Upper-extremity Prosthesis Research Articles

Grasp Posture Variability Leads to Greater Ipsilateral Sensorimotor Beta Activation During Simulated Prosthesis Use

Motor behaviour using upper-extremity prostheses of different levels is greatly variable, leading to challenges interpreting ideal rehabilitation strategies. Elucidating the underlying neural control mechanisms driving variability benefits our understanding of adaptation after limb loss. In this follow-up study, non-amputated participants completed simple and complex reach-to-grasp motor tasks using a body-powered transradial or partial-hand prosthesis simulator. We hypothesised that under complex task constraints, individuals employing variable grasp postures will show greater sensorimotor beta activation compared to individuals relying on uniform grasping, and activation will occur later in variable compared to uniform graspers. In the simple task, partial-hand variable and transradial users showed increased neural activation from the early to late phase of the reach, predominantly in the hemisphere ipsilateral to device use. In the complex task, only partial-hand variable graspers showed a significant increase in neural activation of the sensorimotor cortex from the early to the late phase of the reach. These results suggest that grasp variability may be a crucial component in the mechanism of neural adaptation to prosthesis use, and may be mediated by device level and task complexity, with implications for rehabilitation after amputation.

A scoping review on upper extremity prostheses: Satisfaction, barriers, and their implications in resource-limited countries.

The rates of prosthetic abandonment are not extensively understood especially in resource-limited countries. A scoping review was conducted to examine the literature on the satisfaction with and barriers to using specifically upper limb prostheses. A systematic search of the literature identified 425 studies. After reviewing the articles using predetermined inclusion and exclusion criteria, 7 cross-sectional studies were included in the final review. Barriers to the use of upper limb prostheses include the characteristics of the prosthesis (type, comfort, weight, functionality, price, and availability) and individual patient factors (recent prosthetic user, level of amputation, congenital and accidental limb loss, pain, and duration between amputation and prosthetic fitting). Considering tailored prosthetic design and funding may result in improved prosthetic adherence.

Sex and gender differences in upper extremity prosthesis rejection: A review of literature.

Prosthesis rejection is a significant barrier to rehabilitation of persons with upper limb difference. Many individual factors can affect device rejection, including a person's sex or gender. The objective of this narrative review was to explore the reported differences between the sexes and genders in upper limb prosthesis rejection. This review considered peer-reviewed, published research studies in which the study population were adults (aged 18 and older) who had unilateral or bilateral limb difference (any level) of any etiology with current, past, or no history of prosthetic device usage. Using identified keywords, index terms, and a peer-reviewed search filter, the literature was searched in MEDLINE, Embase, and PsycInfo. The reasons for rejection, disuse, or abandonment of prosthetic devices were extracted, with the focus on reported differences between sex and genders. After searching, 29 articles were selected for full-text review and 15 were included. Only 5 of 15 articles examined differences between the sexes. Women tend to reject upper extremity prostheses more than men both before and after being fit with a device; device characteristics, such as weight and cosmesis, do not appear to be appropriately designed for women; and there may not be adequate consideration of the goals for women with limb difference(s). There is inadequate reporting of sex and gender in the literature on prosthesis rejection; future studies should report and explore these factors to determine whether the needs of the full population with limb loss are being met.

Individuals with moderate to severe hand impairments may struggle to use EMG control for assistive devices.

Neurological trauma, such as stroke, traumatic brain injury (TBI), spinal cord injury, and cerebral palsy can cause mild to severe upper limb impairments. Hand impairment makes it difficult for individuals to complete activities of daily living, especially bimanual tasks. A robotic hand orthosis or hand exoskeleton can be used to restore partial function of an intact but impaired hand. It is common for upper extremity prostheses and orthoses to use electromyography (EMG) sensing as a method for the user to control their device. However some individuals with an intact but impaired hand may struggle to use a myoelectrically controlled device due to potentially confounding muscle activity. This study was conducted to evaluate the application of conventional EMG control techniques as a robotic orthosis/exoskeleton user input method for individuals with mild to severe hand impairments. Nine impaired subjects and ten healthy subjects were asked to perform repeated contractions of muscles in their forearm and then onset analysis and feature classification were used to determine the accuracy of the employed EMG techniques. The average accuracy for contraction identification across employed EMG techniques was 95.4% ± 4.9 for the healthy subjects and 73.9% ± 13.1 for the impaired subjects with a range of 47.0% ± 19.1 - 91.6% ± 8.5. These preliminary results suggest that the conventional EMG control technologies employed in this paper may be difficult for some impaired individuals to use due to their unreliable muscle control.

Home intervention for children and adolescents with unilateral trans-radial and partial carpal reduction deficiencies.

Current training interventions assessing pediatric functional motor skills do not account for children and adolescents with upper limb reductions who utilize a prosthesis. Prosthesis rejection showed that 1 out of 5 prosthesis users will reject their prosthesis due to lack of durability, lack of function, not meeting the participant’s needs, perceived lack of need, and medical restrictions indicating that prosthetic users believed they were more functional without the device. It was hypothesized that an 8-week Home Intervention program will result in significant improvements in gross manual dexterity, bimanual coordination, and the functional activities performed during the program. It was also hypothesized that the novel Prosthesis Measurement of Independent Function (PMIF) score will reflect the Home Intervention performance improvements. Five pediatric participants (ages 5–19 years) with congenital upper limb reductions were fitted with a 3D printed upper extremity prosthesis for their affected limb. Participants then completed the 8-week Home Intervention which included Training activities completed 2×/week for 8 weeks and Non-Training activities completed only at week 1 and week 8. Participant’s times were recorded along with each participant receiving a PMIF score ranging from 0 = unable to complete activity, to 7 = complete independence with activity completion. Results showed a decrease in overall averaged activity times amongst all activities. For all activities performed, individual averaged time decreased with the exception of Ball Play which increased over the 8-week intervention period. There was significant interaction for Home Intervention performance with F = 2.904 (p = 0.003). All participants increased their PMIF scores to 7 (complete independence) at the end of the 8 week intervention period. Decreases in time averages and increases in PMIF scores indicate that learning and functional use of the prostheses have occurred amongst the pediatric participants.

DETERMINANTS OF QUALITY OF LIFE AMONG UPPER LIMB PROSTHESIS USERS PAKISTAN: A MULTICENTER STUDY

Objective: To determine the quality of life among users of upper extremity prosthesis.
 Study Design: Cross sectional study.
 Place and Duration of Study: Day’s Medical Engineering and Artificial Limbs Center Multan and Pakistan Institute of Prosthetic and Orthotic Sciences, Peshawar, Pakistan, from Jul to Dec 2018.
 Methodology: A sample population of 276 users of upper extremity prosthesis was recruited employing convenience sampling including both genders aged 20-50 years. Demographic sheet, 36- Item Short Form Health Survey (SF-36) and Quick Disabilities of the Arm, Shoulder and Hand questionnaire (Quick-DASH) were used to collect data followed by analysis using SPSS-22.
 Results: Mean score on Quick Disabilities of the Arm, Shoulder and Hand questionnaire was 49.2+25.4. The mean scores of 36- Item Short Form Health Survey revealed highest values in the domains of emotional wellbeing (55.8 ± 17.7) and energy/ fatigue (54.0 ± 14.3) while lowest values were noted in the role limitation due to emotional problems (38.9 ± 33.5) and General Health (43.8 ± 19.6) domains.
 Conclusion: The study findings concluded that the overall quality of life of upper limb prosthetic user was low along with significant association of demographic features with SF-36 and Quick DASH.

Upper extremity prosthesis 3D bio-pneumatic self-adjusting clamping to non-homogeneous surfaces under the principle of communicating vessel

There are several models that emulate the mechanical behavior of biological tissues. Its automation, new materials and manufacturing techniques will enable its use in the near future. This research is based on the use of compressed air in pneumatic muscles that actuate the phalanges. The research is important because it proposes a system that adapts to the needs and economic accessibility or people with limited resources. The problem to solve is that it meets certain standards such as: stable grip and pressure and that it adapts to irregularly shaped objects with more natural movements. The principle of communicating vessels and the force exerted by a fluid on the walls of the container that is used. Consequently, the fluid exerts pressure in all directions. The prosthesis with the design of the Flexy Hand 2 is manufactured by inserting pneumatic muscles to each of the fingers connecting them by means of nylon ropes that are attached to the homemade pneumatic muscles connected to a common manifold, regulating the pressure by means of a valve and a degree of freedom. As a result of the above, it can be concluded that the prototype worked favorably.

115 The Impact of Burn Injury on Upper Extremity Prosthesis Users

Abstract Introduction Burns with upper extremity (UE) amputation present a unique rehabilitation challenge. The purpose of this study of UE amputees who are active prosthesis users was to compare outcomes for those with and without burns. Methods This is part of a larger nationwide study of U.S. military members and veterans with UE amputations. In-person data were collected at 5 sites. An therapist measured passive and active range of motion (PROM, AROM); administered the Quick Disability of the Arm, Shoulder, and Hand; Community Reintegration of Injured Service Members-Computer Adaptive-Test; Trinity Amputation and Prosthetic Experience Scale; health-related quality of life (VR-12); Activities Measure for Upper Extremity Amputees; Southampton Assessment Procedure; 9-Hole Peg Test; and Jebsen-Taylor Hand Function Test (JTHF); and recorded residual and phantom pain; timing of prosthesis receipt; and current prosthesis use. The IRB approved this study. Results Data were collected on 126 individuals with UE amputation, of whom 105 had data on etiology and were included. Of these, 13 (12.4%) had burns (B) vs non-burn (NB). The majority were unilateral amputees (69% B, 90% NB). Most were transradial (TR) amputees (B 84.6%, NB 66.3%) as opposed to transhumeral (TH). A minority received their prosthetics within the first 3 months post-amputation (11.1% B, 28.8% NB) (p=0.15). Average age was 57.6 (SD 15.6) years for NB and 53.0 (20.6) years for B. Mean time since amputation was 22.5 (18.0) years for NB and 25.2 (17.3) years for B. The following non-significant differences in outcomes between B and NB were observed. Thirty-nine percent of B were employed full-time vs 18.9% of NB (p=0.15). The primary prosthesis was, for NB, a body-powered prosthesis (66.7%); for B, myoelectric (50%) or body-powered (50%). For unilateral UE amputees, there were no differences between B and NB on performance testing for dexterity and functional tasks or in self-reported disability, quality of life or prevalence or intensity of pain. B trended towards more moderate to severe PROM deficits with shoulder forward flexion (TH B 50%, TH NB 23.1% [p=0.444]; TR B 20%, TR NB 5.6% [p=0.197]) and shoulder abduction (TH B 50%, TH NB 26.9% [p=0.497]; TR B 30%, TR NB 16.4% [p=0.376]). Also, TR amputees with burns trended towards more PROM deficits with elbow flexion (B 20%, NB 6.9% [p=0.212]) and elbow extension (B 20%, NB 8.6% [p=0.272]). AROM deficits also trended greater in B. Conclusions We did not observe differences in physical function, pain levels, or quality of life between those with and without burns. Further studies with larger samples are needed, to include analysis of burn location, burn size, hospital length of stay, and rehabilitation care.

Learning regularized representations of categorically labelled surface EMG enables simultaneous and proportional myoelectric control

BackgroundProcessing the surface electromyogram (sEMG) to decode movement intent is a promising approach for natural control of upper extremity prostheses. To this end, this paper introduces and evaluates a new framework which allows for simultaneous and proportional myoelectric control over multiple degrees of freedom (DoFs) in real-time. The framework uses multitask neural networks and domain-informed regularization in order to automatically find nonlinear mappings from the forearm sEMG envelope to multivariate and continuous encodings of concurrent hand- and wrist kinematics, despite only requiring categorical movement instruction stimuli signals for calibration.MethodsForearm sEMG with 8 channels was collected from healthy human subjects (N = 20) and used to calibrate two myoelectric control interfaces, each with two output DoFs. The interfaces were built from (I) the proposed framework, termed Myoelectric Representation Learning (MRL), and, to allow for comparisons, from (II) a standard pattern recognition framework based on Linear Discriminant Analysis (LDA). The online performances of both interfaces were assessed with a Fitts’s law type test generating 5 quantitative performance metrics. The temporal stabilities of the interfaces were evaluated by conducting identical tests without recalibration 7 days after the initial experiment session.ResultsMetric-wise two-way repeated measures ANOVA with factors method (MRL vs LDA) and session (day 1 vs day 7) revealed a significant (p<0.05) advantage for MRL over LDA in 5 out of 5 performance metrics, with metric-wise effect sizes (Cohen’s d) separating MRL from LDA ranging from left|dright|=0.62 to left|dright|=1.13. No significant effect on any metric was detected for neither session nor interaction between method and session, indicating that none of the methods deteriorated significantly in control efficacy during one week of intermission.ConclusionsThe results suggest that MRL is able to successfully generate stable mappings from EMG to kinematics, thereby enabling myoelectric control with real-time performance superior to that of the current commercial standard for pattern recognition (as represented by LDA). It is thus postulated that the presented MRL approach can be of practical utility for muscle-computer interfaces.

Clinical evaluation of the revolutionizing prosthetics modular prosthetic limb system for upper extremity amputees

Individuals with upper extremity (UE) amputation abandon prostheses due to challenges with significant device weight—particularly among myoelectric prostheses—and limited device dexterity, durability, and reliability among both myoelectric and body-powered prostheses. The Modular Prosthetic Limb (MPL) system couples an advanced UE prosthesis with a pattern recognition paradigm for intuitive, non-invasive prosthetic control. Pattern recognition accuracy and functional assessment—Box & Blocks (BB), Jebsen-Taylor Hand Function Test (JHFT), and Assessment of Capacity for Myoelectric Control (ACMC)—scores comprised the main outcomes. 10 participants were included in analyses, including seven individuals with traumatic amputation, two individuals with congenital limb absence, and one with amputation secondary to malignancy. The average (SD) time since limb loss, excluding congenital participants, was 85.9 (59.5) months. Participants controlled an average of eight motion classes compared to three with their conventional prostheses. All participants made continuous improvements in motion classifier accuracy, pathway completion efficiency, and MPL manipulation. BB and JHFT improvements were not statistically significant. ACMC performance improved for all participants, with mean (SD) scores of 162.6 (105.3), 213.4 (196.2), and 383.2 (154.3), p = 0.02 between the baseline, midpoint, and exit assessments, respectively. Feedback included lengthening the training period to further improve motion classifier accuracy and MPL control. The MPL has potential to restore functionality to individuals with acquired or congenital UE loss.

Upper extremity prosthetic selection influences loading of transhumeral osseointegrated systems.

Percutaneous osseointegrated (OI) implants are increasingly viable as an alternative to socket suspension of prosthetic limbs. Upper extremity prostheses have also become more complex to better replicate hand and arm function and attempt to recreate pre-amputation functional levels. With more functionality comes heavier devices that put more stress on the bone-implant interface, which could be an issue for implant stability. This study quantified transhumeral loading at defined amputation levels using four simulated prosthetic limb-types: (1) body powered hook, (2) myoelectric hook, (3) myoelectric hand, and (4) advanced prosthetic limb. Computational models were constructed to replicate the weight distribution of each prosthesis type, then applied to motion capture data collected during Advanced Activities of Daily Living (AADLs). For activities that did not include a handheld weight, the body powered prosthesis bending moments were 13–33% (range of means for each activity across amputation levels) of the intact arm moments (reference 100%), torsional moments were 12–15%, and axial pullout forces were 30–40% of the intact case (p≤0.001). The myoelectric hook and hand bending moments were 60–99%, torsional moments were 44–97%, and axial pullout forces were 62–101% of the intact case. The advanced prosthesis bending moments were 177–201%, torsional moments were 164–326%, and axial pullout forces were 133–185% of the intact case (p≤0.001). The addition of a handheld weight for briefcase carry and jug lift activities reduced the overall impact of the prosthetic model itself, where the body powered forces and moments were much closer to those of the intact model, and more complex prostheses further increased forces and moments beyond the intact arm levels. These results reveal a ranked order in loading magnitude according to complexity of the prosthetic device, and highlight the importance of considering the patient’s desired terminal device when planning post-operative percutaneous OI rehabilitation and training.

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What's Important: It's a Privilege.

Quantitative Eye Gaze and Movement Differences in Visuomotor Adaptations to Varying Task Demands Among Upper-Extremity Prosthesis Users

New treatments for upper-limb amputation aim to improve movement quality and reduce visual attention to the prosthesis. However, evaluation is limited by a lack of understanding of the essential features of human-prosthesis behavior and by an absence of consistent task protocols. To evaluate whether task selection is a factor in visuomotor adaptations by prosthesis users to accomplish 2 tasks easily performed by individuals with normal arm function. This cross-sectional study was conducted in a single research center at the University of Alberta, Edmonton, Alberta, Canada. Upper-extremity prosthesis users were recruited from January 1, 2016, through December 31, 2016, and individuals with normal arm function were recruited from October 1, 2015, through November 30, 2015. Eight prosthesis users and 16 participants with normal arm function were asked to perform 2 goal-directed tasks with synchronized motion capture and eye tracking. Data analysis was performed from December 3, 2018, to April 15, 2019. Movement time, eye fixation, and range of motion of the upper body during 2 object transfer tasks (cup and box) were the main outcomes. A convenience sample comprised 8 male prosthesis users with acquired amputation (mean [range] age, 45 [30-64] years), along with 16 participants with normal arm function (8 [50%] of whom were men; mean [range] age, 26 [18-43] years; mean [range] height, 172.3 [158.0-186.0] cm; all right handed). Prosthesis users spent a disproportionately prolonged mean (SD) time in grasp and release phases when handling the cups (grasp: 2.0 [2.3] seconds vs 0.9 [0.8] seconds; P < .001; release: 1.1 [0.6] seconds vs 0.7 [0.4] seconds; P < .001). Prosthesis users also had increased mean (SD) visual fixations on the hand for the cup compared with the box task during reach (10.2% [12.1%] vs 2.2% [2.8%]) and transport (37.1% [9.7%] vs 22.3% [7.6%]). Fixations on the hand for both tasks were significantly greater for prosthesis users compared with normative values. Prosthesis users had significantly more trunk flexion and extension for the box task compared with the cup task (mean [SD] trunk range of motion, 32.1 [10.7] degrees vs 21.2 [3.7] degrees; P = .01), with all trunk motions greater than normative values. The box task required greater shoulder movements compared with the cup task for prosthesis users (mean [SD] flexion and extension; 51.3 [12.6] degrees vs 41.0 [9.4] degrees, P = .01; abduction and adduction: 40.5 [7.2] degrees vs 32.3 [5.1] degrees, P = .02; rotation: 50.6 [15.7] degrees vs 35.5 [10.0] degrees, P = .02). However, other than shoulder abduction and adduction for the box task, these values were less than those seen for participants with normal arm function. This study suggests that prosthesis users have an inherently different way of adapting to varying task demands, therefore suggesting that task selection is crucial in evaluating visuomotor performance. The cup task required greater compensatory visual fixations and prolonged grasp and release movements, and the box task required specific kinematic compensatory strategies as well as increased visual fixation. This is the first study to date to examine visuomotor differences in prosthesis users across varying task demands, and the findings appear to highlight the advantages of quantitative assessment in understanding human-prosthesis interaction.

Control methods for upper extremity prostheses

The paper deals with upper extremity prostheses control methods analysis. We consider prostheses control peculiarities for three main levels of amputation (prostheses for hand and fingers amputation, forearm amputation or forearm disarticulation, shoulder amputation or shoulder disarticulation). It is shown how amputation level is connected with used prosthesis control methods. The most perspective control methods for hand and fingers prostheses are the ones with extended feedback and adaptivity. It is beneficial to use neurointerfaces and muscle synergy phenomenon in control methods for forearm prostheses. Non-invasive and intuitive control methods are considered to be the most effective for shoulder prostheses. In spite of a great variety of modern technological achievements, the question of full recovery for all upper extremity functions remains open. A number of still unsolved problems, concerning the development of upper extremity prostheses control systems, is outlined: organization of extended “human – prosthesis”feedback, an effective control of multiple degrees of freedom, and simultaneous usage of the useful signal sources of different origins.

HOW INFILL PERCENTAGE AFFECTS THE ULTIMATE STRENGTH OF A 3D-PRINTED TRANSTIBIAL SOCKET

INTRODUCTION&#x0D; 3D printing for non‐weight‐bearing upper extremity prostheses is becoming increasingly popular as a method of fabrication.1 Some clinics in North America have begun using 3D printing to fabricate lower extremity diagnostic sockets (Figure 1). The strength requirements for upper extremity prostheses are not as rigorous as the strength requirements for lower extremity prostheses. Therefore, strength testing on 3D-printed lower extremity sockets is one of the first steps that needs to be conducted to ensure patient safety. 3D-printed prosthetic sockets are becoming an alternative option to traditional methods because it is possible to customize different parameters to create a strong structure. Infill percentage is an important parameter to research as this can have an influence on the strength of 3D printed sockets.2 As both prosthetists and healthcare professionals, there is a need to become more involved in the process of designing and testing 3D printed sockets. The purpose of this study is to test how changing the infill percentage affects the ultimate strength of a 3D printed transtibial socket during initial contact.&#x0D; Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32038/24453&#x0D; How to cite: Campbell L, Lau A, Pousett B, Janzen E, Raschke S.U. HOW INFILL PERCENTAGE AFFECTS THE ULTIMATE STRENGTH OF A 3D-PRINTED TRANSTIBIAL SOCKET. CANADIAN PROSTHETICS &amp; ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, POSTER PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32038 &#x0D; Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. &#x0D; http://www.aopanet.org/

USER EXPERIENCES WITH TRADITIONAL AND 3D-PRINTED UPPER EXTREMITY PROSTHESES, DEVELOPMENT OF A COMPREHENSIVE SURVEY INSTRUMENT

INTRODUCTION&#x0D; Additive Manufacturing (AM), colloquial known as 3D-printing, has been deemed capable to revolutionize a great number of industries, including the Health Care industry.1 In the field of upper limb prosthetics, it has been attempted to leverage the potential advantages of AM, such as crowd based design optimization, infrastructure independent fabrication, and economical material use, in the interest of providing low-cost, readily available devices to recipients whose needs were only insufficiently met by traditional approaches of device prescription and fitting. While the popular media has been quick to emphasize the potential – perceived or real – of 3D printed prostheses, clinicians have generally been less euphoric and the base of scientific evidence on questions related to these applications has been small.2 As with most research endeavors in prosthetics and orthotics, recruiting sufficient sample sizes to allow solid conclusions is a perennial challenge also in this sub-field. As a consequence, the effectiveness of the many 3D-printed upper limb devices made by volunteers of the E-nable community (Fig.1) is yet to be determined. Self-reported outcome assessment tools can somewhat mitigate the issue of low sample sizes. However, none have been applied to a wider range of device classes, to allow comparative analyses across those. We describe the development and preliminary testing of an online based survey tool to generate comparison outcome data for a wide variety of upper limb prosthetics devices, including varieties that are 3D-printed by hobbyists.&#x0D; Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32009/24428&#x0D; How to cite: Mankoff J, Savage S, Eckert S, Ngo C, Fiedler G. USER EXPERIENCES WITH TRADITIONAL AND 3D-PRINTED UPPER EXTREMITY PROSTHESES, DEVELOPMENT OF A COMPREHENSIVE SURVEY INSTRUMENT. CANADIAN PROSTHETICS &amp; ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, POSTER PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32009 &#x0D; Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. &#x0D; http://www.aopanet.org/&#x0D;

Classifying Imaginary Hand Movement through Electroencephalograph Signal for Neuro-rehabilitation

Brain-Computer-Interface (BCI) has been widely used in the field of neuro-rehabilitation such as automatic controls based on brain commands to upper and lower extremity prosthesis devices in patients with paralysis. In a post-stroke period, approximately 50 % of stroke survivors have unilateral motor deficits leading to a sustained decline in chronic upper extremity function. Stroke affects patients in their productive and elderly age which is potentially creating new problems in national health development. BCI could be used to aid post-stroke patient recovery, so the motion detection and classification are essential for optimizing the BCI device control. Therefore, this study aims to distinguish several hand functions such as grasping, pinching, and hand lifting from releasing movement by the standard actions performed during post-stroke rehabilitation based on brain signals of a healthy subject obtained from an electroencephalogram (EEG) with a 5 channels electrode. In this study, the EEG signals were decomposed using a Discrete Wavelet Transform (DWT) then filtered by a bandpass filter to generate Mu and Beta waves, which were correlated with imaginary movement. Then, the Mu and Beta waves were calculated using a Common Spatial Pattern (CSP) algorithm as the inputs for Extreme Learning Machine (ELM) to distinguish 2 types of imaginary hand movements (grasping v. releasing, pinching v. releasing, hand lifting v. releasing). The results of these classifications shown that ELM and CSP were useful features in distinguishing 2 types of motion with software/system accuracy average above 95 %. Therefore, this could be useful for optimizing BCI devices in neuro-rehabilitation, moreover by combining it with a Functional Electrical Stimulator (FES) as a self-therapy for post-stroke patients.

Wrist-Powered Partial Hand Prosthesis Using a Continuum Whiffle Tree Mechanism: A Case Study.

Among the advances in upper extremity prostheses in the past decades, only a small portion of the results were obtained for partial hand prostheses, possibly due to the highly diverse partial hand presentations and limited space for component integration. In an attempt to address these challenges, this paper presents the design, construction, installation, and experimental characterization of a wrist-powered partial hand prosthesis developed in Shanghai Jiao Tong University (hereafter referred to as the JTP hand), customized for a specific amputee. The JTP hand possesses: 1) a continuum whiffle tree mechanism to allow adaptive grasping; 2) a force-magnifying partial gear pair to enhance the power of the grip; and 3) a phalange-embedded disengageable ratchet to enable or disable backdrivability. Various grasps and gestures were formed using the JTP hand. The obtained results suggest that the proposed design might be a viable option for patients with transmetacarpal amputation.

Extrapolation of Emerging Technologies and Their Long-Term Implications for Myoelectric versus Body-Powered Prostheses: An Engineering Perspective

ABSTRACT The field of prosthetic rehabilitation is at the cusp of a revolution in upper-limb prosthetic techniques and treatment options. After 50 years of largely incremental developments in the design of both body-powered and myoelectric upper extremity prostheses, new technologies are coming of age that will provide sensory feedback to the user. This, in turn, will promote embodiment of the prosthesis, allowing users to believe the device is a true extension of themselves. This will facilitate the incorporation of the prosthesis into their body image and allow users to finally begin to think of the prosthesis as a true limb replacement rather than as a tool. This review surveys innovations in upper-limb prosthetic rehabilitation from an engineering perspective.

Improved prosthetic hand control with concurrent use of myoelectric and inertial measurements

BackgroundMyoelectric pattern recognition systems can decode movement intention to drive upper-limb prostheses. Despite recent advances in academic research, the commercial adoption of such systems remains low. This limitation is mainly due to the lack of classification robustness and a simultaneous requirement for a large number of electromyogram (EMG) electrodes. We propose to address these two issues by using a multi-modal approach which combines surface electromyography (sEMG) with inertial measurements (IMs) and an appropriate training data collection paradigm. We demonstrate that this can significantly improve classification performance as compared to conventional techniques exclusively based on sEMG signals.MethodsWe collected and analyzed a large dataset comprising recordings with 20 able-bodied and two amputee participants executing 40 movements. Additionally, we conducted a novel real-time prosthetic hand control experiment with 11 able-bodied subjects and an amputee by using a state-of-the-art commercial prosthetic hand. A systematic performance comparison was carried out to investigate the potential benefit of incorporating IMs in prosthetic hand control.ResultsThe inclusion of IM data improved performance significantly, by increasing classification accuracy (CA) in the offline analysis and improving completion rates (CRs) in the real-time experiment. Our findings were consistent across able-bodied and amputee subjects. Integrating the sEMG electrodes and IM sensors within a single sensor package enabled us to achieve high-level performance by using on average 4-6 sensors.ConclusionsThe results from our experiments suggest that IMs can form an excellent complimentary source signal for upper-limb myoelectric prostheses. We trust that multi-modal control solutions have the potential of improving the usability of upper-extremity prostheses in real-life applications.