Improving Walking Energy Efficiency in Transtibial Amputees Through the Integration of a Low-Power Actuator in an ESAR Foot.

Reducing energy consumption during walking is a critical goal for transtibial amputees. The study presents the evaluation of a semi-active prosthesis with five transtibial amputees. The prosthesis has a low-power actuator integrated in parallel into an energy-storing-and-releasing foot. The actuator is controlled to compress the foot during the stance phase, supplementing the natural compression due to the user's dynamic interaction with the ground, particularly during the ankle dorsiflexion phase, and to release the energy stored in the foot during the push-off phase, to enhance propulsion. The control strategy is adaptive to the user's gait patterns and speed. The clinical protocol to evaluate the system included treadmill and overground walking tasks. The results showed that walking with the semi-active prosthesis reduced the Physiological Cost Index of transtibial amputees by up to 16% compared to walking using the subjects' proprietary prosthesis. No significant alterations were observed in the spatiotemporal gait parameters of the participants, indicating the module's compatibility with users' natural walking patterns. These findings highlight the potential of the mechatronic actuator in effectively reducing energy expenditure during walking for transtibial amputees. The proposed prosthesis may bring a positive impact on the quality of life, mobility, and functional performance of individuals with transtibial amputation.

Uneven Terrain Recognition Using Neuromorphic Haptic Feedback.

Recent years have witnessed relevant advancements in the quality of life of persons with lower limb amputations thanks to the technological developments in prosthetics. However, prostheses that provide information about the foot-ground interaction, and in particular about terrain irregularities, are still missing on the market. The lack of tactile feedback from the foot sole might lead subjects to step on uneven terrains, causing an increase in the risk of falling. To address this issue, a biomimetic vibrotactile feedback system that conveys information about gait and terrain features sensed by a dedicated insole has been assessed with intact subjects. After having shortly experienced both even and uneven terrains, the recruited subjects discriminated them with an accuracy of 87.5%, solely relying on the replay of the vibrotactile feedback. With the objective of exploring the human decoding mechanism of the feedback startegy, a KNN classifier was trained to recognize the uneven terrains. The outcome suggested that the subjects achieved such performance with a temporal dynamics of 45 ms. This work is a leap forward to assist lower-limb amputees to appreciate the floor conditions while walking, adapt their gait and promote a more confident use of their artificial limb.

Proposal for an ICF-based methodology to foster the return to work of persons with disability.

BACKGROUND: Employment is an essential component of life as it provides income, sense of engagement and opportunities for personal development. Unemployment due to disability following an accident may have dramatic social and psychological consequences on individuals; it is thus fundamental to foster return to work of these persons. OBJECTIVE: The present work was aimed to develop a methodology determining suitable jobs for people living with disability after a job-related accident. METHODS: The Occupational Information Network (O*NET) taxonomy was combined with the International Classification of Functioning, Disability and Health (ICF) to match individual resources with specific job requirements. ICF Linking Rules were employed by two independent groups of researchers to associate ICF codes to O*NET skill and ability descriptors. RESULTS: O*NET descriptors were linked to 92 unique ICF codes. A "Criticality score" combining ICF and O*NET features to assess suitability of selected jobs for persons with disabilities was also proposed. CONCLUSIONS: The proposed methodology represents a novel instrument to support return to work; the capability to assess specific work-related facets through the lens of both the ICF model and O*NET taxonomy would conceivably provide vocational rehabilitation specialists and occupational therapists with a useful tool fostering job placement of workers with disability.

Degree of Safety Against Falls Provided by 4 Different Prosthetic Knee Types in People With Transfemoral Amputation: A Retrospective Observational Study.

OBJECTIVE: People with transfemoral amputation have balance and mobility problems and are at high risk of falling. An adequate prosthetic prescription is essential to maximize their functional levels and enhance their quality of life. This study aimed to evaluate the degree of safety against falls offered by different prosthetic knees. METHODS: A retrospective study was conducted using data from a center for prosthetic fitting and rehabilitation. Eligible individuals were adults with unilateral transfemoral amputation or knee disarticulation. The prosthetic knee models were grouped into 4 categories: locked knees, articulating mechanical knees (AMKs), fluid-controlled knees (FK), and microprocessor-controlled knees (MPK). The outcome was the number of falls experienced during inpatient rehabilitation while wearing the prosthesis. Association analyses were performed with mixed-effect Poisson models. Propensity score weighting was used to adjust causal estimates for participant confounding factors. RESULTS: Data on 1486 hospitalizations of 815 individuals were analyzed. Most hospitalizations (77.4%) were related to individuals with amputation due to trauma. After propensity score weighting, the knee category was significantly associated with falls. People with FK had the highest rate of falling (incidence rate = 2.81 falls per 1000 patient days, 95% CI = 1.96 to 4.02). FK significantly increased the risk of falling compared with MPK (incidence rate ratio [IRRFK-MPK] = 2.44, 95% CI = 1.20 to 4.96). No other comparison among knee categories was significant. CONCLUSIONS: Fluid-controlled prosthetic knees expose inpatients with transfemoral amputation to higher incidence of falling than MPK during rehabilitation training. IMPACT: These findings can guide clinicians in the selection of safe prostheses and reduction of falls in people with transfemoral amputation during inpatient rehabilitation.

Survey of transfemoral amputee experience and priorities for the user-centered design of powered robotic transfemoral prostheses.

BACKGROUND: Transfemoral amputees experience a complex host of physical, psychological, and social challenges, compounded by the functional limitations of current transfemoral prostheses. However, the specific relationships between human factors and prosthesis design and performance characteristics have not yet been adequately investigated. The present study aims to address this knowledge gap. METHODS: A comprehensive single-cohort survey of 114 unilateral transfemoral amputees addressed a broad range of demographic and clinical characteristics, functional autonomy, satisfaction and attitudes towards their current prostheses, and design priorities for an ideal transfemoral prosthesis, including the possibility of active assistance from a robotic knee unit. The survey was custom-developed based on several standard questionnaires used to assess motor abilities and autonomy in activities of daily living, prosthesis satisfaction, and quality of life in lower-limb amputees. Survey data were analyzed to compare the experience (including autonomy and satisfaction) and design priorities of users of transfemoral prostheses with versus without microprocessor-controlled knee units (MPKs and NMPKs, respectively), with a subsequent analyses of cross-category correlation, principal component analysis (PCA), cost-sensitivity segmentation, and unsupervised K-means clustering applied within the most cost-sensitive participants, to identify functional groupings of users with respect to their design priorities. RESULTS: The cohort featured predominantly younger (< 50 years) traumatic male amputees with respect to the general transfemoral amputee population, with pronounced differences in age distribution and amputation etiology (traumatic vs. non-traumatic) between MPK and NMPK groups. These differences were further reflected in user experience, with MPK users reporting significantly greater overall functional autonomy, satisfaction, and sense of prosthesis ownership than those with NMPKs, in conjunction with a decreased incidence of instability and falls. Across all participants, the leading functional priorities for an ideal transfemoral prosthesis were overall stability, adaptability to variable walking velocity, and lifestyle-related functionality, while the highest-prioritized general characteristics were reliability, comfort, and weight, with highly variable prioritization of cost according to reimbursement status. PCA and user clustering analyses revealed the possibility for functionally relevant groupings of prosthesis features and users, based on their differential prioritization of these features-with implications towards prosthesis design tradeoffs. CONCLUSIONS: This study's findings support the understanding that when appropriately prescribed according to patient characteristics and needs in the context of a proactive rehabilitation program, advanced transfemoral prostheses promote patient mobility, autonomy, and overall health. Survey data indicate overall stability, modularity, and versatility as key design priorities for the continued development of transfemoral prosthesis technology. Finally, observed associations between prosthesis type, user experience, and attitudes concerning prosthesis ownership suggest both that prosthesis characteristics influence device acceptance and functional outcomes, and that psychosocial factors should be specifically and proactively addressed during the rehabilitation process.

Types and severity of physical impairments of para taekwondo athletes.

BACKGROUND: Para taekwondo has only recently been added to the Paralympic games scheduled to be held in 2021; however, there is limited research on the classification of the para taekwondo athletes. This study aimed to provide details on the impairments and disabilities of the para taekwondo players. The secondary objective was to investigate the relationship between some of the proposed factors and the athletes' rankings. METHODS: The data of 556 para taekwondo athletes (119 females and 437 males), who had been classified over the past 5 years, were analyzed. RESULTS: The K44 class was the most popular, and 61% of the classified athletes belonged to this class. Acute injury from trauma was the most frequent cause of impairment, and 62.3% of all impairments/disabilities occurred during 0-5 years of age. Approximately 28% of the athletes had <1 year of training prior to international competitions. One-way analysis of variance performed for the combined length of the upper limbs showed significant differences (F(3,311)=455.78, P<0.001) among the K41-K44 classes. There were weak correlations (ρ<0.1) between the ranking and the age of the disability/impairment onset, combined length of the upper limbs, and type of disability. CONCLUSIONS: Continued data collection that provides insights into the impairment profiles of para taekwondo athletes is needed to improve the current classification system in order to enhance the safety and fairness.

Restoring Tactile sensations via neural interfaces for real-time force-and-slippage closed-loop control of bionic hands.

Despite previous studies on the restoration of tactile sensation on the fingers and the hand, there are no examples of use of the routed sensory information to finely control the prosthesis hand in complex grasp and manipulation tasks. Here it is shown that force and slippage sensations can be elicited in an amputee subject by means of biologically-inspired slippage detection and encoding algorithms, supported by a stick-slip model of the performed grasp. A combination of cuff and intraneural electrodes was implanted for eleven weeks in a young woman with hand amputation, and was shown to provide close-to-natural force and slippage sensations, paramount for significantly improving the subject's manipulative skills with the prosthesis. Evidence is provided about the improvement of the subject's grasping and manipulation capabilities over time, thanks to neural feedback. The elicited tactile sensations enabled the successful fulfillment of fine grasp and manipulation tasks with increasing complexity. Grasp performance was quantitatively assessed by means of instrumented objects and a purposely developed metrics. Closed-loop control capabilities enabled by the neural feedback were compared to those achieved without feedback. Further, the work investigates whether the described amelioration of motor performance in dexterous tasks had as central neurophysiological correlates changes in motor cortex plasticity and whether such changes were of purely motor origin, or else the effect of a strong and persistent drive of the sensory feedback.

Simultaneous sEMG Classification of Hand/Wrist Gestures and Forces.

Surface electromyography (sEMG) signals represent a promising approach for decoding the motor intention of amputees to control a multifunctional prosthetic hand in a non-invasive way. Several approaches based on proportional amplitude methods or simple thresholds on sEMG signals have been proposed to control a single degree of freedom at time, without the possibility of increasing the number of controllable multiple DoFs in a natural manner. Myoelectric control based on PR techniques have been introduced to add multiple DoFs by keeping low the number of electrodes and allowing the discrimination of different muscular patterns for each class of motion. However, the use of PR algorithms to simultaneously decode both gestures and forces has never been studied deeply. This paper introduces a hierarchical classification approach with the aim to assess the desired hand/wrist gestures, as well as the desired force levels to exert during grasping tasks. A Finite State Machine was introduced to manage and coordinate three classifiers based on the Non-Linear Logistic Regression algorithm. The classification architecture was evaluated across 31 healthy subjects. The "hand/wrist gestures classifier," introduced for the discrimination of seven hand/wrist gestures, presented a mean classification accuracy of 98.78%, while the "Spherical and Tip force classifier," created for the identification of three force levels, reached an average accuracy of 98.80 and 96.09%, respectively. These results were confirmed by Linear Discriminant Analysis (LDA) with time domain features extraction, considered as ground truth for the final validation of the performed analysis. A Wilcoxon Signed-Rank test was carried out for the statistical analysis of comparison between NLR and LDA and statistical significance was considered at p < 0.05. The comparative analysis reports not statistically significant differences in terms of F1Score performance between NLR and LDA. Thus, this study reveals that the use of non-linear classification algorithm, as NLR, is as much suitable as the benchmark LDA classifier for implementing an EMG pattern recognition system, able both to decode hand/wrist gestures and to associate different performed force levels to grasping actions.

EMG and ENG-envelope pattern recognition for prosthetic hand control.

BACKGROUND: This paper proposes a new approach for neural control of hand prostheses, grounded on pattern recognition applied to the envelope of neural signals (eENG). NEW METHOD: The ENG envelope was computed by taking into account the amplitude and the occurrence of the spike in the neural recording. A pattern recognition algorithm applied on muscular signals was defined as a reference and a comparative analysis with traditionally adopted Spike Sorting Algorithms (SSA) for neural signals has been carried out. Method validation was divided in two parts: firstly, neural signals recorded from one amputee subject through intraneural electrodes were offline analyzed to discriminate between the two performed gestures; secondly, algorithm performance decay with the increase of the number of classes was studied through synthetic data. RESULTS: An accuracy of 98.26% with real data was reached with the pattern recognition applied to eENG. SSA reached an accuracy of 70%. Increasing the number of classes worsens the accuracy of this algorithm. Additionally, computational time for the pattern recognition applied to eENG is very low (32.6 µs for each sample in the data window analyzed). COMPARISON WITH EXISTING METHOD: The eENG was proved to be more reliable in decoding the user intention than the SSA algorithm and it is computationally efficient. CONCLUSIONS: It was demonstrated that it is possible to apply the well-known techniques of EMG pattern recognition to a conveniently processed neural signal and can pave the way to the application of neural gesture decoding in upper limb prosthetics.

Artificial Sphincters to Manage Urinary Incontinence: A Review.

Urinary incontinence affects more than 300 million people worldwide. The implantation of a medical device called an artificial urinary sphincter (AUS) is the gold standard treatment when conservative and minimally invasive therapies fail. In this article, the AUSs (extra-urethral and endo-urethral sphincters) available on the market, both presented at the research level and filed as patents, are reviewed. The ability of the different solutions to effectively replace the natural sphincter are discussed, together with advantages and some possible side effects, such as tissue atrophy, overall invasiveness of the implant, and so forth. Finally, future research priorities are discussed for both endo-urethral and extra-urethral approaches considering key engineering aspects, such as materials, compression and closure mechanisms, and implantation methods, with the long-term aim of developing an effective, reliable, durable, and minimally invasive AUS capable of restoring a normal quality of life for incontinent patients.

Corrections to "Treatment of the Partial Hand Amputation: An Engineering Perspective".

In the above paper, by Imbinto et al. (IEEE Rev. Biomed. Eng., vol. 9, pp. 32-48, 2016), typographical errors appear in (1) (2) (3), whereas (4) is missing of a factor; all the equations are reported within Section III-C of the paper. The modifications are provided in this paper.

A Motion Analysis Protocol for Kinematic Assessment of Poly-Articulated Prosthetic Hands With Cosmetic Gloves.

To provide upper-limb amputees with devices that best fit their needs and to test innovative solutions, it is necessary to quantitatively appraise a device performance with rigorous measurement methods. The aim of this work was to define an optimal motion analysis protocol, suitable for optoelectronic systems, to measure the kinematics of poly-articulated hands even when covered by a cosmetic glove. This is a fundamental aspect, because gloves can decrease device speed and range of motion and, ultimately, patients' acceptance of the artificial limb. In this work, different mathematical models of the joints and marker-sets for motion analysis were conceived. A regression model to choose a reduced marker-set for studying the hand performance with different cosmetic glove models was developed. The proposed approaches for finger motion analysis were experimentally tested on the index finger of the i-Limb, a commercial myoelectric poly-articulated prosthetic hand, but the results can be easily extended to the whole hand and to other poly-articulated prosthetic hands. The methods proposed for the performance analysis of prosthetic hands points out that the cosmetic gloves imply a reduction of the finger flexion/extension (F/E) angles and of the motion velocity. This draws attention to the need for performing independent cyclic tests on commercial products with various cosmetic solutions to better guide component selection.

NLR, MLP, SVM, and LDA: a comparative analysis on EMG data from people with trans-radial amputation.

BACKGROUND: Currently, the typically adopted hand prosthesis surface electromyography (sEMG) control strategies do not provide the users with a natural control feeling and do not exploit all the potential of commercially available multi-fingered hand prostheses. Pattern recognition and machine learning techniques applied to sEMG can be effective for a natural control based on the residual muscles contraction of amputated people corresponding to phantom limb movements. As the researches has reached an advanced grade accuracy, these algorithms have been proved and the embedding is necessary for the realization of prosthetic devices. The aim of this work is to provide engineering tools and indications on how to choose the most suitable classifier, and its specific internal settings for an embedded control of multigrip hand prostheses. METHODS: By means of an innovative statistical analysis, we compare 4 different classifiers: Nonlinear Logistic Regression, Multi-Layer Perceptron, Support Vector Machine and Linear Discriminant Analysis, which was considered as ground truth. Experimental tests have been performed on sEMG data collected from 30 people with trans-radial amputation, in which the algorithms were evaluated for both performance and computational burden, then the statistical analysis has been based on the Wilcoxon Signed-Rank test and statistical significance was considered at p < 0.05. RESULTS: The comparative analysis among NLR, MLP and SVM shows that, for either classification performance and for the number of classification parameters, SVM attains the highest values followed by MLP, and then by NLR. However, using as unique constraint to evaluate the maximum acceptable complexity of each classifier one of the typically available memory of a high performance microcontroller, the comparison pointed out that for people with trans-radial amputation the algorithm that produces the best compromise is NLR closely followed by MLP. This result was also confirmed by the comparison with LDA with time domain features, which provided not significant differences of performance and computational burden between NLR and LDA. CONCLUSIONS: The proposed analysis would provide innovative engineering tools and indications on how to choose the most suitable classifier based on the application and the desired results for prostheses control.

Comparative performance analysis of M-IMU/EMG and voice user interfaces for assistive robots.

People with a high level of disability experience great difficulties to perform activities of daily living and resort to their residual motor functions in order to operate assistive devices. The commercially available interfaces used to control assistive manipulators are typically based on joysticks and can be used only by subjects with upper-limb residual mobilities. Many other solutions can be found in the literature, based on the use of multiple sensory systems for detecting the human motion intention and state. Some of them require a high cognitive workload for the user. Some others are more intuitive and easy to use but have not been widely investigated in terms of usability and user acceptance. The objective of this work is to propose an intuitive and robust user interface for assistive robots, not obtrusive for the user and easily adaptable for subjects with different levels of disability. The proposed user interface is based on the combination of M-IMU and EMG for the continuous control of an arm-hand robotic system by means of M-IMUs. The system has been experimentally validated and compared to a standard voice interface. Sixteen healthy subjects volunteered to participate in the study: 8 subjects used the combined M-IMU/EMG robot control, and 8 subjects used the voice control. The arm-hand robotic system made of the KUKA LWR 4+ and the IH2 Azzurra hand was controlled to accomplish the daily living task of drinking. Performance indices and evaluation scales were adopted to assess performance of the two interfaces.

Evaluation of Pressure Capacitive Sensors for Application in Grasping and Manipulation Analysis.

The analysis of the human grasping and manipulation capabilities is paramount for investigating human sensory-motor control and developing prosthetic and robotic hands resembling the human ones. A viable solution to perform this analysis is to develop instrumented objects measuring the interaction forces with the hand. In this context, the performance of the sensors embedded in the objects is crucial. This paper focuses on the experimental characterization of a class of capacitive pressure sensors suitable for biomechanical analysis. The analysis was performed in three loading conditions (Distributed load, 9 Tips load, and Wave-shaped load, thanks to three different inter-elements) via a traction/compression testing machine. Sensor assessment was also carried out under human- like grasping condition by placing a silicon material with the same properties of prosthetic cosmetic gloves in between the sensor and the inter-element in order to simulate the human skin. Data show that the input-output relationship of the analyzed, sensor is strongly influenced by both the loading condition (i.e., type of inter-element) and the grasping condition (with or without the silicon material). This needs to be taken into account to avoid significant measurement error. To go over this hurdle, the sensors have to be calibrated under each specific condition in order to apply suitable corrections to the sensor output and significantly improve the measurement accuracy.

Literature Review on Needs of Upper Limb Prosthesis Users.

The loss of one hand can significantly affect the level of autonomy and the capability of performing daily living, working and social activities. The current prosthetic solutions contribute in a poor way to overcome these problems due to limitations in the interfaces adopted for controlling the prosthesis and to the lack of force or tactile feedback, thus limiting hand grasp capabilities. This paper presents a literature review on needs analysis of upper limb prosthesis users, and points out the main critical aspects of the current prosthetic solutions, in terms of users satisfaction and activities of daily living they would like to perform with the prosthetic device. The ultimate goal is to provide design inputs in the prosthetic field and, contemporary, increase user satisfaction rates and reduce device abandonment. A list of requirements for upper limb prostheses is proposed, grounded on the performed analysis on user needs. It wants to (i) provide guidelines for improving the level of acceptability and usefulness of the prosthesis, by accounting for hand functional and technical aspects; (ii) propose a control architecture of PNS-based prosthetic systems able to satisfy the analyzed user wishes; (iii) provide hints for improving the quality of the methods (e.g., questionnaires) adopted for understanding the user satisfaction with their prostheses.

Control of Prosthetic Hands via the Peripheral Nervous System.

This paper intends to provide a critical review of the literature on the technological issues on control and sensorization of hand prostheses interfacing with the Peripheral Nervous System (i.e., PNS), and their experimental validation on amputees. The study opens with an in-depth analysis of control solutions and sensorization features of research and commercially available prosthetic hands. Pros and cons of adopted technologies, signal processing techniques and motion control solutions are investigated. Special emphasis is then dedicated to the recent studies on the restoration of tactile perception in amputees through neural interfaces. The paper finally proposes a number of suggestions for designing the prosthetic system able to re-establish a bidirectional communication with the PNS and foster the prosthesis natural control.

Treatment of the Partial Hand Amputation: An Engineering Perspective.

Partial hand amputation is perhaps the most frequent amputation level, worldwide. Although its annual incidence in western countries is roughly 1:18 000 inhabitants, the treatments of partial hand amputations have modestly progressed so far. We have identified three main limitation factors to this progress: 1) the wide range of anatomical and functional presentations, which makes difficult to find standardized and scalable solutions; 2) the technological complexity in replacing the motor and sensory function of a lost digit in the size of a digit; and 3) the fact that a partial hand can be functionally successful mostly when it restores a lost opposition movement, i.e., the ability to oppose the thumb against the fingers while providing enough grasping force and aperture width. This review presents an overview of the existing surgical and technological solutions for treating partial hand amputations, and is specifically targeted to (biomedical) engineers. We critically highlighted the advantages, limitations, and open challenges. Remarkably, current fitting procedures rely on manual approaches by skilled prosthetic technicians rather than on modern engineering methods. Hence, the objective of this study is to comprehensively but concisely overview the field in order to inspire engineers to develop new systems and procedures able to address current open issues.

First in vivo assessment of "Outwalk": a novel protocol for clinical gait analysis based on inertial and magnetic sensors.

A protocol named "Outwalk" was recently proposed to measure the thorax-pelvis and lower-limb kinematics during gait in free-living conditions, by means of an inertial and magnetic measurement system (IMMS). The aim of this study was to validate Outwalk on four healthy subjects when it is used in combination with a specific IMMS (Xsens Technologies, NL), against a reference protocol (CAST) and measurement system (optoelectronic system; Vicon, Oxford Metrics Group, UK). For this purpose, we developed an original approach based on three tests, which allowed to separately investigate: (1) the consequences on joint kinematics of the differences between protocols (Outwalk vs. CAST), (2) the accuracy of the hardware (Xsens vs. Vicon), and (3) the summation of protocols' differences and hardware accuracy (Outwalk + Xsens vs. CAST + Vicon). In order to assess joint-angles similarity, the coefficient of multiple correlation (CMC) was used. For test 3, the CMC showed that Outwalk + Xsens and CAST + Vicon kinematics can be interchanged, offset included, for hip, knee and ankle flexion-extension, and hip ab-adduction (CMC > 0.88). The other joint-angles can be interchanged offset excluded (CMC > 0.85). Tests 1 and 2 also showed that differences in offset between joint-angles were predominantly induced by differences in the protocols; differences in correlation by both hardware and protocols; differences in range of motion by the Xsens accuracy. Results thus support the commencement of a clinical trial of Outwalk on transtibial amputees.

Fine detection of grasp force and posture by amputees via surface electromyography.

The state-of-the-art feed-forward control of active hand prostheses is rather poor. Even dexterous, multi-fingered commercial prostheses are controlled via surface electromyography (EMG) in a way that enforces a few fixed grasping postures, or a very basic estimate of force. Control is not natural, meaning that the amputee must learn to associate, e.g., wrist flexion and hand closing. Nevertheless, recent literature indicates that much more information can be gathered from plain, old surface EMG. To check this issue, we have performed an experiment in which three amputees train a Support Vector Machine (SVM) using five commercially available EMG electrodes while asked to perform various grasping postures and forces with their phantom limbs. In agreement with recent neurological studies on cortical plasticity, we show that amputees operated decades ago can still produce distinct and stable signals for each posture and force. The SVM classifies the posture up to a precision of 95% and approximates the force with an error of as little as 7% of the signal range, sample-by-sample at 25Hz. These values are in line with results previously obtained by healthy subjects while feed-forward controlling a dexterous mechanical hand. We then conclude that our subjects could finely feed-forward control a dexterous prosthesis in both force and position, using standard EMG in a natural way, that is, using the phantom limb.