description of the time-frequency results , this led to four tactile stimulations of the fingertip. Within a trial the distance between the two virtual ridges was constant, and the duration encountered by the participant in each direction of the movement depended completely on the participant’s movement kinematics. Whenever the scanning probe went over the virtual ridges, the vertical columns of the 4 × 4 piston matrix . In the passive condition, stimuli were applied that were characterized by the same mean and standard deviation of the interstimulus intervals as in the active touch condition. Since the passive touch condition did not involve any hand movement, thereby no concept of distance estimation, the participant was asked to judge whether the interval  between two tactile stimuli in the current trial was longer than that in the previous trial.During the task, neuromagnetic data were simultaneously acquired with our 275 channel whole-head MEG system . Data were recorded at a sampling rate of 1,172 Hz, and an anti-aliasing filter set at 293 Hz. The onset of the piston movement served as a trigger for the time-locked analysis of the neuromagnetic data. Evoked magnetic fields elicited during the active exploration condition were compared to the passive stimulation. To demonstrate the recordability of evoked responses elicited by moving across the ridges, somatosensory evoked fields were computed by averaging stimulus-locked brain responses across trials. For each trial in the active condition, we obtained four evoked responses—two ridges  were encountered during both, the left to right movement, and the same two ridges during the returning direction. In the passive condition, the hand was kept stationary and evoked responses were obtained by applying tactile stimuli with interstimulus intervals whose mean and standard deviation were the same as in the active version. At the end of each trial in the passive condition, the participant had to indicate whether the “distance” in the current trial was shorter/longer than that in the previous trial. Because this condition is a temporal discrimination task, the decision of whether subsequent trials differ is based on the perceived duration estimates between the first and the second, and the third and fourth stimuli of each trial. In both, the active and passive conditions, the sound of the tactile stimulation was masked with white noise presented binaurally.The results of the pilot experiment show that the evoked magnetic field can be recorded using the equipment designed as tactile virtual reality. Stimulation artifacts are negligible and did not corrupt major components of the somatosensory evoked fields, in particular with latencies larger than 50 ms. Furthermore, the participant’s pilot data revealed a difference in the evoked response between active and passive touch. Amplitudes of the M60 component were larger in the active touch condition than in the passive condition . FurtherThe topography of the M60, M100 and M120 components for all four stimulus conditions shows the typical pattern of ingoing and outgoing magnetic fields that are expected for right finger stimulation activating primary (M60) and secondary  somatosensory cortex . For theScanning a structured surface by exploratory hand and finger movements generate a steady somatosensory input. While steady-state responses to somatosensory stimuli being delivered at a fixed frequency have been intensively studied in electroencephalography (EEG) and MEG . In the task, regularly spaced virtual gratings were used as stimuli. The ridges of the virtual grating had a width of 2.5 mm wide and a spacing of 10 mm. Whenever the scanning probe reached a position on the touchpad which was associated with virtual ridges the corresponding columns of pistons of the piezo-stimulator inbuilt in the scanning probe were activated. Moving over the virtual ridge neighboring columns of the piston matrix of the scanning probe were activated sequentially, mimicking the moving of the ridge across the fingertip during the hand movement. On the touchpad surface, there were 30 ridges in total. The participant was instructed to move the scanning probe across the touchpad from left to right and back again for 20 s per trial with his right hand. The participant was informed to stay within the central 300 mm of the 400 × 325 mm touchpad in order not to interrupt the sensory input when moving to the outer borders of the pad. Overall there were three training trials and 21 trials during which neuromagnetic responses were recorded. During training trials, the participant was familiarized with the task. He was instructed to find the speed at which the gratings could be perceived best and to maintain the same speed for the subsequent trials during which the magnetic oscillatory steady-state responses were recorded. Whenever the pistons were activated, a trigger was generated to monitor the stimulation of the participant’s index finger.Neuromagnetic steady-state responses were recorded using a 275 channel MEG system  with a sampling rate of 11.719 kHz, and an anti-aliasing filter set at 2.93 kHz in order record short-latency activity. The onset of the piston movement served as a trigger for synchronizing the recording to the stimulation. In addition to brain signals, the piezo control signal determining the protrusion of pistons and the trigger signal indicating the onset of the tactile stimuli were recorded for 7 min.Since the movement-induced stimulation frequency varied in a range extending from 16 to 32 Hz see , the steThe power spectrum of the piezo control signal see  revealedExperiment 4 revealed that movement-induced somatosensory steady-state response can be successfully recorded using the here presented tactile virtual reality. Although peaks around the stimulation onset most likely reflect residual stimulation artifacts, the evoked response was clear and yielded a dipolar pattern which is typical for the activation of primary somatosensory cortex and higher associative sensory brain regions. Due to the movement-dependent stimulation the frequency at which stimuli were presented varied between 10 and 38 Hz. Due to the large variability of the stimulation frequency, band-pass filtering the data at the stimulation frequency did not result in a clear topography of the steady-state response. In contrast, analyzing the steady-state activity as the evoked activity phase-locked to the 7,138 stimulus presentations yielded a well-defined response pattern. The source of the steady-state response included the primary somatosensory cortex in post-central sulcus and extended to the posterior parietal cortex. The involvement of the posterior parietal cortex might reflect the integration of sensory and motor information that is needed to infer the features of the surface texture (Mohan et al., A bias-free and efficient estimation of vibrotactile threshold becomes especially important in clinical applications such as the diagnosis of patients suffering from central or peripheral neuropathy. For example, diabetes is known to affect peripheral nerve condition (Hyllienmark et al., Combining a tactile piezoelectric stimulator with a resistive touchpad, we assembled a virtual tactile reality that enables the investigation of active touch. The objective of the current study is to provide a proof of concept for the applicability and effectiveness of the novel apparatus. We demonstrated successfully the functionality of our device in four psychophysical and neuroimaging experiments.In a first experiment, we estimated vibrotactile detection thresholds while participants actively scanned a virtual textured surface using their index finger. Although thresholds differed from values obtained with other methods, thresholds were consistent for both, the “active” and “passive” threshold estimation procedure. Whether the texture used in the current task was too simple to obtain better sensitivity in the active condition as compared to the passive condition needs to be clarified in future studies. Given the little overlap between the threshold values of Experiment 1 and the published norm values, we are currently unable to link our threshold values to the receptor types described in the literature. In order to further develop the device, future studies are suggested to explore the setup systematically by varying the spatial frequency of the virtual textures and by stimulating the fingertip using a high-resolution piston matrix. In addition, upcoming experiments should investigate how different receptor types can be selectively stimulated using different stimulation parameters. For example, applying a random dot pattern as a stimulation surface and stimulating a larger skin area by using the complete stimulation matrix of all 16 pistons might selectively activate Pacinian corpuscles. Slowly adapting Merkel cells might be best stimulated by broader strips of protruded stimulus pistons inducing lower stimulation frequency than more narrow ridges (Bolanowski et al., The participants’ performance and the integrity of the vibrotactile stimulus processing pathway is usually characterized by the thresholds of various stimulus parameters, such as stimulus intensity, frequency, roughness, etc. Current standard methods to test somatosensory detection and discrimination thresholds involve von-Frey hair probes (Braun et al., The presented device could be considered an initial attempt towards creating an automated and bias-free approach to efficiently examine somatosensory performance in clinical settings. The objective to develop sensitive equipment is critical for the study of somatosensation in patients, particularly those suffering from peripheral neuropathy in diabetes (Christensen, Next, to demonstrate the usability of the setup as a stimulus delivery system during neuroimaging study, we investigated the noise introduced by our device to MEG recordings. Finally, in order to demonstrate the quality of the recorded data and the potential for the investigation of active touch, we conducted MEG measurements while the participant was performing the distance estimation task and the steady-state response task. The MEG results provide convincing evidence that our novel tactile virtual reality setup does not corrupt neuroimaging signals by noise. Results obtained for the acquisition of neuromagnetic activity revealed brain activities contralateral to the stimulated hand, both, for event-related and steady-state conditions. Artifacts appeared specifically at the frequency of operation of the touchpad. Since these frequencies are known, they can be eliminated during data analysis. Using an operating frequency for the touchpad of 600 Hz shifts the artifacts into a frequency range which is clearly defined and far from most of the oscillatory brain activities under investigation. Despite the sources of noise that are inherent to the virtual reality setup, the presented experiments provide a first convincing proof of principle that the equipment has the potential to get insight into how the sensory and motor systems interact in active touch.Although in the here presented experiments we have used the scanning probe only in left to right and right to left direction, ridges with any arbitrary direction can also be presented in order to explore a multitude of textures. In general, a wide range of virtual surfaces with different degrees of complexity can be programmed. Thereby, the extension of the surface texture is defined by the size of the touchpad. Since the number of stimulation pistons can be potentially increased, the spatial resolution of the stimulation matrix can be improved further. Moreover, various layouts of piston arrangements can be configured that might allow for more refined stimulations. Currently, stimulation pistons are retracted by gravity. Fixating the pistons in their retainers by elastic filaments would even enable the exploration of textures placed in any direction in space. Given these possible developments, the here presented equipment should be only regarded as a first prototype.Concluding, the capability to quickly determine somatosensory thresholds the new device opens a wide perspective to study both, multisensory integration, and sensorimotor gating. It will allow detailed investigations of the interaction between hand movements and somatosensation in active touch. More importantly, its compatibility with neuroimaging methods such as MEG will furthermore enable the extension of somatosensory research towards the investigation of neural correlates of active scanning of surface textures.The datasets generated for this study are available on request to the corresponding author.The study was in full accordance with the Frontiers authors guidelines. The study was evaluated by the Ethics Board of the Medical Faculty of the University of Tübingen.AB has designed the somatosensory threshold paradigm, has written parts of the manuscript and handled the revision of the manuscript. DK has analyzed the data and has written the manuscript. AP has collected the data and provided the initial drafts of the manuscript. YL has contributed to the data analysis. MZ has provided the project idea and has edited the manuscript. CS has provided critical comments and valuable contributions to the manuscript. CB is responsible for the technical realization of the project. He has written parts of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.