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Recent studies on human upper limb motion highlighted the benefit of dimensionality reduction techniques to extrapolate informative joint patterns. These techniques can simplify the description of upper limb kinematics in physiological conditions, serving as a baseline for the objective assessment of movement alterations, or to be implemented in a robotic joint. However, the successful description of kinematic data requires a proper alignment of the acquisitions to correctly estimate kinematic patterns and their motion variability. Here, we propose a structured methodology to process and analyze upper limb kinematic data, considering time warping and task segmentation to register task execution on a common normalized completion time axis. Functional principal component analysis (fPCA) was used to extract patterns of motion of the wrist joint from the data collected by healthy participants performing activities of daily living. Our results suggest that wrist trajectories can be described as a linear combination of few functional principal components (fPCs). In fact, three fPCs explained more than 85% of the variance of any task. Wrist trajectories in the reaching phase of movement were highly correlated among participants and significantly more than trajectories in the manipulation phase ( $\text{p}< 0.01$ ). These findings may be useful in simplifying the control and design of robotic wrists, and could aid the development of therapies for the early detection of pathological conditions.

Many organisms employ reversible dormancy, or seedbank , in response to environmental fluctuations. This life-history strategy alters fundamental eco-evolutionary forces, leading to distinct patterns of genetic diversity. Two models of dormancy have been proposed based on the average duration of dormancy relative to coalescent timescales: weak seedbank, induced by scheduled seasonality (e.g., plants, invertebrates), and strong seedbank, where individuals stochastically switch between active and dormant states (e.g., bacteria, fungi). The weak seedbank coalescent is statistically equivalent to the Kingman coalescent with a scaled mutation rate, allowing the use of existing inference methods. In contrast, the strong seedbank coalescent differs fundamentally, as only active lineages can coalesce, while dormant lineages cannot. Additionally, dormant individuals typically mutate at a slower rate than active ones. Consequently, despite the significant role of dormancy in the eco-evolutionary dynamics of many organisms, no methods currently exist for inferring population dynamics involving dormancy and associated parameters. We present a Bayesian framework for jointly inferring a latent genealogy, seedbank parameters, and evolutionary parameters from molecular sequence data under the strong seedbank coalescent. We derive the exact probability density of genealogies sampled under the strong seedbank coalescent, characterize the corresponding likelihood function, and present efficient computational algorithms for its evaluation based on our theoretical framework. We develop a tailored Markov chain Monte Carlo sampler and implement our inference framework as a package SeedbankTree within BEAST2. Our work provides both a theoretical foundation and practical inference framework for studying the population genetic and genealogical impacts of dormancy.

Background: Recurrent glioblastoma (rGBM) has limited treatment options. This phase 1 protocol was designed to study the safety and preliminary efficacy of TPI 287, a central nervous system penetrant microtubule stabilizer, in combination with bevacizumab (BEV) for the treatment of rGBM., Methods: GBM patients with up to 2 prior relapses without prior exposure to anti-angiogenic therapy were eligible. A standard 3 + 3 design was utilized to determine the maximum tolerated dose (MTD) of TPI 287. Cohorts received TPI 287 at 140-220 mg/m 2 every 3 weeks and BEV 10 mg/kg every 2 weeks during 6-week cycles. An MRI was performed after each cycle, and treatment continued until progression as determined via response assessment in neuro-oncology criteria., Results: Twenty-four patients were enrolled at 6 centers. Treatment was generally well tolerated. Fatigue, myelosuppression, and peripheral neuropathy were the most common treatment emergent adverse events. Dose-limiting toxicity was not observed, thus the MTD was not determined. Twenty-three patients were evaluable for median and 6-month progression-free survival, which were 5.5 months (mo) and 40%, respectively. Median and 12-month overall survival were 13.4 mo and 64%, respectively. The optimal phase 2 dose was determined to be 200 mg/m 2 ., Conclusions: TPI 287 can be safely combined with BEV for the treatment of rGBM and preliminary efficacy supports further investigation of this combination., Competing Interests: S.A.G. served as a consultant for Cellevolve, Novocure, Sumitomo Dainippon Pharma Oncology, Wex Pharmaceuticals, served as an advisory board member for Cornerstone Specialty Network, Daiichi Sankyo, Novocure, Sumitomo Dainippon Pharma Oncology, Wex Pharmaceuticals, received travel support from Cornerstone Specialty Network, Cortice Biosciences, Novocure, Wex Pharmaceuticals, served on the speaker’s bureau for Novocure and holds an equity interest in COTA. L.B.N. served on a data safety monitoring board for C.N.S. Pharmaceuticals and a scientific advisory board for Servier. S.L.S. and G.F. were employed by the study sponsor. S.H., N.M., P.D., S.S., M.R., L.C., have no conflicts to declare., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

The loss of sensitivity of the upper limb due to neurological injuries severely limits the ability to manipulate objects, hindering personal independence. Non-invasive augmented sensory feedback techniques are used to promote neural plasticity hence to restore the grasping function. This work presents a wearable device for restoring sensorimotor hand functions based on Discrete Event-driven Sensory Control policy. It consists of an instrumented glove that, relying on piezoelectric sensors, delivers short-lasting vibrotactile stimuli synchronously with the relevant mechanical events (i.e., contact and release) of the manipulation. We first performed a feasibility study on healthy participants (20) that showed overall good performances of the device, with touch-event detection accuracy of 96.2% and a response delay of 22 ms. Later, we pilot tested it on two participants with limited sensorimotor functions. When using the device, they improved their hand motor coordination while performing tests for hand motor coordination assessment (i.e., pick and place test, pick and lift test). In particular, they exhibited more coordinated temporal correlations between grip force and load force profiles and enhanced performances when transferring objects, quantitatively proving the effectiveness of the device.

Background: Learning of a visuomotor task not only leads to changes in motor performance but also improves proprioceptive function of the trained joint/limb system. Such sensorimotor learning may show intra-joint transfer that is observable at a previously untrained degrees of freedom of the trained joint., Objective: Here, we examined if and to what extent such learning transfers to neighboring joints of the same limb and whether such transfer is observable in the motor as well as in the proprioceptive domain. Documenting such intra-limb transfer of sensorimotor learning holds promise for the neurorehabilitation of an impaired joint by training the neighboring joints., Methods: Using a robotic exoskeleton, 15 healthy young adults (18-35 years) underwent a visuomotor training that required them to make continuous, increasingly precise, small amplitude wrist movements. Wrist and elbow position sense just-noticeable-difference (JND) thresholds and spatial movement accuracy error (MAE) at wrist and elbow in an untrained pointing task were assessed before and immediately after, as well as 24 h after training., Results: First, all participants showed evidence of proprioceptive and motor learning in both trained and untrained joints. The mean JND threshold decreased significantly by 30% in trained wrist (M: 1.26° to 0.88°) and by 35% in untrained elbow (M: 1.96° to 1.28°). Second, mean MAE in untrained pointing task reduced by 20% in trained wrist and the untrained elbow. Third, after 24 h the gains in proprioceptive learning persisted at both joints, while transferred motor learning gains had decayed to such extent that they were no longer significant at the group level., Conclusion: Our findings document that a one-time sensorimotor training induces rapid learning gains in proprioceptive acuity and untrained sensorimotor performance at the practiced joint. Importantly, these gains transfer almost fully to the neighboring, proximal joint/limb system., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Restoration of sensorimotor function after amputation has remained challenging because of the lack of human-machine interfaces that provide reliable control, feedback, and attachment. Here, we present the clinical implementation of a transradial neuromusculoskeletal prosthesis-a bionic hand connected directly to the user's nervous and skeletal systems. In one person with unilateral below-elbow amputation, titanium implants were placed intramedullary in the radius and ulna bones, and electromuscular constructs were created surgically by transferring the severed nerves to free muscle grafts. The native muscles, free muscle grafts, and ulnar nerve were implanted with electrodes. Percutaneous extensions from the titanium implants provided direct skeletal attachment and bidirectional communication between the implanted electrodes and a prosthetic hand. Operation of the bionic hand in daily life resulted in improved prosthetic function, reduced postamputation, and increased quality of life. Sensations elicited via direct neural stimulation were consistently perceived on the phantom hand throughout the study. To date, the patient continues using the prosthesis in daily life. The functionality of conventional artificial limbs is hindered by discomfort and limited and unreliable control. Neuromusculoskeletal interfaces can overcome these hurdles and provide the means for the everyday use of a prosthesis with reliable neural control fixated into the skeleton.

The loss of sensitivity of the upper limb due to central or peripheral neurological injuries severely limits the ability to manipulate objects, hindering personal independence. Non-invasive augmented sensory feedback techniques are used to promote neural plasticity hence to restore the grasping function. We devised a wearable device for hand sensorimotor rehabilitation capable of reliably detect transient tactile events based on custom piezoelectric polyvinylidene fluoride (PVDF) sensors and deliver discrete bursts of vibrations upon these events. We integrated the sensors into a fabric glove and tested the device in a pilot bench test exploring its ability to detect object contact and release as well as object slippage. Due to their broad bandwidth, the sensors proved to be suitable for both the applications: they responded with clear peaks when touching or releasing the object and increased the high-frequency content of the signal during slippage.

Study Design: This was a systematic review., Objective: The present study aims to review the available literature concerning sacroiliac joint (SIJ) pain and degeneration after lumbosacral fixation to identify the prevalence and potential risk factors., Summary of Background Data: Although numerous factors can predispose patients to SIJ degeneration and pain various clinical studies indicate lumbosacral arthrodesis as a major cause., Materials and Methods: The PubMed-MEDLINE, Cochrane Central Registry of Controlled Trials, and Embase Biomedical database were searched. Peer-reviewed comparative studies, cohort studies, case series studies and case control studies, conducted either in a retrospective or prospective design, that registered data about SIJ pain and degeneration after lumbosacral fixation were included., Results: Twenty-one studies including 2678 patients met the inclusion criteria. The percentage of SIJ pain after lumbosacral fixation diagnosed with injections and physical examination varied widely, from 3% to 90%. Among patients who underwent spinal fusion, SIJ pain prevalence was higher when arthrodesis was fixed compared with floating fusions (59% vs. 10%, P -value >0.05). The prevalence of SIJ degenerative changes at computed tomography scan was more frequent in patients who underwent spinal arthrodesis than in those who did not (75% vs. 38.2%, P -value ≤0.05)., Conclusion: According to current evidence, patients who received lumbosacral fixation are at risk of SIJ pain. Number of fused levels, involvement of pelvis or sacrum in the arthrodesis area, inadequate lumbosacral sagittal alignment, and site of bone graft harvesting could be possible risk factor leading to sacroiliac degeneration and pain after lumbar spine fixation that should be investigated by physicians. However, there is a lack of homogeneity of the studies that address the problem, therefore, further prospective comparative studies, with a homogeneous architecture and cohorts are needed., Level of Evidence: Level III., Competing Interests: The authors declare no conflict of interest., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

The coalescent is a powerful statistical framework that allows us to infer past population dynamics leveraging the ancestral relationships reconstructed from sampled molecular sequence data. In many biomedical applications, such as in the study of infectious diseases, cell development, and tumorgenesis, several distinct populations share evolutionary history and therefore become dependent. The inference of such dependence is a highly important, yet a challenging problem. With advances in sequencing technologies, we are well positioned to exploit the wealth of high-resolution biological data for tackling this problem. Here, we present adaPop, a probabilistic model to estimate past population dynamics of dependent populations and to quantify their degree of dependence. An essential feature of our approach is the ability to track the time-varying association between the populations while making minimal assumptions on their functional shapes via Markov random field priors. We provide nonparametric estimators, extensions of our base model that integrate multiple data sources, and fast scalable inference algorithms. We test our method using simulated data under various dependent population histories and demonstrate the utility of our model in shedding light on evolutionary histories of different variants of SARS-CoV-2., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Cappello et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The design of prosthetic controllers by means of neurophysiological signals still poses a crucial challenge to bioengineers. State of the art of electromyographic (EMG) continuous pattern recognition controllers rely on the questionable assumption that repeated muscular contractions produce repeatable patterns of steady-state EMG signals. Conversely, we propose an algorithm that decodes wrist and hand movements by processing the signals that immediately follow the onset of contraction (i.e., the transient EMG). We collected EMG data from the forearms of 14 non-amputee and 5 transradial amputee participants while they performed wrist flexion/extension, pronation/supination, and four hand grasps (power, lateral, bi-digital, open). We firstly identified the combination of wrist and hand movements that yielded the best control performance for the same participant (intra-subject classification). Then, we assessed the ability of our algorithm to classify participant data that were not included in the training set (cross-subject classification). Our controller achieved a median accuracy of ~96% with non-amputees, while it achieved heterogeneous outcomes with amputees, with a median accuracy of ~89%. Importantly, for each amputee, it produced at least one acceptable combination of wrist-hand movements (i.e., with accuracy >85%). Regarding the cross-subject classifier, while our algorithm obtained promising results with non-amputees (accuracy up to ~80%), they were not as good with amputees (accuracy up to ~35%), possibly suggesting further assessments with domain-adaptation strategies. In general, our offline outcomes, together with a preliminary online assessment, support the hypothesis that the transient EMG decoding could represent a viable pattern recognition strategy, encouraging further online assessments.

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk., (© 2022. The Author(s).)

Genomic surveillance of SARS-CoV-2 has been instrumental in tracking the spread and evolution of the virus during the pandemic. The availability of SARS-CoV-2 molecular sequences isolated from infected individuals, coupled with phylodynamic methods, have provided insights into the origin of the virus, its evolutionary rate, the timing of introductions, the patterns of transmission, and the rise of novel variants that have spread through populations. Despite enormous global efforts of governments, laboratories, and researchers to collect and sequence molecular data, many challenges remain in analyzing and interpreting the data collected. Here, we describe the models and methods currently used to monitor the spread of SARS-CoV-2, discuss long-standing and new statistical challenges, and propose a method for tracking the rise of novel variants during the epidemic.

Longitudinal molecular data of rapidly evolving viruses and pathogens provide information about disease spread and complement traditional surveillance approaches based on case count data. The coalescent is used to model the genealogy that represents the sample ancestral relationships. The basic assumption is that coalescent events occur at a rate inversely proportional to the effective population size N e ( t ), a time-varying measure of genetic diversity. When the sampling process (collection of samples over time) depends on N e ( t ), the coalescent and the sampling processes can be jointly modeled to improve estimation of N e ( t ). Failing to do so can lead to bias due to model misspecification. However, the way that the sampling process depends on the effective population size may vary over time. We introduce an approach where the sampling process is modeled as an inhomogeneous Poisson process with rate equal to the product of N e ( t ) and a time-varying coefficient, making minimal assumptions on their functional shapes via Markov random field priors. We provide efficient algorithms for inference, show the model performance vis-a-vis alternative methods in a simulation study, and apply our model to SARS-CoV-2 sequences from Los Angeles and Santa Clara counties. The methodology is implemented and available in the R package adapref. Supplementary files for this article are available online.

Dexterous use of the hands depends critically on sensory feedback, so it is generally agreed that functional supplementary feedback would greatly improve the use of hand prostheses. Much research still focuses on improving non-invasive feedback that could potentially become available to all prosthesis users. However, few studies on supplementary tactile feedback for hand prostheses demonstrated a functional benefit. We suggest that confounding factors impede accurate assessment of feedback, e.g., testing non-amputee participants that inevitably focus intently on learning EMG control, the EMG's susceptibility to noise and delays, and the limited dexterity of hand prostheses. In an attempt to assess the effect of feedback free from these constraints, we used silicone digit extensions to suppress natural tactile feedback from the fingertips and thus used the tactile feedback-deprived human hand as an approximation of an ideal feed-forward tool. Our non-amputee participants wore the extensions and performed a simple pick-and-lift task with known weight, followed by a more difficult pick-and-lift task with changing weight. They then repeated these tasks with one of three kinds of audio feedback. The tests were repeated over three days. We also conducted a similar experiment on a person with severe sensory neuropathy to test the feedback without the extensions. Furthermore, we used a questionnaire based on the NASA Task Load Index to gauge the subjective experience. Unexpectedly, we did not find any meaningful differences between the feedback groups, neither in the objective nor the subjective measurements. It is possible that the digit extensions did not fully suppress sensation, but since the participant with impaired sensation also did not improve with the supplementary feedback, we conclude that the feedback failed to provide relevant grasping information in our experiments. The study highlights the complex interaction between task, feedback variable, feedback delivery, and control, which seemingly rendered even rich, high-bandwidth acoustic feedback redundant, despite substantial sensory impairment., Competing Interests: The authors have declared that no competing interests exist.

Background: Proprioceptive deficits after stroke are associated with poor upper limb function, slower motor recovery, and decreased self-care ability. Improving proprioception should enhance motor control in stroke survivors, but current evidence is inconclusive. Thus, this study examined whether a robot-aided somatosensory-based training requiring increasingly accurate active wrist movements improves proprioceptive acuity as well as motor performance in chronic stroke., Methods: Twelve adults with chronic stroke completed a 2-day training (age range: 42-74 years; median time-after-stroke: 12 months; median Fugl-Meyer UE: 65). Retention was assessed at Day 5. Grasping the handle of a wrist-robotic exoskeleton, participants trained to roll a virtual ball to a target through continuous wrist adduction/abduction movements. During training vision was occluded, but participants received real-time, vibro-tactile feedback on their forearm about ball position and speed. Primary outcome was the just-noticeable-difference (JND) wrist position sense threshold as a measure of proprioceptive acuity. Secondary outcomes were spatial error in an untrained wrist tracing task and somatosensory-evoked potentials (SEP) as a neural correlate of proprioceptive function. Ten neurologically-intact adults were recruited to serve as non-stroke controls for matched age, gender and hand dominance (age range: 44 to 79 years; 6 women, 4 men)., Results: Participants significantly reduced JND thresholds at posttest and retention (Stroke group: pretest: mean: 1.77° [SD: 0.54°] to posttest mean: 1.38° [0.34°]; Control group: 1.50° [0.46°] to posttest mean: 1.45° [SD: 0.54°]; F[2,37] = 4.54, p = 0.017, η p 2  = 0.20) in both groups. A higher pretest JND threshold was associated with a higher threshold reduction at posttest and retention (r = - 0.86, - 0.90, p ≤ 0.001) among the stroke participants. Error in the untrained tracing task was reduced by 22 % at posttest, yielding an effect size of w = 0.13. Stroke participants exhibited significantly reduced P27-N30 peak-to-peak SEP amplitude at pretest (U = 11, p = 0.03) compared to the non-stroke group. SEP measures did not change systematically with training., Conclusions: This study provides proof-of-concept that non-visual, proprioceptive training can induce fast, measurable improvements in proprioceptive function in chronic stroke survivors. There is encouraging but inconclusive evidence that such somatosensory learning transfers to untrained motor tasks. Trial registration Clinicaltrials.gov; Registration ID: NCT02565407; Date of registration: 01/10/2015; URL: https://clinicaltrials.gov/ct2/show/NCT02565407 .

Proprioceptive training is a neurorehabilitation approach known to improve proprioceptive acuity and motor performance of a joint/limb system. Here, we examined if such learning transfers to the contralateral joints. Using a robotic exoskeleton, 15 healthy, right-handed adults (18-35 years) trained a visuomotor task that required making increasingly small wrist movements challenging proprioceptive function. Wrist position sense just-noticeable-difference thresholds (JND) and spatial movement accuracy error (MAE) in a wrist-pointing task that was not trained were assessed before and immediately as well as 24 h after training. The main results are: first, training reduced JND thresholds (- 27%) and MAE (- 33%) in the trained right wrist. Sensory and motor gains were observable 24 h after training. Second, in the untrained left wrist, mean JND significantly decreased (- 32%) at posttest. However, at retention the effect was no longer significant. Third, motor error at the untrained wrist declined slowly. Gains were not significant at posttest, but MAE was significantly reduced (- 27%) at retention. This study provides first evidence that proprioceptive-focused visuomotor training can induce proprioceptive and motor gains not only in the trained joint but also in the contralateral, homologous joint. We discuss the possible neurophysiological mechanism behind such sensorimotor transfer and its implications for neurorehabilitation.

Longitudinal molecular data of rapidly evolving viruses and pathogens provide information about disease spread and complement traditional surveillance approaches based on case count data. The coalescent is used to model the genealogy that represents the sample ancestral relationships. The basic assumption is that coalescent events occur at a rate inversely proportional to the effective population size $N&#95;{e}(t)$, a time-varying measure of genetic diversity. When the sampling process (collection of samples over time) depends on $N&#95;{e}(t)$, the coalescent and the sampling processes can be jointly modeled to improve estimation of $N&#95;{e}(t)$. Failing to do so can lead to bias due to model misspecification. However, the way that the sampling process depends on the effective population size may vary over time. We introduce an approach where the sampling process is modeled as an inhomogeneous Poisson process with rate equal to the product of $N&#95;{e}(t)$ and a time-varying coefficient, making minimal assumptions on their functional shapes via Markov random field priors. We provide scalable algorithms for inference, show the model performance vis-a-vis alternative methods in a simulation study, and apply our model to SARS-CoV-2 sequences from Los Angeles and Santa Clara counties. The methodology is implemented and available in the R package adapref.

During COVID19 and other viral pandemics, rapid generation of host and pathogen genomic data is critical to tracking infection and informing therapies. There is an urgent need for efficient approaches to this data generation at scale. We have developed a scalable, high throughput approach to generate high fidelity low pass whole genome and HLA sequencing, viral genomes, and representation of human transcriptome from single nasopharyngeal swabs of COVID19 patients.

Background: Human sensorimotor control of dexterous manipulation relies on afferent sensory signals. Explicit tactile feedback is generally not available to prosthetic hand users, who have to rely on incidental information sources to partly close the control loop, resulting in suboptimal performance and manipulation difficulty. Recent studies on non-invasive supplementary sensory feedback indicated that time-discrete vibrational feedback delivered upon relevant mechanical events outperforms continuous tactile feedback. However, we hypothesize that continuous tactile feedback can be more effective in non-routine manipulation tasks (i.e., tasks where the grip force is modified reactively in response to the sensory feedback due to the unpredictable behavior of the manipulated object, such as picking and holding a virtual fragile object) if delivered to highly sensitive areas. We further hypothesize that this continuous tactile feedback is not necessary during all the duration of the manipulation task, since adaptation occurs., Methods: We investigated the effectiveness of continuous tactile feedback in precision manipulation, together with a new sensory feedback policy, where the continuous tactile feedback is gradually removed when the grasp reaches a steady state (namely, transient tactile feedback). We carried out an experiment in a virtual-reality setting with custom tactile feedback devices, which can apply continuous pressure and vibrations, attached to the thumb and index finger. We enrolled 24 healthy participants and instructed them to pick and hold a fragile virtual cube without breaking it. We compared their manipulation performance when using four different sensory feedback methods, i.e., no tactile feedback, discrete vibrations, continuous tactile feedback, and transient tactile feedback. The latter consisted of gradually removing the continuous feedback in the static phase of the grasp., Results: Continuous tactile feedback leads to a significantly larger number of successful trials than discrete vibrational cues and no feedback conditions, yet the gradual removal of the continuous feedback yields to comparable outcomes. Moreover, the participants preferred the continuous stimuli over the vibrational cues and the removal in the static phase did not significantly impact their appreciation of the continuous tactile feedback., Conclusions: These results advocate for the use of continuous supplementary tactile feedback for fine manipulation control and indicate that it can seamlessly be removed in the static phase of the grasp, possibly due to the mechanism of sensory adaptation. This encourages the development of energy-efficient supplementary feedback devices for prosthetic and telemanipulation applications, where encumbrance and power consumption are burdensome constraints.

Statistical inference of evolutionary parameters from molecular sequence data relies on coalescent models to account for the shared genealogical ancestry of the samples. However, inferential algorithms do not scale to available data sets. A strategy to improve computational efficiency is to rely on simpler coalescent and mutation models, resulting in smaller hidden state spaces. An estimate of the cardinality of the state-space of genealogical trees at different resolutions is essential to decide the best modeling strategy for a given dataset. To our knowledge, there is neither an exact nor approximate method to determine these cardinalities. We propose a sequential importance sampling algorithm to estimate the cardinality of the sample space of genealogical trees under different coalescent resolutions. Our sampling scheme proceeds sequentially across the set of combinatorial constraints imposed by the data, which in this work are completely linked sequences of DNA at a non recombining segment. We analyze the cardinality of different genealogical tree spaces on simulations to study the settings that favor coarser resolutions. We apply our method to estimate the cardinality of genealogical tree spaces from mtDNA data from the 1000 genomes and a sample from a Melanesian population at the β -globin locus.

The large state space of gene genealogies is a major hurdle for inference methods based on Kingman's coalescent. Here, we present a new Bayesian approach for inferring past population sizes, which relies on a lower-resolution coalescent process that we refer to as "Tajima's coalescent." Tajima's coalescent has a drastically smaller state space, and hence it is a computationally more efficient model, than the standard Kingman coalescent. We provide a new algorithm for efficient and exact likelihood calculations for data without recombination, which exploits a directed acyclic graph and a correspondingly tailored Markov Chain Monte Carlo method. We compare the performance of our Bayesian Estimation of population size changes by Sampling Tajima's Trees (BESTT) with a popular implementation of coalescent-based inference in BEAST using simulated and human data. We empirically demonstrate that BESTT can accurately infer effective population sizes, and it further provides an efficient alternative to the Kingman's coalescent. The algorithms described here are implemented in the R package phylodyn, which is available for download at https://github.com/JuliaPalacios/phylodyn., (Copyright © 2019 by the Genetics Society of America.)

Knit, woven, and nonwoven fabrics offer a diverse range of stretch and strain limiting mechanical properties that can be leveraged to produce tailored, whole-body deformation mechanics of soft robotic systems. This work presents new insights and methods for combining heterogeneous fabric material layers to create soft fabric-based actuators. This work demonstrates that a range of multi-degree-of-freedom motions can be generated by varying fabrics and their layered arrangements when a thin airtight bladder is inserted between them and inflated. Specifically, we present bending and straightening fabric-based actuators that are simple to manufacture, lightweight, require low operating pressures, display a high torque-to-weight ratio, and occupy a low volume in their unpressurized state. Their utility is demonstrated through their integration into a glove that actively assists hand opening and closing.

Background: Spinal cord injury is a devastating condition that can dramatically impact hand motor function. Passive and active assistive devices are becoming more commonly used to enhance lost hand strength and dexterity. Soft robotics is an emerging discipline that combines the classical principles of robotics with soft materials and could provide a new class of active assistive devices. Soft robotic assistive devices enable a human-robot interaction facilitated by compliant and light-weight structures. The scope of this work was to demonstrate that a fabric-based soft robotic glove can effectively assist participants affected by spinal cord injury in manipulating objects encountered in daily living., Methods: The Toronto Rehabilitation Institute Hand Function Test was administered to 9 participants with C4-C7 spinal cord injuries to assess the functionality of the soft robotic glove. The test included object manipulation tasks commonly encountered during activities of daily living (ADL) and lift force measurements. The test was administered to each participant twice; once without the assistive glove to provide baseline data and once while wearing the assistive glove. The object manipulation subtests were evaluated using a linear mixed model, including interaction effects of variables such as time since injury. The lift force measures were separately evaluated using the Wilcoxon signed-rank test., Results: The soft robotic glove improved object manipulation in ADL tasks. The difference in mean scores between baseline and assisted conditions was significant across all participants and for all manipulated objects. An improvement of 33.42 ± 15.43% relative to the maximal test score indicates that the glove sufficiently enhances hand function during ADL tasks. Moreover, lift force also increased when using the assistive soft robotic glove, further demonstrating the effectiveness of the device in assisting hand function., Conclusions: The results gathered in this study validate our fabric-based soft robotic glove as an effective device to assist hand function in individuals who have suffered upper limb paralysis following a spinal cord injury.

Stretchable strain sensors, as the soft mechanical interface, provide the key mechanical information of the systems for healthcare monitoring, rehabilitation assistance, soft exoskeletal devices, and soft robotics. Stretchable strain sensors based on 2D flat film have been widely developed to monitor the in-plane force applied within the plane where the sensor is placed. However, to comprehensively obtain the mechanical feedback, the capability to detect the out-of-plane force, caused by the interaction outside of the plane where the senor is located, is needed. Herein, a 3D-structured stretchable strain sensor is reported to monitor the out-of-plane force by employing 3D printing in conjunction with out-of-plane capillary force-assisted self-pinning of carbon nanotubes. The 3D-structured sensor possesses large stretchability, multistrain detection, and strain-direction recognition by one single sensor. It is demonstrated that out-of-plane forces induced by the air/fluid flow are reliably monitored and intricate flow details are clearly recorded. The development opens up for the exploration of next-generation 3D stretchable sensors for electronic skin and soft robotics., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Proprioceptive function can become enhanced during motor learning. Yet, we have incomplete knowledge to what extent proprioceptive function is trainable and how a training that enhances proprioception may influence performance in untrained motor skills. To address this knowledge gap, healthy young adults (N = 14) trained in a visuomotor task that required learners to make increasingly accurate wrist movements. Using a robotic exoskeleton coupled with a virtual visual environment, participants tilted a virtual table through continuous wrist flexion/extension movements with the goal to position a rolling ball on table into a target. With learning progress, the level of difficulty increased by altering the virtual ball mechanics and the gain between joint movement and ball velocity. Before and after training, wrist position sense acuity and spatial movement accuracy in an untrained, discrete wrist-pointing task was assessed using the same robot. All participants showed evidence of proprioceptive-motor learning. Mean position sense discrimination threshold improved by 34%. Wrist movement accuracy in the untrained pointing task improved by 27% in 13/14 participants. This demonstrates that a short sensorimotor training challenging proprioception can a) effectively enhance proprioceptive acuity and b) improve the accuracy of untrained movement. These findings provide a scientific basis for applying such somatosensory-based motor training to clinical populations with known proprioceptive dysfunction to enhance sensorimotor performance.

In this paper, we present a soft wearable robot for the shoulder which has the potential to assist individuals suffering from a range of neuromuscular conditions affecting the shoulder to perform activities of daily living. This wearable robot combines two types of soft textile pneumatic actuators which were custom developed for this particular application to support the upper arm through shoulder abduction and horizontal flexion/extension. The advantage of a textile-based approach is that the robot can be lightweight, low-profile, comfortable and non-restrictive to the wearer, and easy to don like an item of clothing. The actuator's ability to fold flat when not in use allows the robot to be almost invisible under clothing, potentially allowing the user to avoid any stigma associated with using assistive devices in public. To abduct the arm, a textilebased pneumatic actuator was developed to fit within the axilla to push the arm upwards, while a pair of smaller actuators pivot the abduction actuator to allow for horizontal extension and flexion. The individual textile actuators were experimentally evaluated before being integrated into a wearable garment. Human subject testing was performed to evaluate the ability of the robot to assist the arm by monitoring changes in biological muscle activity when comparing the robot powered on and off. Preliminary results show large reductions in muscular effort in targeted muscles, demonstrating the feasibility and promise of such a soft wearable robot for the shoulder.

The development of a portable assistive device to aid patients affected by neuromuscular disorders has been the ultimate goal of assistive robots since the late 1960s. Despite significant advances in recent decades, traditional rigid exoskeletons are constrained by limited portability, safety, ergonomics, autonomy and, most of all, cost. In this study, we present the design and control of a soft, textile-based exosuit for assisting elbow flexion/extension and hand open/close. We describe a model-based design, characterisation and testing of two independent actuator modules for the elbow and hand, respectively. Both actuators drive a set of artificial tendons, routed through the exosuit along specific load paths, that apply torques to the human joints by means of anchor points. Key features in our design are under-actuation and the use of electromagnetic clutches to unload the motors during static posture. These two aspects, along with the use of 3D printed components and off-the-shelf fabric materials, contribute to cut down the power requirements, mass and overall cost of the system, making it a more likely candidate for daily use and enlarging its target population. Low-level control is accomplished by a computationally efficient machine learning algorithm that derives the system's model from sensory data, ensuring high tracking accuracy despite the uncertainties deriving from its soft architecture. The resulting system is a low-profile, low-cost and wearable exosuit designed to intuitively assist the wearer in activities of daily living., Competing Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Patent and invention disclosure “MODULAR AND ENERGY EFFICIENT SOFT WEARABLE EXOSUIT”. PCT Application No.: PCT/SG2016/050383. International Filing Date: 11 August 2016.

Proprioception is essential for planning and controlling limb posture and movement. In our recent work, we introduced a standardized robot-aided method for measuring proprioceptive discrimination thresholds at the wrist to obtain reliable and accurate measures of proprioceptive acuity. Weber's law defines discrimination thresholds as a constant ratio between the just noticeable difference and the reference or standard stimulus. Reporting Weber's fractions thus provides the possibility of comparing results with the reports of others collected worldwide. This work aims to determine that Weber's Law holds for proprioceptive discrimination thresholds and to provide Weber's fraction for wrist joint proprioception. To this end, eight healthy subjects experienced two passive wrist movements of different amplitude and verbally indicated which was larger. An adaptive psychophysical procedure established the amplitude of the largest stimulus according to participants' responses. This comparison stimulus was then compared to a standard stimulus amplitude of 10°, 20°, 30° or 40°. The discrimination thresholds for each standard stimulus were established at the 75% correct response level. The obtained thresholds followed Weber's Law indicating that larger amplitudes were associated with higher discrimination thresholds. Based on a linear regression function the overall Weber's fraction, defined as the slope of the line, was computed to be 0.09. This result expands the present limited knowledge on wrist proprioception showing that its proprioceptive acuity follows Weber's law.

Proprioception provides information about limb configuration which are essential for planning and controlling its posture and movement. Asymmetries in the way dominant and non-dominant limbs exploit proprioceptive information have been previously evaluated, with contradictory results due to the difference in the employed methodology. A measure of proprioceptive acuity that does not reflect the influence of one limb on the other consists in the evaluation of the psychophysical threshold. This metric, evaluated separately for each limb and involving only passive movements, reflects a reliable measure of proprioceptive acuity. The aim of this work is to first evaluate the proprioceptive acuity of the non-dominant wrist joint in flexion/extension and adduction/abduction and to compare these results to the acuity of the dominant wrist. Data were collected during a unidirectional 2-alternative-forcedchoice test performed by six right-handed subjects. We found acuity of 1.31°, 1.26°, 1.33° and 1.63° respectively for abduction, adduction, extension and flexion of the non-dominant wrist. Acuity of the dominant wrist was assessed for five of the subjects for abduction and flexion and resulted lower (mean values were respectively 1.64° and 2.14°). The preliminary results suggest a leading role of the non-dominant wrist in the processing of the proprioceptive feedback.

Proprioception is the sense of the body awareness. Proprioceptive deficits represent frequent consequences of several neurological conditions like stroke, Parkinson's disease and others. The assessment of such somatosensory function is crucial, although the available clinical tests are not sensitive enough. The human wrist is a crucial joint for many activities of daily living and to address the lack of its characterization in terms of proprioceptive acuity the authors in previous studies proposed a novel method that combined the use of a 3-DoF robot and a threshold haunting paradigm. Further experiments were performed to characterize the proprioceptive acuity of the dominant wrist for adduction, extension, pronation and supination by using a 2-alternative-forced-choice test. The acuity thresholds obtained from six subjects (mean values ± standard deviation of 1.65±0.39 for extension, 1.13±0.34 for adduction, 1.90±0.58 for pronation and 1.70±0.30 for supination) were finally combined with the ones harvested in the previous studies for flexion and abduction in order to build the first comprehensive database of human wrist proprioceptive acuity.

Introduction: Impaired proprioception severely affects the control of gross and fine motor function. However, clinical assessment of proprioceptive deficits and its impact on motor function has been difficult to elucidate. Recent advances in haptic robotic interfaces designed for sensorimotor rehabilitation enabled the use of such devices for the assessment of proprioceptive function., Purpose: This study evaluated the feasibility of a wrist robot system to determine proprioceptive discrimination thresholds for two different DoFs of the wrist. Specifically, we sought to accomplish three aims: first, to establish data validity; second, to show that the system is sensitive to detect small differences in acuity; third, to establish test-retest reliability over repeated testing., Methodology: Eleven healthy adult subjects experienced two passive wrist movements and had to verbally indicate which movement had the larger amplitude. Based on a subject's response data, a psychometric function was fitted and the wrist acuity threshold was established at the 75% correct response level. A subset of five subjects repeated the experimentation three times (T1, T2, and T3) to determine the test-retest reliability., Results: Mean threshold for wrist flexion was 2.15°± 0.43° and 1.52°± 0.36° for abduction. Encoder resolutions were 0.0075°(flexion-extension) and 0.0032°(abduction-adduction). Motor resolutions were 0.2°(flexion-extension) and 0.3°(abduction-adduction). Reliability coefficients were r T2-T1 = 0.986 and r T3-T2 = 0.971., Conclusion: We currently lack established norm data on the proprioceptive acuity of the wrist to establish direct validity. However, the magnitude of our reported thresholds is physiological, plausible, and well in line with available threshold data obtained at the elbow joint. Moreover, system has high resolution and is sensitive enough to detect small differences in acuity. Finally, the system produces reliable data over repeated testing.

A novel actuator is introduced that combines an elastically compliant composite structure with conventional electromechanical elements. The proposed design is analogous to that used in Series Elastic Actuators, its distinctive feature being that the compliant composite part offers different stable configurations. In other words, its elastic potential presents points of local minima that correspond to robust stable positions (multistability). This potential is known a priori as a function of the structural geometry, thus providing tremendous benefits in terms of control implementation. Such knowledge enables the complexities arising from the additional degrees of freedom associated with link deformations to be overcome and uncover challenges that extends beyond those posed by standard rigidlink robot dynamics. It is thought that integrating a multistable elastic element in a robotic transmission can provide new scenarios in the field of assistive robotics, as the system may help a subject to stand or carry a load without the need for an active control effort by the actuators.