The reality of myoelectric prostheses : understanding what makes these devices difficult for some users to control

Users of myoelectric prostheses can often find them difficult to control. This can lead to passive-use of the device or total rejection, which can have detrimental effects on the contralateral limb due to overuse. Current clinically available prostheses are ‘open loop’ systems, and although considerable effort has been focused on developing biofeedback to “close the loop”, there is evidence from laboratory-based studies that other factors, notably improving predictability of response, may be as, if not more, important. Interestingly, despite a large volume of research aimed at improving myoelectric prostheses, it is not currently known which aspect of clinically available systems has the greatest impact on overall functionality and everyday usage. A protocol has therefore been designed to assess EMG skill of the user and predictability of the prosthesis response as significant parts of the control chain, and to relate these to functionality and everyday usage. Here we present the protocol and results from early pilot work. A set of experiments has been developed. Firstly to characterize user skill in generating the required level of EMG signal, as well as the speed with which users are able to make the decision to activate the appropriate muscles. Secondly, to measure unpredictability introduced at the skin-electrode interface, in order to understand the effects of the socket mounted electrode fit under different loads on the variability of time taken for the prosthetic hand to respond. To evaluate prosthesis user functionality, four different outcome measures are assessed. Using a simple upper limb functional task prosthesis users are assessed for (1) success of task completion, (2)task duration, (3) quality of movement, and (4) gaze behavior. To evaluate everyday usage away from the clinic, the symmetricity of their real-world arm use is assessed using activity monitoring. These methods will later be used to assess a prosthesis user cohort, to establish the relative contribution of each control factor to the individual measures of functionality and everyday usage (using multiple regression models). The results will support future researchers, designers and clinicians in concentrating their efforts on the area which will have the greatest impact on improving prosthesis use

Upper limb activity of twenty myoelectric prosthesis users and twenty healthy anatomically intact adults

The upper limb activity of twenty unilateral upper limb myoelectric prosthesis users and twenty anatomically intact adults were recorded over a 7-day period using two wrist worn accelerometers (Actigraph, LLC). This dataset reflects the real-world activities of the participants during their normal day-to-day routines. Participants included students, working adults, and retirees recruited from across the United Kingdom. This is the first published dataset of its kind and offers a potential wealth of knowledge into a poorly understood cohort. The raw unprocessed data files and the activity count data exported from the Actilife software are provided. We also provide a non-wear algorithm developed for the removal of prosthesis non-wear periods and resulting activity count data corresponding to prothesis wear periods. Finally, we have included the transposed activity diaries provided by the participants. Analysis to date has primarily involved assessment of the symmetry of upper limb activity, however, there is potential to undertake additional analysis such as understanding the differences in the way a prosthesis is used compared to an anatomical arm

Evaluating reachable workspace and user control over prehensor aperture for a body-powered prosthesis

Using a shoulder harness and control cable, a person can control the opening and closing of a bodypowered prosthesis prehensor. In many setups the cable does not pass adjacent to the shoulder joint center allowing shoulder flexion on the prosthetic side to be used for prehensor control. However, this makes cable setup a difficult compromise as prosthesis control is dependent on arm posture; too short and the space within which a person can reach may be unduly restricted, too long and the user may not be able to move their shoulder sufficiently to take up the inevitable slack at some postures and hence have no control over prehensor movement. Despite the fundamental importance of reachable workspace to users, to date there have been no studies in prosthetics on this aspect. Here, a methodology is presented to quantify the reduction in the reachable volume due to the harness, and to record the range-of-motion of the prehensor at a series of locations within the reachable workspace. Ten anatomically intact participants were assessed using a body-powered prosthesis simulator. Data was collected using a 3D motion capture system and an electronic goniometer. The harnessed reachable workspace was 38-85% the size of the unharnessed volume with participants struggling to reach across the body and above the head. Across all arm postures assessed, participants were only able to achieve full prehensor range-of-motion in 9%. The methodologies presented could be used to evaluate future designs of both body-powered and myoelectric prostheses

Real-world testing of the Self Grasping Hand, a novel adjustable passive prosthesis : a single group pilot study

(1) Background: This study investigated the feasibility of conducting a two-week “real- world” trial of the Self Grasping Hand (SGH), a novel 3-D printed passive adjustable prosthesis for hand absence; (2) Methods: Single-group pilot study of nine adults with trans-radial limb absence. Five used body-powered split-hooks and four had passive cosmetic hands as their usual prosthesis. Data from activity monitors were used to measure wear time and bilateral activity. At the end of the 2-week trial, function and satisfaction were measured using the Orthotics and Prosthetics Users’ Survey Function Scale (OPUS) and the prosthesis satisfaction sub-scales of the Trinity Amputations and Prosthesis Experience Scale (TAPES). Semi-structured interviews captured consumer feedback and suggestions for improvement; (3) Results: Average SGH wear time over 2 weeks was 17.5h (10% of total prosthesis wear time) for split-hook users and 83.5h (63% of total prosthesis wear time) for cosmetic hand users. Mean satisfaction was 5.2/10, and mean function score was 47.9/100; (4) Two-week real-world consumer testing of the SGH is feasible using the methods described. Future SGH designs need to be more robust with easier grasp lock/unloc

Why does my prosthetic hand not always do what it is told?

There are online videos that appear to show electrically powered prosthetic (artificial) hands to be near-perfect replacements for a missing hand. However, for many users, the reality can be quite different. Prosthetic hands do not always respond as expected, which can be frustrating. A prosthetic hand is controlled by muscle signals in the remaining part of the person’s affected arm, using sensors called electrodes. The electrodes are embedded within the socket, which is the part of the prosthetic arm that connects it to the person’s arm. When they activate their muscles, the hand can open, close, or change its grip. If the socket moves, it can pull the electrodes away from the skin. As a result, the muscle activity signaling the person’s intention cannot be properly detected, and the hand will not work very well. In this article, we explain why socket fit may be the most important part of a prosthetic arm

An evaluation of contralateral hand involvement in the operation of the Delft Self-Grasping Hand, an adjustable passive prosthesis

The Delft Self-Grasping Hand is an adjustable passive prosthesis operated using the concept of tenodesis (where opening and closing of the hand is mechanically linked to the flexion and extension of the wrist). As a purely mechanical device that does not require harnessing, the Self-Grasping Hand offers a promising alternative to current prostheses. However, the contralateral hand is almost always required to operate the mechanism to release a grasp and is sometimes also used to help form the grasp; hence limiting the time it is available for other purposes. In this study we quantified the amount of time the contralateral hand was occupied with operating the Self Grasping Hand, classified as either direct or indirect interaction, and investigated how these periods changed with practice. We studied 10 anatomically intact participants learning to use the Self-Grasping Hand fitted to a prosthesis simulator. The learning process involved 10 repeats of a feasible subset of the tasks in the Southampton Hand Assessment Procedure (SHAP). Video footage was analysed, and the time that the contralateral hand was engaged in grasping or releasing was calculated. Functionality scores increased for all participants, plateauing at an Index of Functionality of 33.5 after 5 SHAP attempts. Contralateral hand involvement reduced significantly from 6.47 (first 3 attempts) to 4.68 seconds (last three attempts), but as a proportion of total task time remained relatively steady (increasing from 29% to 32%). For 9/10 participants most of this time was supporting the initiation of grasps rather than releases. The reliance on direct or indirect interactions between the contralateral hand and the prosthesis varied between participants but appeared to remain relatively unchanged with practice. Future studies should consider evaluating the impact of reliance on the contralateral limb in day-to-day life and development of suitable training methods