Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation.

BACKGROUND: Virtual and augmented reality (AR) have become popular modalities for training myoelectric prosthesis control with upper-limb amputees. While some systems have shown moderate success, it is unclear how well the complex motor skills learned in an AR simulation transfer to completing the same tasks in physical reality. Limb loading is a possible dimension of motor skill execution that is absent in current AR solutions that may help to increase skill transfer between the virtual and physical domains. METHODS: We implemented an immersive AR environment where individuals could operate a myoelectric virtual prosthesis to accomplish a variety of object relocation manipulations. Intact limb participants were separated into three groups, the load control (CGLD; [Formula: see text]), the AR control (CGAR; [Formula: see text]), and the experimental group (EG; [Formula: see text]). Both the CGAR and EG completed a 5-session prosthesis training protocol in AR while the CGLD performed simple muscle training. The EG attempted manipulations in AR while undergoing limb loading. The CGAR attempted the same manipulations without loading. All participants performed the same manipulations in physical reality while operating a real prosthesis pre- and post-training. The main outcome measure was the change in the number of manipulations completed during the physical reality assessments (i.e. completion rate). Secondary outcomes included movement kinematics and visuomotor behavior. RESULTS: The EG experienced a greater increase in completion rate post-training than both the CGAR and CGLD. This performance increase was accompanied by a shorter motor learning phase, the EG's performance saturating in less sessions of AR training than the CGAR. CONCLUSION: The results demonstrated that limb loading plays an important role in transferring complex motor skills learned in virtual spaces to their physical reality analogs. While participants who did not receive limb loading were able to receive some functional benefit from AR training, participants who received the loading experienced a greater positive change in motor performance with their performance saturating in fewer training sessions.

Neurophysiology of slip sensation and grip reaction: insights for hand prosthesis control of slippage.

Sensory feedback is pivotal for a proficient dexterity of the hand. By modulating the grip force in function of the quick and not completely predictable change of the load force, grabbed objects are prevented to slip from the hand. Slippage control is an enabling achievement to all manipulation abilities. However, in hand prosthetics, the performance of even the most innovative research solutions proposed so far to control slippage remain distant from the human physiology. Indeed, slippage control involves parallel and compensatory activation of multiple mechanoceptors, spinal and supraspinal reflexes, and higher-order voluntary behavioral adjustments. In this work, we reviewed the literature on physiological correlates of slippage to propose a three-phases model for the slip sensation and reaction. Furthermore, we discuss the main strategies employed so far in the research studies that tried to restore slippage control in amputees. In the light of the proposed three-phase slippage model and from the weaknesses of already implemented solutions, we proposed several physiology-inspired solutions for slippage control to be implemented in the future hand prostheses. Understanding the physiological basis of slip detection and perception and implementing them in novel hand feedback system would make prosthesis manipulation more efficient and would boost its perceived naturalness, fostering the sense of agency for the hand movements.

An Adaptive Multi-Modal Control Strategy to Attenuate the Limb Position Effect in Myoelectric Pattern Recognition.

Over the last few decades, pattern recognition algorithms have shown promising results in the field of upper limb prostheses myoelectric control and are now gradually being incorporated in commercial devices. A widely used approach is based on a classifier which assigns a specific input value to a selected hand motion. While this method guarantees good performance and robustness within each class, it still shows limitations in adapting to different conditions encountered in real-world applications, such as changes in limb position or external loads. This paper proposes an adaptive method based on a pattern recognition classifier that takes advantage of an augmented dataset-i.e., representing variations in limb position or external loads-to selectively adapt to underrepresented variations. The proposed method was evaluated using a series of target achievement control tests with ten able-bodied volunteers. Results indicated a higher median completion rate >3.33% for the adapted algorithm compared to a classical pattern recognition classifier used as a baseline model. Subject-specific performance showed the potential for improved control after adaptation and a ≤13% completion rate; and in many instances, the adapted points were able to provide new information within classes. These preliminary results show the potential of the proposed method and encourage further development.

Adapting myoelectric control in real-time using a virtual environment.

BACKGROUND: Pattern recognition technology allows for more intuitive control of myoelectric prostheses. However, the need to collect electromyographic data to initially train the pattern recognition system, and to re-train it during prosthesis use, adds complexity that can make using such a system difficult. Although experienced clinicians may be able to guide users to ensure successful data collection methods, they may not always be available when a user needs to (re)train their device. METHODS: Here we present an engaging and interactive virtual reality environment for optimal training of a myoelectric controller. Using this tool, we evaluated the importance of training a classifier actively (i.e., moving the residual limb during data collection) compared to passively (i.e., maintaining the limb in a single, neutral orientation), and whether computational adaptation through serious gaming can improve performance. RESULTS: We found that actively trained classifiers performed significantly better than passively trained classifiers for non-amputees (P < 0.05). Furthermore, collecting data passively with minimal instruction, paired with computational adaptation in a virtual environment, significantly improved real-time performance of myoelectric controllers. CONCLUSION: These results further support previous work which suggested active movements during data collection can improve pattern recognition systems. Furthermore, adaptation within a virtual guided serious game environment can improve real-time performance of myoelectric controllers.

Directional Forgetting for Stable Co-Adaptation in Myoelectric Control.

Conventional myoelectric controllers provide a mapping between electromyographic signals and prosthetic functions. However, due to a number of instabilities continuously challenging this process, an initial mapping may require an extended calibration phase with long periods of user-training in order to ensure satisfactory performance. Recently, studies on co-adaptation have highlighted the benefits of concurrent user learning and machine adaptation where systems can cope with deficiencies in the initial model by learning from newly acquired data. However, the success remains highly dependent on careful weighting of these new data. In this study, we proposed a function driven directional forgetting approach to the recursive least-squares algorithm as opposed to the classic exponential forgetting scheme. By only discounting past information in the same direction of the new data, local corrections to the mapping would induce less distortion to other regions. To validate the approach, subjects performed a set of real-time myoelectric tasks over a range of forgetting factors. Results show that directional forgetting with a forgetting factor of 0.995 outperformed exponential forgetting as well as unassisted user learning. Moreover, myoelectric control remained stable after adaptation with directional forgetting over a range of forgetting factors. These results indicate that a directional approach to discounting past training data can improve performance and alleviate sensitivities to parameter selection in recursive adaptation algorithms.

An Insulated Flexible Sensor for Stable Electromyography Detection: Applicationto Prosthesis Control.

Electromyography (EMG), the measurement of electrical muscle activity, is used in a variety of applications, including myoelectric upper-limb prostheses, which help amputees to regain independence and a higher quality of life. The state-of-the-art sensors in prostheses have a conductive connection to the skin and are therefore sensitive to sweat and require preparation of the skin. They are applied with some pressure to ensure a conductive connection, which may result in pressure marks and can be problematic for patients with circulatory disorders, who constitute a major group of amputees. Due to their insulating layer between skin and sensor area, capacitive sensors are insensitive to the skin condition, they require neither conductive connection to the skin nor electrolytic paste or skin preparation. Here, we describe a highly stable, low-power capacitive EMG measurement set-up that is suitable for real-world application. Various flexible multi-layer sensor set-ups made of copper and insulating foils, flex print and textiles were compared. These flexible sensor set-ups adapt to the anatomy of the human forearm, therefore they provide high wearing comfort and ensure stability against motion artifacts. The influence of the materials used in the sensor set-up on the magnitude of the coupled signal was demonstrated based on both theoretical analysis and measurement.The amplifier circuit was optimized for high signal quality, low power consumption and mobile application. Different shielding and guarding concepts were compared, leading to high SNR.

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. TRIAL REGISTRATION: The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Prosthetic Rehabilitation for a Patient With Purpura Fulminans Undergoing Quadruple Amputation: A Case Report.

Purpura fulminans (PF) is a rare and life-threatening syndrome characterized by cutaneous purpura resulting from disseminated intravascular coagulation (DIC) and intravascular thrombosis. PF typically develops as a severe complication of infections and is associated with high mortality rates. Effective treatment involves early recognition, aggressive resuscitation, appropriate antibiotic therapy, and the correction of coagulation abnormalities. Nevertheless, despite effective treatment, patients often ultimately require amputation of the affected limbs. This case report details the rehabilitation process of a patient with PF who underwent quadruple amputation. The patient, a 48-year-old male, underwent quadruple amputation due to PF. After intensive care, he was admitted to a convalescent rehabilitation ward for prosthetic rehabilitation. The rehabilitation process combined physical and occupational therapy to facilitate independent living through the use of upper and lower limb prostheses and assistive devices. The patient presented with ulcerative lesions on the anterior surfaces of both knee joints upon admission. During treatment, he developed osteomyelitis of the right patella, which required intravenous antibiotics and limited rehabilitation to bed-based exercises. Following the administration of intravenous therapy, the prosthetist proceeded with the fabrication of lower limb prostheses. Subsequently, the patient was able to commence standing and gait training, and by the time of discharge, he was able to walk without a cane. Upper limb prostheses enabled independence in activities of daily living (ADLs) such as eating, dressing, and toileting. He was also able to perform cooking-related activities that are part of the instrumental activities of daily living (IADLs). This case highlights the importance and achievable outcomes of rehabilitation for patients with PF who have undergone quadruple amputation. A multidisciplinary approach utilizing both upper and lower limb prostheses, as well as assistive devices, enabled significant functional recovery.

Grasping Embodiment: Haptic Feedback for Artificial Limbs.

Upper-limb prostheses are subject to high rates of abandonment. Prosthesis abandonment is related to a reduced sense of embodiment, the sense of self-location, agency, and ownership that humans feel in relation to their bodies and body parts. If a prosthesis does not evoke a sense of embodiment, users are less likely to view them as useful and integrated with their bodies. Currently, visual feedback is the only option for most prosthesis users to account for their augmented activities. However, for activities of daily living, such as grasping actions, haptic feedback is critically important and may improve sense of embodiment. Therefore, we are investigating how converting natural haptic feedback from the prosthetic fingertips into vibrotactile feedback administered to another location on the body may allow participants to experience haptic feedback and if and how this experience affects embodiment. While we found no differences between our experimental manipulations of feedback type, we found evidence that embodiment was not negatively impacted when switching from natural feedback to proximal vibrotactile feedback. Proximal vibrotactile feedback should be further studied and considered when designing prostheses.

Evoking Apparent Moving Sensation in the Hand via Transcutaneous Electrical Nerve Stimulation.

The restoration of sensory feedback in amputees plays a fundamental role in the prosthesis control and in the communication on the afferent channel between hand and brain. The literature shows that transcutaneous electrical nerve stimulation (TENS) can be a promising non-invasive technique to elicit sensory feedback in amputees, especially in the lower limb through the phenomenon of apparent moving sensation (AMS). It consists of delivering a sensation that moves along a specific part of the body. This study proposes to use TENS to elicit tactile sensations and adopt AMS to reproduce moving sensations on the hand, such as those related to an object moving in the hand or slipping upward or downward. To this purpose, the developed experimental protocol consists of two phases: (i) the mapping of the evoked sensations and (ii) the generation of the AMS. In the latter phase, the pulse amplitude variation (PAV), the pulse width variation (PWV), and the interstimulus delay modulation (ISDM) methods were compared. For the comparative analysis, the Wilcoxon-Mann-Whitney test with Bonferroni correction (P < 0.016) was carried out on the success rate and on the ranking of methods expressed by the subjects. Results from the mapping protocol show that the delivered sensations were mostly described by the subjects as almost natural and superficial tingling. Results from the AMS protocol show that, for each movement direction, the success rate of ISDM method is higher than that of PWV and PAV and significantly higher than that of PAV for the ulnar-median direction. It recreates an AMS in the hand that effectively allows discriminating the type of sensation and distinguishing the movement direction. Moreover, ISDM was ranked by the subjects as the favorite method for recreating a well-defined and comfortable moving sensation only in the median-ulnar direction. For the ranking results, there was not a statistically significant difference among the methods. The experiments confirmed the good potential of recreating an AMS in the hand through TENS. This encourages to push forward this study on amputees and integrate it in the closed-loop control of a prosthetic system, in order to enable full control of grasp stability and prevent the objects from slippage.

Towards resolving the co-existing impacts of multiple dynamic factors on the performance of EMG-pattern recognition based prostheses.

BACKGROUND AND OBJECTIVE: Mobility of subject (MoS) and muscle contraction force variation (MCFV) have been shown to individually degrade the performance of multiple degrees of freedom electromyogram (EMG) pattern recognition (PR) based prostheses control systems. Though these factors (MoS-MCFV) co-exist simultaneously in the practical use of the prosthesis, their combined impact on PR-based system has rarely been studied especially in the context of amputees who are the target users of the device. METHODS: To address this problem, this study systematically investigated the co-existing impact of MoS-MCFV on the performance of PR-based movement intent classifier, using EMG recordings acquired from eight participants who performed multiple classes of targeted limb movements across static and non-static scenarios with three distinct muscle contraction force levels. Then, a robust feature extraction method that is invariant to the combined effect of MoS-MCFV, namely, invariant time-domain descriptor (invTDD), was proposed to optimally characterize the multi-class EMG signal patterns in the presence of both factors. RESULTS: Experimental results consistently showed that the proposed invTDD method could significantly mitigate the co-existing impact of MoS-MCFV on PR-based movement-intent classifier with error reduction in the range of 7.50%~17.97% (p<0.05), compared to the commonly applied methods. Further evaluation using 2-dimentional principal component analysis (PCA) technique, revealed that the proposed invTDD method has obvious class-separability in the PCA feature space, with a significantly lower standard error (0.91%) compared to the existing methods. CONCLUSION: This study offers compelling insight on how to develop accurately robust multiple degrees of freedom control scheme for multifunctional prostheses that would be clinically viable. Also, the study may spur positive advancement in other application areas of medical robotics that adopts myoelectric control schemes such as the electric wheelchair and human-computer-interaction systems.

Patient perspectives on benefits and risks of implantable interfaces for upper limb prostheses: a national survey.

Objective: Patient perspectives on benefits and risks of implantable interfaces for prostheses are needed. Methods: A telephone survey was administered to 808 Veterans. Multivariate logistic regression identified factors associated with willingness to consider surgery to restore touch and better movement control. Risk and benefit ratings were compared. Results: 41.8% of unilateral and 40.6% of bilateral amputees were willing to consider surgery for touch; 49.0% were willing to consider surgery for control. Persons 65-75 years and >75 were 0.42 (p= 0.0009) and 0.19 (p< 0.0001) as likely as those 18-45 to consider surgery for touch, those with better mental health (MH) were 0.47 (p= 0.0005) as likely as those with worse, and those with infection etiology were 1.7 (p= 0.03) as likely as those without. Persons 65-75 and >75 were 0.28 and 0.12 as likely as those 18-45 to consider surgery for control (p's<0.0001). Myoelectric users were 2.16 (p= 0.006) as likely as body-powered users and persons with better MH were 0.61 (p= 0.03) as likely as those with worse to consider surgery for control. Long-term risks were most unacceptable. Durability, comfort, and improved functional abilities were most important. Conclusions: There is substantial interest in prosthetic interfaces to gain a sense of touch and greater movement control.

Design and Assessment of Control Maps for Multi-Channel sEMG-Driven Prostheses and Supernumerary Limbs.

Proportional and simultaneous control algorithms are considered as one of the most effective ways of mapping electromyographic signals to an artificial device. However, the applicability of these methods is limited by the high number of electromyographic features that they require to operate-typically twice as many the actuators to be controlled. Indeed, extracting many independent electromyographic signals is challenging for a number of reasons-ranging from technological to anatomical. On the contrary, the number of actively moving parts in classic prostheses or extra-limbs is often high. This paper faces this issue, by proposing and experimentally assessing a set of algorithms which are capable of proportionally and simultaneously control as many actuators as there are independent electromyographic signals available. Two sets of solutions are considered. The first uses as input electromyographic signals only, while the second adds postural measurements to the sources of information. At first, all the proposed algorithms are experimentally tested in terms of precision, efficiency, and usability on twelve able-bodied subjects, in a virtual environment. A state-of-the-art controller using twice the amount of electromyographic signals as input is adopted as benchmark. We then performed qualitative tests, where the maps are used to control a prototype of upper limb prosthesis. The device is composed of a robotic hand and a wrist implementing active prono-supination movement. Eight able-bodied subjects participated to this second round of testings. Finally, the proposed strategies were tested in exploratory experiments involving two subjects with limb loss. Results coming from the evaluations in virtual and realistic settings show encouraging results and suggest the effectiveness of the proposed approach.

Identifying the benefits and risks of emerging integration methods for upper limb prosthetic devices in the United States: an environmental scan.

Objectives: Novel connective and control methods between an upper limb prosthetic device and end-user have large potential rewards and risks, making economic evaluation difficult. Methods: We conducted an environmental scan to assess user perspectives on advancements in upper limb prosthetic device integration. The environmental scan consisted of a PubMed literature search, grey literature review, formation of a community advisory board (CAB) and key informant interviews. The CAB guided the study and was comprised of adults with personal or professional experiences with upper limb prostheses. Results: The environmental scan highlights 4 main types of integration in upper-limb prostheses: osseointegration, targeted muscle reinnervation, cortical integration and peripheral nerve/muscle integration. The PubMed literature search resulted in the greatest number of matches for 'targeted muscle reinnervation upper limb' (N = 65) and 'upper limb osseointegration' (N = 54). The grey literature review found targeted muscle reinnervation and peripheral nerve/muscle integration to be most discussed amongst end-users and regulators. Of these four methods, greater device control versus invasiveness of implant is a clear benefit-risk tradeoff. Conclusion: This scan highlights a gap in user-centered research in upper limb prosthetic devices. Future directions include the development of a stated-preference instrument incorporating these methods of integration. Expert opinion: Upper limb loss greatly impacts one's productivity and quality of life. Despite a variety of prosthetic device options, high user dissatisfaction and rejection rates persist. Using community-based participatory research practices, we engaged end-users and identified the importance of option value. Many individuals said they would forego a present-day option to maintain the opportunity to adopt a device in the future, a point not addressed in the literature. Of the four emerging integration methods identified, targeted muscle reinnervation and peripheral nerve/muscle integration are highly promising, yet a better understanding of end-user preferences for these methods is still needed.

Identifying and prioritizing concerns associated with prosthetic devices for use in a benefit-risk assessment: a mixed-methods approach.

OBJECTIVE: We identified and prioritized concerns reported by stakeholders associated with novel upper-limb prostheses. METHODS: An evidence review and key-informant engagement, identified 62 concerns with upper-limb prostheses with implantable components. We selected 16 concerns for inclusion in a best-worst scaling (BWS) prioritization survey. Focus groups and BWS were used to engage stakeholders at a public meeting on prostheses. In 16 BWS choice tasks, attendees selected the most and least influential concern when choosing an upper-limb prosthesis. Aggregate data were analyzed using choice frequencies and conditional logit analysis. Latent class analysis examined heterogeneity in priorities. Estimates were adjusted to importance ratios which indicate how influential each concern is in the decision making process. RESULTS: Forty-seven (47) stakeholders from diverse backgrounds completed the BWS survey (response rate 51%). On aggregate, the most influential concern was reliability of the device (importance ratio: 13%), and least influential was the concern of an outdated device (importance ratio: 1%). Latent class analysis identified two classes with approximately 50% of participants each. The first class was most influenced by effectiveness of the device. The second class was most influenced by minimizing risks. CONCLUSION: In this pilot, we identified heterogeneity in how participants prioritize concerns for upper-limb prostheses.

Ipsilateral Scapular Cutaneous Anchor System: An alternative for the harness in body-powered upper-limb prostheses.

BACKGROUND: Body-powered prosthesis users frequently complain about the poor cosmesis and comfort of the traditional shoulder harness. The Ipsilateral Scapular Cutaneous Anchor System offers an alternative, but it remains unclear to what extent it affects the perception and control of cable operation forces compared to the traditional shoulder harness. OBJECTIVE: To compare cable force perception and control with the figure-of-nine harness versus the Ipsilateral Scapular Cutaneous Anchor System and to investigate force perception and control at different force levels. STUDY DESIGN: Experimental trial. METHODS: Ten male able-bodied subjects completed a cable force reproduction task at four force levels in the range of 10-40 N using the figure-of-nine harness and the Anchor System. Perception and control of cable operating forces were quantified by the force reproduction error and the force variability. RESULTS: In terms of force reproduction error and force variability, the subjects did not behave differently when using the two systems. The smallest force reproduction error and force variability were found at the smallest target force level of 10 N. CONCLUSION: The Anchor System performs no differently than the traditional figure-of-nine harness in terms of force perception and control, making it a viable alternative. Furthermore, users perceive and control low operation forces better than high forces. Clinical relevance The Ipsilateral Scapular Cutaneous Anchor System offers an alternative for the traditional harness in terms of cable operation force perception and control and should therefore be considered for clinical use. Low cable operation forces increase the perception and control abilities of users.

Causes of Performance Degradation in Non-invasive Electromyographic Pattern Recognition in Upper Limb Prostheses.

Surface Electromyography (EMG)-based pattern recognition methods have been investigated over the past years as a means of controlling upper limb prostheses. Despite the very good reported performance of myoelectric controlled prosthetic hands in lab conditions, real-time performance in everyday life conditions is not as robust and reliable, explaining the limited clinical use of pattern recognition control. The main reason behind the instability of myoelectric pattern recognition control is that EMG signals are non-stationary in real-life environments and present a lot of variability over time and across subjects, hence affecting the system's performance. This can be the result of one or many combined changes, such as muscle fatigue, electrode displacement, difference in arm posture, user adaptation on the device over time and inter-subject singularity. In this paper an extensive literature review is performed to present the causes of the drift of EMG signals, ways of detecting them and possible techniques to counteract for their effects in the application of upper limb prostheses. The suggested techniques are organized in a table that can be used to recognize possible problems in the clinical application of EMG-based pattern recognition methods for upper limb prosthesis applications and state-of-the-art methods to deal with such problems.

Resolving the adverse impact of mobility on myoelectric pattern recognition in upper-limb multifunctional prostheses.

Electromyogram pattern recognition (EMG-PR) based control for upper-limb prostheses conventionally focuses on the classification of signals acquired in a controlled laboratory setting. In such a setting, relatively stable and high performances are often reported because subjects could consistently perform muscle contractions corresponding to a targeted limb motion. Meanwhile the clinical implementation of EMG-PR method is characterized by degradations in stability and classification performances due to the disparities between the constrained laboratory setting and clinical use. One of such disparities is the mobility of subject that would cause changes in the EMG signal patterns when eliciting identical limb motions in mobile scenarios. In this study, the effect of mobility on the performance of EMG-PR motion classifier was firstly investigated based on myoelectric and accelerometer signals acquired from six upper-limb amputees across four scenarios. Secondly, three methods were proposed to mitigate such effect on the EMG-PR motion classifier. From the obtained results, an average classification error (CE) of 9.50% (intra-scenario) was achieved when data from the same scenarios were used to train and test the EMG-PR classifier, while the CE increased to 18.48% (inter-scenario) when trained and tested with dataset from different scenarios. This implies that mobility would significantly lead to about 8.98% increase of classification error (p < 0.05). By applying the proposed methods, the degradation in classification performance was significantly reduced from 8.98% to 1.86% (Dual-stage sequential method), 3.17% (Hybrid strategy), and 4.64% (Multi-scenario strategy). Hence, the proposed methods may potentially improve the clinical robustness of the currently available multifunctional prostheses. TRIAL REGISTRATION: The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Cutaneous sensory outcomes from three transhumeral targeted reinnervation cases.

BACKGROUND: Although targeted muscle reinnervation has been shown to be effective in enhancing prosthetic control for upper limb amputees, restored hand sensations have been variable. An understanding of possible sensory feedback channels is crucial in working toward more effective closed-loop prosthetic control. OBJECTIVES: To compare sensory outcomes of different targeted sensory reinnervation approaches. STUDY DESIGN: Case series, cross-sectional, and retrospective. METHODS: Three transhumeral amputees that had undergone different sensory reinnervation approaches were recruited. Skin pressure sensitivity thresholds and anatomic sensory mapping were performed using Semmes-Weinstein monofilaments. The clinical charts of the subjects were reviewed to compare the sensory maps performed during the earlier post-reinnervation period. RESULTS: While the first two subjects achieved return of hand sensations on the stump skin in early follow-up, the maps showed attenuation over time. The last subject developed discrete sensations of all digits in the recipient cutaneous nerve territories away from the reinnervated muscles. CONCLUSIONS: These findings confirm that it is feasible to restore hand sensation after transhumeral targeted reinnervation, but there is a significant intersubject variability. The intrafascicular approach may be particularly effective in restoring digit sensation and deserves further exploration, as do factors affecting stability of the hand maps over time. CLINICAL RELEVANCE: In addition to enabling intuitive motor control of myoelectric prosthesis, targeted reinnervation can also result in sensory restoration of the hand. Documentation of sensory mapping present after reinnervation may assist with exploring future techniques for sensory enhancement, with the goal of working toward closed-loop prosthetic control.

Characteristics of a volume-adjustable compression chamber for transradial prosthetic interface.

In the transradial limb-socket contact interface, the physiological properties and prosthetic operating habits of the residual limb might affect the comfort and functionality of the prosthesis. To enhance the comfort and functionality of the interface, a frame-type socket with four volume-adjustable compression chambers was proposed for the transradial amputation level. The contact pressure of the limb-socket interface was adjusted by the volume changes in the chambers and controlled by a vacuum pump and the corresponding control system. The parameters of the chamber were designed in accordance with the biomechanics of the forearm soft tissue. The chamber with a negative stiffness characteristic was theoretically compared with the chamber with a positive stiffness characteristic. The results showed that the former had a superior performance to the latter in safety and pump performance requirements. A physical model of the transradial frame-type prosthetic interface was also manufactured with four negative stiffness chambers. The experimental results showed that this new prosthetic interface achieved more fitting time and better performance in comfort and functionality than the fixed frame-type socket. This new prosthetic interface with volume-adjustable compression chambers might be an alternative choice for transradial amputees.