In this paper we predict Bitcoin movements by utilizing a machine-learning framework. We compile a dataset of 24 potential explanatory variables that are often employed in the finance literature. Using daily data from 2nd of December 2014 to July 8th 2019, we build forecasting models that utilize past Bitcoin values, other cryptocurrencies, exchange rates and other macroeconomic variables. Our empirical results suggest that the traditional logistic regression model outperforms the linear support vector machine and the random forest algorithm, reaching an accuracy of 66%. Moreover, based on the results, we provide evidence that points to the rejection of weak form efficiency in the Bitcoin market. Does Bitcoin respond to financial, cryptocurrency, and macroeconomic shocks? Should Bitcoin follow the efficient market hypothesis? Do the other cryptocurrencies affect the volatility of Bitcoin prices? Bitcoin emerged in 2009 as the world’s first cryptocurrency, attracting new investors due to high returns. This is reflected by the returns of Bitcoin, as quoted on Coinbase, increasing by more than 120% from 2016 to 2017, reaching USD20.000 from USD900 for the purchase of a single Bitcoin token. In early 2017, the market capitalization of Bitcoin grew significantly from around USD18 billion to nearly USD600 billion at the end of that year. As an investment asset, Bitcoin was originally in the retail sector but has now become the benchmark for all other digital currencies that have emerged, such as Ethereum, XRP and Litecoin, among others.Prior research has compared Bitcoin to gold due to its low correlation with other financial assets . In a siAlthough there are also some studies that focus on predicting stock market price movements, it is important to consider the cryptocurrency market, which, according to Ferreira et al. , is charHowever, Bitcoin and other digital assets are not backed by any tangible assets. In general, Bitcoin and other cryptocurrencies are known to react to certain public market announcements ,7. In thVarious types of modeling methodologies have been applied in an attempt to forecast Bitcoin prices. Among the most prominent techniques are: random forest , artificAkyildirim et al.  focus onIn our study, we attempt to uncover the potential relationship between cryptocurrencies and other financial variables using a machine-learning framework on weekly data. To accomplish this, we compile a pool of 24 potential regressors based on economic theory and prior research. Using three different techniques, an SVM model with a linear kernel and a random forest algorithm, we examine the directional forecasting performance of our models in comparison to the commonly used logistic regression model. The innovation of our work stems from the application of state-of-art machine-learning methodology and the empirical identification of a relationship between Bitcoin and other cryptocurrencies and macroeconomic variables. We also specifically test the relationship between Bitcoin prices, exchange rates, and interest rates as a possible empirical validation of the Efficient Market Hypothesis (EMH) under a machine-learning framework.The results of the empirical investigation provide evidence that the returns on Bitcoin are independent of returns on other cryptocurrencies or macroeconomic determinants. This reveals that Bitcoin is a special asset independent of monetary policy or other digital currencies. According to this, investors could be able to utilize Bitcoin as a hedge against regulatory frameworks affecting interest rates and inflation. Given its ability to act as a hedge and its resistance to quantitative easing due to its limited supply, Bitcoin has the potential to flourish and strongly influence alternative investments for several years to come.The remainder of the paper is organized in the following way: In the next section, we describe the data. We developed a binary classifier based on SVM to predict the stock price movements of Bitcoin. The data was collected daily from Coinlore.com, a website providing high-frequency cryptocurrency data. The macroeconomic variables and interest rates were obtained from the Federal Reserve Bank of St. Louis (FRED), and the collection of selected exchange rates were acquired from Yahoo finance. The data spans from the 2nd of December 2014 to 8th July 2019. We compiled a dataset of 24 variables, which included the economic policy uncertainty (EPU) index as a factor, given that an increase in the EPU will change investors’ sentiments for the worse, according to Yen and Cheng  could inOverall, more than 700 observations were collected, but because the stock exchange is closed on weekends and there were many missing values, we applied a filtering process to the data. After we filtered the data, the final sample consisted of 239 observations. Financial returns  regression methodology is that the nature of the dependent variable makes OLS regression results irrelevant due to the heteroskedasticity of the estimated errors and the hypothesis violations in the asymptotic efficiency of the estimated coefficients. To solve this issue, we estimated the probability If the estimated Data classification and regression tasks usually include the use of the SVM, a supervised machine-learning methodology. It has gained great popularity due to its ability to provide highly accurate prediction results without making a priori assumptions concerning the phenomenon under investigation. Finding the ideal hyperplane that maximizes the distance between the two classes and the highest level of accuracy enables the SVM to classify the data into two classes . A tiny The hyperplane is defined as:The SVM with a linear kernel has become widespread, given that it possesses faster training and classification speeds with significantly fewer memory requirements than nonlinear cores due to the SBM’s compact representation of the decision function. In our research, we also examine the linear kernel where it detects the separating hyperplane in the original dimensional space of the dataset. The mathematical representation of the Radian Basis Function (RBF) kernel is the following:Over-fitting is a common issue that appears in the training set, where the model “learns” to accurately describe the training data, while giving worse performance to the test set. This concern is described in the literature as the “low bias–high variance” ,24. To aRandom forest is an ensemble technique that combines the idea of decision trees with the bootstrapping and aggregating procedure to create a diversified pool of individual regression systems . The ranOur study uses four separate performance indicators to illustrate how effectively the machine-learning categorization models execute detailed forecasting. The confusion matrix is created as shown in Based on the results of the confusion matrix, the following performance metrics are computed to evaluate the models.All performance metrix ratios range from 0 to 1. In our research, accuracy is the key performance matric to evaluate and compare the machine-learning models, as the models do not have balanced problems between the two classes of the target variable. Accuracy is expressed as the ratio of all the true predictions (positives and negatives) to the total number for all datasets. Moreover, accuracy is considered a significant performance metric in classification problems ,29. HowePrecision estimates the ratio of true positives cases among all cases , showing how many times our model predicted the positive class, and the numerator counts how many of those classes were actually positive, while the F1-Score is the harmonic mean of precision and sensitivity. Recall is the fraction of the true positive instances (cases) among all the cases , reporting all the positive cases. The numerator counts how many of those cases were correctly predicted by our model.Given the scope of this study, we apply a coarse-to-fine grid search scheme on the training set. We can obtain the optimal values of the hyperparameters that maximize the predictive ability of the SVM and random forest models. To accomplish this, we use a 5-fold cross validation process, avoiding overfitting issues. Given the balanced nature of our dataset, the procedure continued to identify the best parameters of the optimal model. The results of the hyperparameters of the SVM model with an RBF kernel are c = 0.0001 and γ = 100, while the optimal hyperparameters for the random forest model that we tested were n-estimators = 75 .However, the generalization ability of the trained model is evaluated using the testing dataset, which includes 239 observations. Results of 96 observations present an upward trend in the Bitcoin’s price, while 143 observations have a negative direction. As a performance matric, we employ four different metrics, recall (sensitivity), accuracy, precision, and F1-Score.According to Bitcoin has evolved rapidly over the past decades and is attracting strong attention from investors, who see this as part of the alternative investment space. With this significantly growing attention from the investment community, Bitcoin is an important asset class for researchers and traders alike. The objective of our paper is to construct a model which predicts Bitcoin movements and to investigate whether Bitcoin follows an efficient market hypothesis or a random walk. To achieve this, we collect a large dataset consisting of 24 variables that includes exchange rates, interest rates, macroeconomic variables, another 13 cryptocurrencies, and four auxiliary variables, spanning the period from 2 December 2014 to 8 July 2019. The dataset includes 239 observations (5-days frequency), divided into two subsamples: in-sample and out-of-sample. Two different machine-learning techniques and a traditional regression model are used, namely, logistic regression, the support vector machine and the random forest algorithm, which demonstrate the predictability of the upward or downward price moves. For the machine-learning model, the optimal values of the respective hyperparameters were initially found using five-fold cross-validation and out-of-bag methods to avoid overfitting.The empirical analysis confirms that the returns of Bitcoin are not affected by the returns of other cryptocurrencies or macroeconomic variables. This implies that Bitcoin is a unique asset that is not related to economic policy or other digital currencies. This suggests that investors can use Bitcoin as a hedge against government policy on inflation and interest rates. Given its hedging qualities and its robustness to quantitative easing due to its fixed supply, Bitcoin has the ability to continue to grow and make an important contribution to alternative investments for years to come.


Re = 50 and 150 did not lead to measurable changes in CFL heights or stress reductions for all investigated particle volume fractions. These measurements were used to describe the complete chain of how CFL formation leads to a stress reduction, which reduces the apparent viscosity of the suspension and results in the Fåhræus–Lindqvist effect. This chain of causes was investigated for the first time for flows with high Reynolds numbers  at channel Reynolds numbers relevant to ventricular assist device (VAD) applications. For this, detailed studies of local particle distributions of a particulate blood analog fluid are combined with wall shear stress and pressure loss measurements in two complementary set-ups with identical flow geometry, bulk Reynolds numbers and particle Reynolds numbers. For all investigated particle volume fractions of up to  Newsletter Transplant with data from the Global Observatory on Donation and Transplantation (GODT) shows that 8409 hearts were transplanted in 2021 compared to 21,935 patients on the waiting list [Around 64 million people worldwide suffer from heart failure . In the g region . Since sNonetheless, the understanding of the VAD gap flow is of great importance because it is known from the literature that red blood cells (RBCs) tend to migrate and separate from plasma in flows of similar geometric dimensions ,12,13,14heometer . To undeL, radius r and flow rate Q, where The effect originates from the flow forces acting on RBCs, which lead to a migration of the RBCs towards the center of the microgeometry and to a formation of a cell-free layer (CFL) . Due to Equation  . pBAFs are liquids with similar flow properties (density and viscosity) and corresponding flow behavior (Newtonian and non-Newtonian) to blood, in which particles are suspended that are intended to mimic the cells . The use of pBAFs offers important advantages over the use of real blood, such as better handling , less agThe main focus is the general study of particle migration and CFL formation of pBAFs in microfluidic systems at high Reynolds numbers , we measure the CFL height and determine the particle distribution in the microchannel flow. With this distribution, an inhomogeneous viscosity distribution Direct measurements of wall shear stress (WSS) in the pBAF flow allow the assessment of shear stress changes due to CFL formation. For this purpose, the pBAF flow is compared to a flow of an equivalent homogeneous blood analog fluid (hBAF) with the same density In the final step, pressure loss measurements across the microchannel are used to determine the extent to which CFL formation and shear stress reduction lead to a reduction in pressure losses in the channel. Based on these results, an apparent viscosity For this purpose, the particle-laden flow in straight microchannels of Addressing all of these issues provides the basis for a deeper understanding of real flow conditions in narrow VAD gaps at high Reynolds numbers, where particle/cell migration might greatly affect the flow.In this section, we explain how we studied the particle migration, CFL foration and the Fåhræus–Lindqvist effect in the flow of the particulate blood analog fluid (pBAF). For this purpose, Our hypothesis is that a reduction in stresses and pressure losses in the channel occurs through CFL foration in the pBAF. In order to quantify this reduction, we compared the results of the experimental pBAF flow with simulation results of a (particle-free) homogeneous fluid, with the same density Micronit Microfluidics BV  and were fabricated using an isotropic wet etching technique. Two channel variants were designed and used to integrate the various measuring methods. These channels are illustrated in The particle-laden flows in the pBAFs were analysed in straight microchannels. These were made of borosilicate glass by ial VADs .narrow channel and is used for the majority of the measurements, specifically the laser optical measurements (for identification of the CFL) as well as the pressure loss measurements (for identification of the Fåhræus–Lindqvist effect) performed here. The second variant is the broad channel. It has dimensions of narrow channel was necessary. For the flush wall installation, a 5 mm wide hole was made in the broad channel by laser cutting on the upper wall.The first channel variant is a rectangular microchannel with a length and width of narrow channel and 46.6 for the broad channel. This is a necessary criterion to guarantee that the flow and the particle migration in both channels are not affected by the channel’s side walls.The flows in both channels can be considered as plane channel flows since the aspect ratios r than 7 . The asph is the channel height). Furthermore, the fluid properties of density Reynolds number similarities were used in order to guarantee similar flow conditions in both channels. Here, two Reynolds numbers are important for the dynamics of particulate flow, see Equations  and 4)..4). The  in ref. ). It is h [Furthermore, the particle Reynolds number, rom ref.  indicateheight h . It is aow field . ContrarThe particulate blood analog fluids (pBAFs) used in this study consist of two fluidic systems. The fluidic systems are summarized in  of RBCs .Firstly, a pBAF is used, which is based on a glycerol–water–ammonium thiocyanate mixture. This fluid is called a refractive-index-matched (RIM) fluid and has been successfully applied in preceding studies to study the suspension dynamics in square capillaries by means of laser optical measurements . The denSecondly, a particulate BAF is used, which consists of water–polyethylenglycol (PEG) 200 mixtures with polystyrol (PS) particles  Density measurements and rheological characterizations of the fluidic systems were carried out by means of a Stabinger viscosimeter ..ϕ comparh-positions).For the assessment of particle positions in pBAFs and the evaluation of the CFL, the astigmatism particle tracking velocimetry (APTV) technique was utilized. APTV is a single-camera technique allowing to extend a planar image-based 2D-PTV approach to a 3D tracking approach with the help of astigmatic particle images. Astigmatism is introduced by placing a cylindrical lens into the optical path, causing particle images to deform depending on its out-of-plane distance to the reference planes of the optical system ,39. An iEclipse LV100, Nikon Corporation, Minato (Tokio), Japan) is used for the APTV measurements with a magnification of 20 and a cylindrical lens placed in front of a dual-frame CCD camera  of 200 mm focal length.For dilute particle systems, the out-of-plane position of a particle can be reconstructed from the astigmatic image shape with an accuracy that is on the order of magnitude of the particle diameter itself ,40. The Calibration. For calibration, labeled suspension particles with a particle volume fraction of n et al. . As the Flow measurements. The same carrier liquid mixture as for the calibration was used with different volume fractions Solo PIV Nd:Yag Laser System, New Wave Research Inc., Fremont, CA, USA) and were recorded with a dual-frame CCD camera . Particle images assume minimal and maximal image sizes of 20–200 pixels depending on their astigmatic aberration. Double images are taken 12 mm downstream of the channel inlet at 13 Hz frequency with interframing times of Due to the recording of double images, the same recording set can be used for the determination of velocity profiles, particle distributions and thus the CFL heights.Image processing and data analysis. For the determination of velocities, raw images were pre-processed to enhance the signal-to-noise ratio utilizing a median filter with a kernel size of 7 px × 7 px and a bandwidth filter to filter structures of 5 to 50 pixels in diameter. In the follow-up step, particle image center points were detected in double frames. To track particle displacements, a standard in-house 2D particle tracking algorithm was applied based on a two-time-step-based nearest neighbor approach. This is also possible for cases of higher particle volume fractions, since a fixed amount of suspension particles of h-position was assigned to each particle based on the corresponding position on the calibration curve that results from the Euclidean distance approach .In addition to the test rig for the laser optical APTV measurements, the same test rig was built in which pressure (losses) and wall shear stress measurements were carried out. The aim of these measurements is to capture the effect of the CFL on the near-wall stresses and pressure losses in the microchannels. Our hypothesis is that the CFL in the pBAF will reduce the high near-wall stresses in the channel, thereby decreasing the pressure loss in the whole rig compared to the flow of an equivalent, homogeneous fluid with the same density and viscosity . This reduction in acting stresses due to CFL formation is detectable with our WSS sensors.Fusion 6000-x, Chemyx Inc., Stafford, TX, USA), tubing connectors and a collection tank (g). The pressure drop in the rig is accounted for by two absolute pressure sensors ((f), IS-P Tube Pressure Senors, HiTec Zang GmBH, Herzogenrath, Germany), which are placed before (f1) and behind (f2) in the microchannel.The test rig is shown in broad channel, the wall shear stress sensor ((a), RealShear M-Series, Lenterra Inc., Newark, NJ, USA) is inserted into the hole at the top wall of the microchannel. The wall shear stress sensor has a swimmer at the head, which is deflected by the wall shear stress in the flow. Two optical fibers are installed in a fiber Bragg grating on the swimmer. The deflection of the swimmer changes the reflected wavelength in the grating, which is correlated with the corresponding wall shear stress. This swimmer must be integrated flush with the wall in the microchannel so that it does not actively influence the flow. For this purpose, a polychromatic light sensor (h) and a stepper motor (i) were used, with which a desired installation height of The core of the test rig is the measuring cell (b), in which the microchannels (d) are positioned. In the case of the Flow simulations of the whole test rig for the mechanical analyses were performed by direct numerical simulation (DNS). These simulations were performed assuming homogeneous blood analog fluids (hBAFs). These are fluids where no particle migration effects take place and which have the same densities The computational domain of the simulation with the used computational grid is shown in The simulations were performed by solving the Navier–Stokes equations in ANSYS CFX 2022R2  with a finite volume method. A second-order spatial discretization scheme was used and a time-independent flow situation was assumed. All walls were considered to be hydraulically smooth; a laminar Hagen–Poiseuille velocity profile, corresponding to Convergence was reached in the simulation when the root mean square residuals dropped below h with the associated, local viscosity h.With the help of all experiments and flow simulations, the local viscosity distribution The acting stresses in the flow will be altered due to this non-uniform local viscosity distribution. In particular, the highest stresses near the wall should be reduced by CFL formation due to the sole presence of the carrier fluid at the wall  from meTo determine this apparent viscosity, we reduced the viscosity of the hBAF flow simulations until the corresponding The results of astigmatic particle tracking velocimetry, wall shear stress and pressure loss measurements are analysed in the following sections to gain a complete picture of local, particulate flow properties, such as inhomogeneous particle concentrations, and understand their impact on global flow properties such as the shear stresses and pressure losses.Particle distributions for different channel Reynolds numbers icipated .In h is z-axis) over channel height increments of To formulate a quantitative measurement for the CFL height, we will herein refer to the CFL as the near-wall region, where the local volume fraction Between the channel center line and the CFL region, a PSSA region can be identified with increased local volume fractions. As shown in In igration . This miOn the one hand, particles will migrate towards the channel center, where shear rates are low or even zero along the channel center line. On the other hand, particle local volume fractions are nearly zero in the CFL, which also suggests a migration of particles towards the wall. However, here, the wall lift forces grow rapidly with decreasing wall distances. It is known from the literature that the net lift force, which is the sum of the shear gradient force and the wall lift force near the wall, scales proportionally to the relative particle–wall distance v et al. ,52. FurtThe CFL height is indicated in  Asmolov  showed tThe local particle distribution directly influences the local viscosity distribution of the flow. As can be seen from Equation , this wih in The relative viscosity distribution The particle local volume fraction is equal to zero near the the wall in all cases. In this region, the local viscosity equals the viscosity of the pure carrier fluid and the relative viscosity The local viscosity Equation . These abroad channel, for which the test rig was not designed. This applies to volume fractions at 5% and Reynolds numbers above This effect can be seen from the measurements with the wall shear stress sensor, shown in As can be seen from the table, all results with the hBAF indicate a normalized value of one, which is expected as However, this is not the case for the pBAF, where a reduction in the normalized friction coefficient is recognizable compared to the hBAF in the range of narrow channel.For all other conditions, the experimentally assessed pressure loss values After characterizing the near-wall flow and CFL of the pBAFs, the global effect of particle migration on the flow losses is discussed. Analyses were performed for all Reynolds numbers and volume fractions, except for The normalized ents see .In addition, two further derivations are noticeable from tion see , the diftion see ). This lMoreover, no clear trend in the dependence of the pressure losses on Reynolds number is seen in Based on these pressure loss analyses, the ratio of apparent viscosity to rheometric bulk viscosity Through combined experimental studies, detailed insights into particle migration and CFL formation at high Reynolds numbers in the order of Furthermore, APTV measurements revealed that an increase in particle volume fraction from quations : the bulEquation ) remainsDue to these relative pressure loss changes, the apparent viscosity ncreased . For thiThe most striking result of this study is that no changes in the CFL height, particle distribution and hence local viscosity distribution are measured, even though the channel Reynolds number triples  is hardly effected. For a particle system with dominating inertial forces, the CFL is naturally confined by the PSSA position and therefore will also undergo very little changes. How far this trend persists for higher volume fractions, where shear-induced particle migration is expected to also play a major role, is still to be investigated.A similar trend of Reynolds-independent CFL heights was observed by Stergiou et al.  at reducBased on our results, future investigations aim to directly compare the CFL characteristics of real blood flows and the pBAF flows at hematocrits, particle volume fractions of With the results of this study, initial assumptions can be made about the real shear stress distribution in the gap flows of a VAD. As can be seen from the measured results of pressure losses and wall shear stresses, the stresses are reduced in the microgemoetry with the pBAFs compared to the hBAFs for all conditions. For all investigated Reynolds numbers, a wall shear stress is established which is about However, this effect of stress reduction is not considered in the current analysis of VAD flow fields, e.g., by numerical flow simulations in VADs. In these simulations, blood fluid modeling assumes a hBAF flow almost exclusively. The results of this study are an indication that numerical fluid modeling should also account for cell migration in narrow VAD gaps. Otherwise, there will be a significant overestimation of stresses in the VAD flow simulation. Further experimental studies, with pBAFs as well as with blood at various hematocrits, will be performed by us in the future to develop a numerical blood flow model that accounts for these migration effects.The objective of this paper was to investigate particle migration and its impact on the stress field of blood analog fluids in microfluidic flows at high Reynolds numbers (Particle migration was studied in microchannels of 150 microns in height at particle volume fractions up to ribution , which rribution  and presribution . The preIf the described flow conditions also occur in VAD gaps, this would imply that the stress field acting on the blood cells in the gap is strongly dependent on cell migration. Due to this migration, lower stresses would act on the cells in the VAD gap than previously thought.However, further studies are needed to verify this. To date, only particulate blood analog fluids have been used at low hematocrits/volume fractions. Further studies with animal blood and higher hematocrits (


Previous research has shown that modified noun phrases (henceforth NPs) are subsequently retrieved faster than unmodified NPs. This effect is often called the “semantic complexity effect”. However, little is known about its mechanisms and underlying factors. In this study, we tested whether this effect is truly caused by the semantic information added by the modification, or whether it can be explained by the sheer amount of time that the processor spends expecting or maintaining an NP in the encoding phase. The results showed that time spent expecting or maintaining an NP can explain the effect over and above semantic and/or syntactic complexity. Our results challenge the current memory-based mechanisms for the modification effect such as the “distinctiveness” and “head-reactivation” accounts, and offer new and valuable insight into the memory processes during sentence comprehension. For example, successful resolution of long-distance syntactic dependencies such as (1), and referential dependencies such as (2), depend on the successful retrieval of words from earlier parts of the sentence:bear) needs to be retrieved as its syntactic object  and “it” in (2) depends on successful retrieval of “bear”. In (1), “bear” has been moved from the position immediately following “chased” to an earlier position to create emphasis via a syntactic operation called “clefting”. When “chased” is being processed, the displaced word ,the injured and dangerous bear) facilitates its subsequent retrieval compared to leaving the same NP unmodified  or post-nominally , the head noun (bear) is encountered before the modifying information (injured and dangerous), and as such, the processor necessarily spends more time maintaining the representation of the head noun when there is post-modifying information compared to when there is no such information. In addition to time spent, post-modifying information might also recruit more attentional/memory resources because post-modifiers tend to convey more complex information (2. ormation .the injured and dangerous bear), pre-modifying information is encountered before the head noun. However, because the determiner (the) predicts an upcoming head noun, the processor spends more time expecting the head noun in the case of pre-modified relative to unmodified NPs. Similar to post-modifiers, longer time spent expecting the head noun in the case of premodifiers might result in heightened attention, leading to more robust encoding of the head noun when it is encountered, which then facilitates its subsequent retrieval.In the case of pre-modified NPs . In the bear) and Pre-modified  NPs such as (3a) and (3b), respectively, to try to replicate previous findings on the pre-modification effect . However, three items were later removed due to coding errors. Participants read the sentences for comprehension in a self-paced reading paradigm. Two versions of each experimental sentence contained Unmodified We also added two conditions where the modification was replaced with as many Korean characters as there were English words in the Pre-modified condition. This manipulation simulated additional time spent on the NP in the Pre-Modified condition, but without adding syntactic or semantic content.the), revealing that the masking characters were modifying an upcoming head noun. In the No-Cue condition, the syntactic cue was replaced with a masking character too, making the function of the masking characters unknown: The sentence could go on with an adjective (It was interesting…) or verb participle (It was decided…), for instance.In order to understand whether prediction of an NP can explain the retrieval effect, in the Cue-Giving condition (3c), the masking Korean characters were presented with English syntactic cues , and allocation of attentional resources to it, then the critical verbs in the No-Cue condition should also be read faster than those in the Unmodified condition.bear in 3), and a subsequent clause with a verb whose processing depended on retrieval of the target NP . In addition to the experimental stimuli, we also created 30 fillers, half of which included a random number of masking characters at random parts in the sentence. 16 of the critical sentences and 18 fillers were followed by a comprehension question to encourage participants to pay close attention to the task. The experiment was programmed and run in Ibex Farm (http://spellout.net/ibexfarm/).All experimental stimuli consisted of a clefted subject NP . We restricted the participants to native speakers of English who resided in the US with HIT approval rates of equal or greater than 95%. Participants also had to indicate whether they spoke any languages other than English. Using this data, we ensured that none of the participants spoke or read Korean. The task took approximately 40 minutes, and each participant was paid $2.Each trial started with participants viewing dashed lines corresponding to the number of words contained in the current sentence. Then the participants read the sentences by pressing the spacebar on the keyboard, which revealed the words one at a time. As each word appeared, the preceding word disappeared from the screen. If the current item had a comprehension question, it would appear on the screen after the last word of the sentence was read, and the participant had to indicate whether it was true or false by clicking on the TRUE or FALSE words that appeared below the sentence. If there was no question for the current trial, the next trial would automatically start when the participants pressed the space bar. There were two practice trials at the beginning of the experiment so that the participants had a chance to become accustomed to the experimental procedure.p values using the normal approximation method  in the Cue-Giving condition compared to the Unmodified condition. The critical verb  was read reliably faster in the Cue-Giving condition than in the Unmodified condition. The two words following the critical verb  were read significantly faster in both the Cue-Giving and No-Cue conditions. Finally, the third word following the verb  was read faster in the all three conditions relative to the Unmodified condition.We replicated the standard semantic complexity effect, with modified NPs facilitating subsequent reading times e.g., . HoweverImportantly, our results revealed faster reading times at the retrieval site and the following regions when the English modifications were replaced with masking characters, regardless of whether a determiner predicted an upcoming NP . This pattern of results shows that ease of subsequent retrieval is not necessarily a function of representational complexity in the form of semantic richness and/or syntactic complexity. Rather, the mere amount of time that the processor expects an upcoming noun enhances encoding and therefore facilitates subsequent retrieval.In fact, the late emergence of the semantic complexity effect  may suggest that time spent causes more robust encoding than semantic complexity, perhaps because the semantic content consumes some of the attentional resource that would otherwise be devoted to encoding the target NP also see  below.the) in the Cue-Giving condition. Because no retrieval should be triggered on this word, this effect is somewhat surprising. We think this is probably because the integration of all the words following the target NPs  is easier when that word is encoded more robustly (due to time spent). In fact, based on bear) might facilitate the integration of new information in general, regardless of whether the new information triggers retrieval of a specific previously encoded NP or not. Importantly, similar early effects have been reported by previous studies  strengthen the effect of time spent, perhaps by directing attention to the upcoming head noun more efficiently (perhaps through prediction). Another important observation is that the effect already appeared on the second word preceding the critical word  were masked too. Example experimental stimuli are shown in (4). We also increased the number of participants to 116 to maximize power.In this experiment, we tested the effect of post-modification on resolving syntactic dependencies. To this end, we used the same stimuli as in (4)that) was read faster in the Cue-Giving condition. The word immediately preceding the critical word  exhibited a reverse complexity effect such that it was read more slowly in the Modified than in the Unmodified condition. The critical verb (chased) and the three following words (in the cold) were all read significantly faster in the Modified, Cue-Giving and No-Cue conditions relative to the Unmodified (baseline) condition.bear; see above). We also observed an unexpected reverse semantic complexity effect on the word immediately preceding the critical word, with slower reading times for the English modified than for the unmodified NP. This effect may be spurious or may reflect a (late) processing cost associated with the temporary ambiguity present in the sentences of this experiment. Specifically, given the clefted structure of sentences, the target noun and the modifying relative clause (It was the bear that was injured and dangerous) could be viewed as a complete sentence, making the rest of the sentence surprising for the English modified condition, and perhaps leading to elevated reading times on the next content word (hunters).Again, we replicated the standard semantic complexity effect, with semantically richer and syntactically more complex NPs resulting in facilitated subsequent retrieval e.g., . ConsistIn this experiment, we wished to investigate the effect of time-dependent attention on referential (rather than syntactic) dependences. As mentioned above, pronouns have been shown to trigger the retrieval of their referents . Thus, pronouns also provide a reasonable testing ground for the effect of time vs. complexity. A sample experimental item is shown in (5). 116 participants took part in this experiment.(5).when and was) in the Modified condition, all the words were significantly faster in the Modified, Cue-Giving and No-Cue conditions relative to the Unmodified condition.hunters). Moreover, and as mentioned above, we think these early effects likely reflect a general speed-up due to ease of integration of words with the target when it is encoded more robustly and therefore is more activated in memory. In fell) may already reactivate the target NP’s representation, giving it an extra activation boost before the pronoun is encountered. Critically, even without regard to what is causing these early effects, these effects are emerging for all three conditions of interest, indicating that whatever it is that semantic complexity does, time-dependent attention does too.Unlike Experiments 1 and 2, faster reading times were observed for almost all regions in this experiment. There are substantial differences in the structure of the sentences in this experiment relative to the previous two experiments. Specifically, the sentences in this experiment were not cleft constructions and did not include a second character , and referential dependency resolution . The criFor instance, as mentioned in the Introduction, in the case of pre-modifiers, the head  noun is revealed after the masking characters, and, consequently, the processor is forced to expect an upcoming word (either the head noun or any other word) for a longer time, which might increase attention. In the case of post-modifiers, the head noun is given and the masking characters follow it. As such, the processor spends more time maintaining the head noun’s representation in memory. Interestingly, post-modifiers have also been argued to increase attention because they tend to convey more complex information . Thus, wthe) in An important aspect of our results is that English syntactic cues, namely the determiners  extra information with the head noun when English modifying words were replaced with masking characters. However, note that low processing cost also applies to the Unmodified condition, but this condition consistently produced the longest reading times across all three experiments. Thus, less processing effort is unlikely to have caused our results also see .distinctiveness account, due to the added semantic information contained in modifications, modified NPs result in representations that are more distinct from other representations. As such, the retrieval operation suffers less from other interfering representations, leading to easier retrieval. Under the head-reactivation account, information whose processing depends on a particular word causes reactivation of that word in memory. Translated to the modification effect, this means that processing modifying words causes the head noun to be re-activated in memory, leading to higher levels of ultimate activation for the head noun when it is modified than not  the most accessible item in memory at the time the masking characters are being read. As such, between maintaining the already-active head noun and trying to make sense of unfamiliar and, to the current participants, meaningless characters, maintaining a highly accessible representation is cognitively much easier and therefore the more likely scenario. Additionally, given that we do observe enhanced retrieval ease for both Cue-Giving and the No-Cue conditions in Experiments 2 and 3, it is clear that the target NP was encoded more robustly compared to the unmodified condition, and given that our participants reported not speaking Korean, the only viable scenario is that the masking characters allowed more time for the encoding of the preceding head noun.Two aspects about the design of our experiments might challenge our conclusions. First, in the Cue-Giving condition of possible , interprOne limitation of this study is the use of masking characters while reading English sentences. Although such a design might be unnatural, and might therefore reduce the ecological validity of the study, we argue that it is sometimes necessary to have such manipulations in order to isolate effects of interest. In fact, previous psycholinguistic research has used similar manipulations such as beeps and construction noise to better understand reference comprehension . MoreoveWe examined the underlying mechanism for the semantic complexity effect . By replacing modifying English words with masking characters, we increased the time spent maintaining or expecting a head noun thereby heightening attention to the encoding process. The results showed the same degree of facilitation during subsequent retrieval as standard modification, indicating that time spent maintaining or expecting an NP and the concomitant enhanced attention (and not solely or exclusively semantic or syntactic complexity) are the key factors underlying the modification effect.


The sphenoethmoidal meningocele is a herniation of the meninges through a communication of the skull base with an aeric cavity. It means the presence of an osteomeningeal breach, which is manifested by cerebrospinal rhinorrhea and nasal obstruction. iIs diagnosis is based on a very specific radiological assessment and biology allows the dosage of certain substances to confirm the nature of the cerebrospinal fluid, such as beta-2-transferrin, Once the breach has been found, the endoscopic route exclusively allows the pathology to be treated and the defect to be reconstructed using different materials before the occurrence of serious complications such as meningitis. Meningocele is defined by a hernia of the meninges through a bone defect of the skull base in a cavity, a rare pathological entity. Its sphenoethmoidal location is exceptional. It can be spontaneous or post-traumatic but poses a problem for management. The endoscopic route endonasal has found its place in the treatment of this pathology.The particularity of this disease is that it can remain asymptomatic for a long time as it can manifest itself by a serious complication involving the vital prognosis.A 42-year-old female, with no significant pathological history, presented with a 5-year-old right chronic nasal obstruction associated with intermittent clear rhinorrhea, complicated 15 days ago of meningitis for which she was treated with antibiotic therapy. The clinical examination found a bluish-pink formation of the posterior-upper part of the right nasal fossa at nasofibroscopy Figure .The patient underwent endoscopic endonasal surgery, which allowed resection of the meningocele and individualization of the osteomeningeal breach Figure  that wasThe surgical specimen was sent for histological study which confirmed the diagnosis of meningocele. The postoperative course was simple and we performed a lumbar puncture in order to reduce the intracranial pressure, which favored healing and complete closure of the breach. The duration of hospitalization was four days. After 18 months, no signs of recurrence or complications were noted.There are several forms of meningocele, Van Nouhuys and Bruyn classified them into spheno-ethmoidal, spheno-orbital, trans-ethmoidal or cribriform, sphenomaxillary, and trans-sphenoidal meningocele . Spheno-There are two techniques for the treatment of meningoceles and the reconstruction of osteomeningeal breaches: the classic neurosurgical route and the endoscopic route. The endonasal endoscopic approach has proven to be effective in the treatment of this pathology, highlighting the osteomeningeal breach, resecting the meningocele, and sealing the bony defect . SeveralThe success rate with the endoscopic approach reaches 80-85% of cases with less morbidity compared to the transcranial approach such as anosmia, frontal retraction and cerebral hemorrhage ,10.Meningocele is a rare pathology that can simulate a nasal tumor and can have serious life-threatening complications. Its diagnosis requires an appropriate workup and the treatment has benefited from the progression of endoscopic endonasal surgery. These minimally invasive procedures have very low morbidity and a success rate close to 90%.


In recent years, significant progress has been made in employing reinforcement learning for controlling legged robots. However, a major challenge arises with quadruped robots due to their continuous states and vast action space, making optimal control using simple reinforcement learning controllers particularly challenging. This paper introduces a hierarchical reinforcement learning framework based on the Deep Deterministic Policy Gradient (DDPG) algorithm to achieve optimal motion control for quadruped robots. The framework consists of a high-level planner responsible for generating ideal motion parameters, a low-level controller using model predictive control (MPC), and a trajectory generator. The agents within the high-level planner are trained to provide the ideal motion parameters for the low-level controller. The low-level controller uses MPC and PD controllers to generate the foot-end force and calculates the joint motor torque through inverse kinematics. The simulation results show that the motion performance of the trained hierarchical framework is superior to that obtained using only the DDPG method. In contrast to their wheeled and tracked counterparts, quadruped robots confer two pronounced mobility advantages: discrete footholds and the capacity for multi-degree-of-freedom limb movements. The first advantage stems from the ability of quadruped robots to adeptly navigate intricate terrains, adroitly surmounting obstacles and spanning gaps, all while exerting minimal ground pressure. The second advantage resides in quadruped robots’ quadrilateral configuration, with each limb endowed with diverse degrees of freedom. This architecture empowers them to manifest a diverse spectrum of motion patterns and behaviors. Quadruped robots can dynamically regulate their body height, proactively dampen vibrations, and adroitly manipulate objects using their limbs, thereby significantly enhancing their overall flexibility . These mIn recent years, there has been a burgeoning interest in quadruped robot research, encompassing diverse domains like industrial applications and robot education. The control strategies applied to these robots can be broadly categorized into two classes: conventional control methods and reinforcement-learning (RL)—based approaches. Notably, conventional control methods, including model predictive control (MPC) ,9, have However, a significant challenge arises in the context of quadruped robots due to their continuous states and extensive action space. The continuous states of quadruped robots necessitate the continual processing and interpretation of uninterrupted sensory inputs. These inputs encompass crucial parameters such as position, velocity, and orientation. This processing is essential to accurately determine the robot’s current state, which forms the foundation for subsequent decision-making. Concurrently, the extensive action space available to quadruped robots equips them with a broad spectrum of potential actions. These actions span from diverse gaits to nuanced variations in leg positions and joint torques. However, the sheer abundance of feasible actions gives rise to a phenomenon known as combinatorial explosion. This phenomenon poses a formidable challenge, obstructing the systematic exploration and optimization of the most optimal set of actions ,15. The To address these formidable challenges, researchers have employed diverse strategies, encompassing techniques like predefined signals and action-reference-guided learning . AnotherThis paper introduces a stratified framework in which the upper-level planning layer furnishes motion parameters to the lower-level control layer. Following this, the lower-level control layer computes the relevant motor torque predicated on the input parameters, thereby attaining meticulous robot control. This methodology efficiently diminishes the exploration range at the upper level, thereby expediting real-time adaptations and revisions to accommodate alterations and uncertainties in the system. Consequently, it amplifies the training efficiency and bolsters the resilience of the system.To establish the forward kinematics of the quadruped robot, this paper employs the D–H modeling method, enabling the derivation of the single-leg Jacobian matrix and the analysis of the simplified dynamic model. The proposed HRL framework consists of a high-level planner that utilizes the Deep Deterministic Policy Gradient (DDPG) method to generate the optimal motion parameters for the robot. At the lower level, the controller employs the MPC method and composite trajectory planning method to address the foot-end forces during the support and swing phases and calculate the output torque for each joint motor. The motion performance of both the DDPG method and the proposed hierarchical method during training is analyzed using Matlab/Simulink software. This analysis serves to validate the effectiveness of the hierarchical deep reinforcement learning (DRL) model and acts as a reference for subsequent motor selection and optimization of actual prototypes.Kinematics elucidates the geometric correlation between the robot’s end effector and the position of each joint, whereas dynamics elucidates the mechanical interplay between joint positions and torques. These two disciplines serve as the cornerstone for comprehensively studying robots.The experimental platform chosen for this study is the Spot-Micro, a four-legged robot model consisting of a body and four legs. Each leg possesses a 3-degree-of-freedom hinge structure comprising a rolling hip joint, a pitching hip joint, and a pitching knee joint.To depict the functional relationship between the position and orientation of the leg end and the center of the robot’s body, the D–H modeling method is employed to establish the corresponding D–H model. Physical and simplified representations of the model are illustrated in 0 axis pointing vertically upwards. The {1} coordinate system is fixed on the rolling hip joint and rotates with it, with the Z1 axis pointing towards the left. The {2} coordinate system is fixed on the pitching hip joint and rotates accordingly, with the Z2 axis pointing out of the plane of the paper. The {3} coordinate system is fixed on the pitching knee joint and rotates with it, with the Z3 axis pointing out of the plane of the paper. The {4} coordinate system is fixed on the foot end and moves with the lower leg, with the Z4 axis pointing out of the plane of the paper. As shown in According to the relationship between the above coordinate systems, the D–H parameter table of a single leg of the quadruped robot is shown in In the above table, Taking the left front leg as an example, the transformation matrix from the centroid to the foot-end coordinate system of the quadruped robot is derived as follows:According to the above coordinate system relationship, the Jacobian matrix of a single leg can be obtained by computing the partial derivatives of the forward kinematics equations with respect to the joint angles for each joint.m and ir is the corresponding position of the foot-end legs, Due to the inherent complexity of dynamic models of quadruped robots, some simplifications are necessary . In thisThis section provides a comprehensive description of the hierarchical framework, which consists of two components: the high-level planner and the low-level controller. The high-level planner is designed based on the DDPG algorithm, while the low-level controller consists of MPC and a trajectory generator.The HRL framework is shown in The high-level planner operates by receiving high-level observations , which represents the environment as a tuple ol tasks ,20,21. TThe algorithm employed in this study can be compartmentalized into three core segments: initialization, interaction, and update. During the runtime, the network parameters and the replay buffer are primed in the initial phase. The DDPG algorithm amalgamates elements from the Deep Q-Network (DQN) algorithm and the Actor–Critic framework. This amalgamation involves four distinct networks: a critic network coupled with its corresponding target network, in conjunction with an actor network accompanied by its corresponding target network. Within the scope of this research, the DDPG algorithm encompasses four neural networks: the actor network, critic network, target actor network, and target critic network. Each of these neural networks is composed of two concealed layers, with one comprising 512 neurons and the other comprising 256 neurons. The activation function for each layer is executed using the rectified linear unit (ReLU) function.In each episode, noise is injected to augment the interaction with the environment. The data acquired from these interactions are preserved in the replay buffer. When the time for network updates arrives, a minibatch of data is chosen at random from the buffer. Subsequently, the critic network, actor network, and their respective target networks undergo consecutive updates. This iterative update procedure persists for every episode until the algorithm reaches its termination point.A random minibatch of ta based on the current state ts, interacting with the environment to generate rewards tr+1 and new states ts+1. The parameter The actor network is mainly responsible for generating actions In order to ensure more stable training, periodic soft updates are performed on the target networks. The update functions for the target critic network parameter In this paper, the high-level observations , effective learning facilitation is achieved.The reward function was designed to encourage a faster velocity and longer duration while penalizing deviations from the desired direction and excessive torque. The reward function is represented as follows:Previous studies have demonstrated that setting termination conditions can improve the efficiency of learning. In this study, the cessation criteria are delineated as follows. The experiment will be halted if any of the subsequent conditions are met: the yaw angle, roll angle, or pitch angle exceeds a predetermined threshold; the center-of-mass position descends below a specified value; or any joint of the robot comes into contact with the ground.The high-level planning layer in the framework is responsible for providing several motion parameters to the lower-level control layer. These include the forward velocity , the optimization objective is constructed using MPC to achieve the desired control performance.To minimize the impact on the joints during the lifting and landing phases and ensure a smooth foot trajectory, a defined foot trajectory is employed in this paper.Upon receiving the swing leg motion parameters, namely the step length (S) and swing foot height (H), from the high-level input, the trajectory generator calculates the foot trajectory. The displacement, velocity, and acceleration during the swing period are depicted in i, and Once the foot trajectory is obtained, the PD controller calculates the real-time swing foot forces.By solving the MPC problem and tracking the foot tip trajectory, the foot contact forces of the supporting leg and the swinging leg are obtained. The torque of each joint in a single leg can be calculated by utilizing the principle of virtual work and employing the Jacobian matrix from Equation (3). These torque values are subsequently inputted into the hardware to facilitate robot control.The robot underwent training using Simulink to simulate its walking behavior on flat terrain, evaluating the HRL architecture. Two sets of comparative experiments were conducted. In the first set, solely the DDPG algorithm was employed for training, with the DDPG directly generating the joint motor torques for robot control (referred to as Group_0). In the second set, training was conducted using the hierarchical framework (referred to as Group_1). A total of 4000 training cycles were executed, with each cycle limited to a maximum duration of 10 s. The specific parameters of the robot can be found in For a comprehensive analysis of motion in the two experimental groups, the variations in the robot’s center of mass in the XYZ-axis directions were recorded throughout the entire gait cycle, as shown in The changes in the roll and pitch angles of the robot throughout the entire motion process were recorded, as depicted in This paper presents a gait control framework utilizing hierarchical reinforcement learning for quadruped robots. The framework aims to enhance the training efficiency of the agent while maintaining the stability of traditional control methods.The proposed framework comprises a high-level planner responsible for generating reference motion parameters and a low-level controller that calculates the required torques for each motor to achieve a trot gait. The algorithm is specifically designed with a predetermined state space, action space, and reward function. The current state is utilized as the input to obtain the motion parameters.The low-level controller utilizes MPC to calculate the optimal foot-end forces for the support legs and subsequently determines the necessary output torques for each joint motor. For the swing legs, a combination of composite trajectory planning and a PD controller is employed to track the foot-end trajectory and compute the required output torques for each joint motor.Simulation experiments were conducted to evaluate the effectiveness of the gait control framework using both deep reinforcement learning and hierarchical reinforcement learning. Experimental data were collected and comparatively analyzed to draw meaningful conclusions.(1)In this study, kinematic and dynamic analyses of a quadruped robot were conducted. The D–H method was utilized to analyze the kinematics of a single leg in the quadruped robot, enabling the determination of the mapping relationship between the center of mass and the foot-end position, as well as the calculation of the Jacobian matrix. Following this, the dynamic models of the robot were simplified, resulting in the representation of a single-rigid-body state.(2)An HRL framework was designed, consisting of a high-level planner and a low-level controller. Drawing inspiration from the concept of HRL, the complex control task of the quadruped robot was decomposed into two levels: high-level planning and low-level control. The high-level planner employed the DDPG algorithm to generate motion parameters for the robot. The leg motions were categorized into the support and swing phases. For the support leg, an optimization problem based on the MPC method was formulated to determine the optimal foot-end force. In the swing leg, a composite swing trajectory was employed to achieve the desired foot-end position at each time step, and a PD controller was utilized to generate a virtual foot-end force. The required torque for each joint motor was then calculated using the Jacobian matrix.(3)The quadruped robot was simulated in Simulink, incorporating the aforementioned approaches. Simulation experiments were conducted using both deep reinforcement learning and hierarchical reinforcement learning methods. The results of these experiments confirmed the superiority of the hierarchical reinforcement learning method.The main contents and conclusions of this paper are summarized as follows:Our forthcoming experiments will be dedicated to fabricating a physical quadruped robot prototype with the ability to function within authentic environmental conditions. Our emphasis will encompass the amalgamation of diverse sensors to procure real-time environmental data. Furthermore, we intend to migrate the control algorithms established within simulated environments to the robot platform. This migration process will encompass the translation of algorithms into tangible hardware control interfaces.


Assistive ankle-foot orthoses (AAFOs) are powerful solutions to assist or rehabilitate gait on humans. Existing AAFO technologies include passive, quasi-passive, and active principles to provide assistance to the users, and their mechanical configuration and control depend on the eventual support they aim for within the gait pattern. In this research we analyze the state-of-the-art of AAFO and classify the different approaches into clusters, describing their basis and working principles. Additionally, we reviewed the purpose and experimental validation of the devices, providing the reader with a better view of the technology readiness level. Finally, the reviewed designs, limitations, and future steps in the field are summarized and discussed. Locomotion is a primary task for human beings and an essential component for a rich quality of life. There might be diverse  causes that limit the locomotion ability in humans, especially the efficiency and effectiveness of gait. Among all multi-body segments and muscles involved in walking, those related to the ankle joint are major contributors to perform the required mechanical work .Over the last decades, wearable assistive ankle-foot orthoses (AAFOs) have been developed and applied to assist ankle motion in humans. The main aim of these devices is to either reinforce and enhance the mobility in able-bodied subjects , or to rDespite the end goal to be achieved with the AAFO, a major distinction between these devices can be made according to their working principle. Passive AAFOs are those devices that rely on passive elements such as dampers or springs to store and release energy during gait, containing no control or electronics. Quasi-passive (or semi-active) AAFOs use computer control to adjust the performance of a passive element, and sometimes also hold a small motor to modulate their stiffness. Finally, active AAFOs, also called robotic exoskeletons, come with electric or pneumatic actuators connected to a power source to deliver assistive torques or forces to the users.There are previous reviews that analyzed to some extent the application of articulated AAFOs and their influence on gait. These studies either focused on a single working principle such as passive  or activ• Understand and describe the actuation mechanisms adopted within the three groups of AAFOs .• Classify different robotic AAFOs with regard to their mechanical configuration, purpose and effects when evaluated in healthy and impaired subjects.• Summarize the novelties and limitations of the reviewed systems to be considered in future designs.The aim of this paper is to assess the mechanical designs of devices that focus on providing assistance at the ankle level, and evaluate the gait effects generated by these devices when being tested. This research effort is intended to:In order to contextualize this work, we start with discussing the biomechanics of gait, highlighting the importance of the ankle-complex joint and giving an overview of the most common pathological gait patterns associated with ankle muscles’ weakness and the demanded assistances. In Human gait is a very complex activity that involves the coordination of various systems such as the musculoskeletal, nervous, and cardiovascular systems . One of The ankle-complex joint has an important and clear role during the full gait cycle . At the The role of the ankle-complex joint is compromised in many people with neurological disorders such as stroke, incomplete spinal cord injury or cerebral palsy. This causes a diminished walking ability and the appearance of pathological gait patterns . The impdrop-foot, reflected by an insufficient toe clearance. This deficit is normally compensated by increased knee and hip flexion and hip abduction during swing. Additionally, during initial stance and just after initial heel contact, dorsiflexors’ weakness can also prevent the controlled deceleration of the foot, which is often known as foot-slap.Weakness in the ankle dorsiflexors  may affect gait in both swing and initial stance phases : during equinus pattern  mostly affect the stance phase of gait. Especially, the existence of spasticity or contracture in the gastrocnemius and/or soleus results in  pattern , charactce phase . In geneAlthough the ankle-complex joint has three degrees of freedom (DOF), the primary plane during locomotion and where most of the motion is performed is the sagittal plane . IdeallyThe accomplishment of all the above-mentioned actions within a design is a real challenge, especially because adding extra weight to a device located at the ankle  could hamper the performance of the user increasing their energy cost of walking . MoreovePassive AAFOs are those that do not require any external power supply to generate the assistance. They have the main benefit of being lightweight compared with active AAFOs, so their use is closer to daily basis. To provide assistance, passive AAFOs need to be articulated, and normally they rely on passive elements such as springs, dampers, or elastic bands . In most cases, the design parameters of the passive elements  can be optimized only in very specific situations. Thus, these devices have the main limitation of hindering users’ performance for tasks they are not designed for. Regardless of the passive element that is being used, a relevant classification of passive AAFOs can be done based on their working principle and the mechanical configuration of the device see .The importance of tuning the mechanical properties of an articulated AAFO has gained importance in the last few years, and in that regard, adjustable dynamic response AAFOs (ADR-AAFOs)  have beeThe target users’ group of ADR-AAFOs is very wide , but allSpring-cam mechanisms can be used to compensate for diverse walking impairments by customizing individualized torque-angle curves according to the cam shape and the spring stiffness . The camIn patients suffering from equinus pattern, the self generated activity of the human has a large effect on the ankle motion. Clutch-dependent AAFOs  offer thBody-weight dependent clutches for AAFOs are normally located at the bottom of the user’s shoe, and they use the weight of the user during the stance phase to passively control the storage and release of energy. The core of a body-weight dependent clutch can be either compliant  , a mechaAnkle angle dependent clutches for AAFOs use the motion of the ankle joint during gait to control the storage and release of energy. These mechanisms are normally more complicated than body-weight clutches as, during a gait cycle, the ankle goes through plantarflexion twice, and thereby, this motion is not directly related to stance and swing phase (as happened with the body-weight). In this case, the pawl-ratchet principle is often used to engage and disengage the mechanism. Angle dependent clutches can be connected to passive elements such as springs , or to pOil dampers can also be used as hydraulically resistant shock absorbers. When the ankle joint moves to plantarflexion during initial stance the resistance produced by an oil damper reduces the rate of angular change. Following this working principle, Passive AAFOs are less adaptable than active (powered) devices due to their simplified design and their inability to control their functions. A trade-off between both solutions are the quasi-passive (or semi-active) devices, where sensors and small motors with low energy consumption are used to modulate the stiffness of passive elements . This enSimilar to passive AAFOs, there are designs for quasi-passive devices that rely on the action of a clutch. However, in this case, the clutch is normally electrically controlled, and sometimes a small motor is also used to combine both passive energy storage and additional power supply . Such isAnother electromagnetically driven clutch-dependent AAFO designed to capture heel-strike energy loss and recycle it into push-off propulsion was recently presented by Finally, Other quasi-passive designs have been proposed in the literature with the same aim of improving the possibilities of passive AAFOs by adjusting the stiffness or damping. As these designs vary quite a lot from each other, we provide a short description of four of them without following a specific classification.The first solution, called SmartAFO , used a Finally, the quasi-passive AAFO designed in  is a dieThere are certain conditions of motion control and assistance that cannot be accomplished with passive elements due to their limited adaptability and control. Active AAFOs have the advantage of using external power supplies and actuators to address these limitations. Differences between active AAFOs’ designs can be found looking to their mechanical configuration and the control strategies used to assist ankle function see .The straightforward configuration is composed of a rigid transmission between the actuator and the orthosis structure  Figure . This coTo improve the adaptability, comfort, and efficiency of active AAFOs, some research groups have opted for using compliant elements in the torque transmission. These elements allow certain adaptations to the user and reduce the movement restrictions imposed by the orthoses. In this regard, a common approach is the use of elastic elements in series with the actuators to achieve the mentioned compliance  see Fig. This coA different approach to obtain a compliant mechanism while reducing the inertia of the device is the use of cables or wires to transmit the force to the human segments  Mooney . These dFollowing a bioinspired approach, PAMs were developed to generate forces when they get deformed by pressurized air. Some researchers opted for the use of PAM actuators for active AAFOs  Figure . These aThe performance of active AAFOs is determined by the control strategy followed to supply the intended assistance. In this regard, the control algorithm of these devices can be analysed following the bio-inspired hierarchical paradigm previously reported . This paIn the context of wearable robotic devices, particularly active AAFOs, these neural controllers are translated into control algorithms. The high-level controllers are responsible for the intention detection and the context extraction, being independent of the device itself. For this reason, we do not report the high-level control in this manuscript. The mid-level controllers, responsible for the movement pattern generation, and the low-level controllers, responsible for closing the feedback loop, are described below.Depending on the low-level control of active AAFOs, the deliverance of the assistance and thus the actuator behaviour can be performed following different paradigms. The most used approach is based on torque or force closed-loops . These cMid-level controllers are also required to coordinate an AAFO’s action with the current user’s gait state, thus ensuring that the assistance is delivered at the correct timing . This coSince these strategies are limited to the instants of detection of the key events, some authors prefer to characterize the full step with a monotonically increasing signal, called continuous gait phase, that is reset once the step is over. Thereby, it enables a more versatile control strategy not limited to key instants. The gait phase can be calculated based on the duration of previous steps and the time elapsed from the last heel-strike  or can bFinally, a third option would be to generate reference trajectories to be followed by the device from data directly measured on the subject. These references can be based on movement information from the assisted joint  or on thAlthough the reviewed literature  has reveAssisting paretic ankle functions is the most common objective of AAFOs, being the purpose of 36 out of 54 reviewed devices . The main difference between devices’ approaches relies on the strategy adopted to assist the impaired walking. Some devices (12 out of 36) were designed to provide assistance during the whole gait cycle, e.g., . The resWhen authors pursued to improve healthy performance (20 out of 54), they always opted for complementing the push-off function of the ankle, regardless whether they followed passive, e.g., , quasi-pFinally, some AAFOs were designed to be used for rehabilitation practices. This objective represents the least common purpose, being only the function of 2 out of 54 devices . These tAdapting to different gait phases, speeds, and terrains is of a great significance for any AAFO. Limiting these adaptations would imply a reduced versatility of the device as well as a hindrance towards the user’s improvement. Moreover, adaptability of the AAFOs does not only refer to adaptations to the environment or walking condition, but also the required adaptation to the user’s progression while using the device.Passive AAFOs that do not utilize clutches have inherent limitations in terms of adaptability, as the open-loop function of passive elements limits their ability to adapt to different walking conditions and tasks. These passive devices are not capable of providing assistance to either dorsi- or plantarflexion without hindering the other. The problem is resolved to some extent by using body-weight dependent clutches . These Quasi-passive AAFOs can more accurately switch the function of the passive elements to better react to changes in gait phases . Some ofFinally, active AAFOs are able to control dorsi- and plantarflexion separately, thereby, they offer more possibilities for adaptation irrespective of whether their main purpose is to support drop-foot , foot-sRegarding the subjects involved in the experiments, three main validation strategies have been reported across the reviewed articles . Some auWhen reporting validations with subjects, authors focused on the assessment of three main aspects: 1) the lower-limbs kinematics, related to functional aspects of gait; 2) the muscular adaptations that occur when users received the assistance provided by the AAFO; and 3) the metabolic cost of walking.Kinematic analysis is the most common assessment when impaired walking subjects are involved , only accounting for 20 out of 52 of the reported validations with humans . Those tEffects in muscular activity is the most common outcome reported when healthy subjects are involved in the experiment  passive devices in general have not been extensively tested to prove their good performance in adapting to different users and walking terrains. On the contrary, active AAFOs have the major benefit of being able to provide large levels of assistance fully controllable in amplitude and timing, which enables them to adapt to different velocities or varying ground conditions . HoweverThe stiffer the actuator, the more delicate and accurate the controller should be to track the user’s motion or intention. Therefore, most of the active devices use compliant actuation that decreases the demands of the controllers due to the inherent adjustable behavior of the actuator. Starting from the geared actuator, the straightforward compliant system is formed by adding an elastic element, i.e., a spring, in series with the actuator . These SAn important issue about the assistance provided by active AAFOs is the strategy followed to deliver a timed assistance without disturbing the subject. In this sense, non-compliant devices with a rigid power transmission can only rely on control strategies that synchronize the subject’s gait with the action of the AAFO. However, the nature of compliant mechanisms allows for a slight absorption of the hampering effect of imprecise controllers, which permits the transparent behaviour of the AAFO when the assistive torque is not given.Devices based on PAMs are characterized by the best compromise between exerted force and lightweight . HoweverFinally, AAFOs driven by cables have the potential of being the most lightweight active approach . By placBy analyzing the experimental validations performed with the reviewed AAFOs , we can The push-off assistance is the preferred goal for all three AAFOs categories . In most cases, the target populations for this type of support are healthy (empowerment), or aging and people who suffer from muscle weaknesses (assistance). Most of these devices have only been validated with experiments on healthy subjects .As mentioned earlier, due to the lack of consensus in the used experimental procedures between studies, it is very difficult to find common reported criteria for an objective comparison of the performance of different AAFOs.When addressing the functional performance of their device, technological indicators that describe the physical capability of the AAFO are normally provided. In that regard, researchers tried to report results on, for example, joint kinematics, spatio-temporal parameters, interaction forces, adaptability to walking speed, and effects on muscular activity or energy consumption. However, not all these topics were addressed for all devices, and even more importantly, the topics contemplated were assessed following different methodologies or with different target populations. Therefore and in order to have a fair quantitative comparison, it is essential to make sets of bench-marking criteria that researchers can follow to evaluate their devices, which is the approach also proposed by Additionally, there is also a lack of evaluations of the devices in diverse conditions that are decisive for representing daily-life situations. Currently, devices are mostly evaluated during flat overground walking, treadmill, or just technically. Experiments on non-standardized settings like uneven terrains, when maneuvering around, or just start and stop gait for instance, have not been sufficiently discussed. Thus, although it is possible to hypothesize, for example, that AAFOs with body-weight dependent clutches are superior to spring-cam or angle-dependent clutches in providing assistance while walking on a slope, no evidence is available for proving this claim.The effect of the AAFOs on users’ balance or user’s safety further than locomotion support are important aspects that are scarcely considered in the literature. There are some studies with active AAFOs that investigated the capacity of the device on improving balance capabilities of the users , but theFinally, the users’ perceived experiences in terms of perceptual, emotional and cognitive aspects are also barely reported. A reason for that might be the small number of studies and evaluations with human beings at long term, which limits the inclusion of questionnaires or human-in-the-loop experiments with variations of the technical device that report experiences of final-users. These reports would be very useful, for example, to assess the perceived comfort, control (embodiment and agency) and required effort when using an specific AAFO.Based on the above-mentioned points, the advantages and disadvantages reported in There have been quite some advances in passive AAFOs in the last years, but still these devices are not robustly prepared to address all kinds of situations encountered in everyday life. Started from less than 10 years ago, quasi-passive solutions represent a compromise between passive and active devices, resulting in an increasing trend that opted for using low electrical power to activate clutches. A trend for these devices (started in 2016) was to use other types of actuation rather than just springs and dampers for applying the assistance. The electroadhesive and dielectric elastomer actuators are examples of this. However, most of the passive and quasi-passive approaches have the limitation of providing assistance only towards dorsi- or plantarflexion, but not both. A groundbreaking step for (quasi) passive designs would be to have a device able to provide a configurable assistance on both directions with minor modifications.Active AAFOs have the potential of being fully controllable to assist several gait functions with a single design. These devices are now evolving to lighter and more compliant solutions that should be transparent for the user while they are not providing assistance. Following the tendency of passive devices to assist activities of daily living, active AAFOs should also be tested in unrestricted environments to assess their performance when assisting gait under more challenging and rapidly varying conditions (variations of terrain and gait velocity).