19 research outputs found

    Transfer of mode switching performance:from training to upper-limb prosthesis use

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    BACKGROUND: Current myoelectric prostheses are multi-articulated and offer multiple modes. Switching between modes is often done through pre-defined myosignals, so-called triggers, of which the training hardly is studied. We evaluated if switching skills trained without using a prosthesis transfer to actual prosthesis use and whether the available feedback during training influences this transfer. Furthermore we examined which clinically relevant performance measures and which myosignal features were adapted during training. METHODS: Two experimental groups and one control group participated in a five day pre-test-post-test design study. Both experimental groups used their myosignals to perform a task. One group performed a serious game without seeing their myosignals, the second group was presented their myosignal on a screen. The control group played the serious game using the touchpad of the laptop. Each training session lasted 15 min. The pre- and post-test were identical for all groups and consisted of performing a task with an actual prosthesis, where switches had to be produced to change grip mode to relocate clothespins. Both clinically relevant performance measures and myosignal features were analysed. RESULTS: 10 participants trained using the serious game, 10 participants trained with the visual myosignal and 8 the control task. All participants were unimpaired. Both experimental groups showed significant transfer of skill from training to prosthesis use, the control group did not. The degree of transfer did not differ between the two training groups. Clinically relevant measure 'accuracy' and feature of the myosignals 'variation in phasing' changed during training. CONCLUSIONS: Training switching skills appeared to be successful. The skills trained in the game transferred to performance in a functional task. Learning switching skills is independent of the type of feedback used during training. Outcome measures hardly changed during training and further research is needed to explain this. It should be noted that five training sessions did not result in a level of performance needed for actual prosthesis use. Trial registration The study was approved by the local ethics committee (ECB 2014.02.28_1) and was included in the Dutch trial registry (NTR5876)

    Performance among different types of myocontrolled tasks is not related

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    Studies on myocontrolled assistive technology (AT), such as myoelectric prostheses, as well as rehabilitation practice using myoelectric controlled interfaces, commonly assume the existence of a general myocontrol skill. This is the skill to control myosignals in such a way that they are employable in multiple tasks. If this skill exists, training any myocontrolled task using a certain set of muscles would improve the use of myocontrolled AT when the AT is controlled using these muscles. We examined whether a general myocontrol skill exists in myocontrolled tasks with and without a prosthesis. Unimpaired, right-handed adults used the sEMG of wrist flexors and extensors to perform several tasks in two experiments. In Experiment 1, twelve participants trained a myoelectric prosthesis-simulator task and a myocontrolled serious game for five consecutive days. Performance was compared between tasks and over the course of the training period. In Experiment 2, thirty-one participants performed five myocontrolled tasks consisting of two serious games, two prosthesis-simulator tasks and one digital signal matching task. All tasks were based on tasks currently used in clinical practice or research settings. Kendall rank correlation coefficients were computed to analyze correlations between the performance on different tasks. In Experiment 1 performance on the tasks showed no correlation for multiple outcome measures. Rankings within tasks did not change over the training period. In Experiment 2 performance did not correlate between any of the tasks. Since performance between different tasks did not correlate, results suggest that a general myocontrol skill does not exist and that each myocontrolled task requires a specific skill. Generalization of those findings to amputees using AT should be done with caution since in both experiments unimpaired participants were included. Moreover, training duration in Experiment 2 was short. Our findings indicate that training and assessment methods for myocontrolled AT use should focus on tasks frequently performed in daily life by the individual using the AT instead of merely focusing on training myosignals

    The Anatomy of Action Systems:Task Differentiation When Learning an EMG Controlled Game

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    This study aims to determine to what extent the task for an action system in its initial development relies on functional and anatomical components. Fifty-two able-bodied participants were randomly assigned to one of three experimental groups or to a control group. As a pre- and post-test all groups performed a computer game with the same goal and using the same musculature. One experimental group also trained to perform this test, while the other two experimental groups learned to perform a game that differed either in its goal or in the musculature used. The observed change in accuracy indicated that retaining the goal of the task or the musculature used equally increased transfer performance relative to controls. Conversely, changing either the goal or the musculature equally decreased transfer relative to training the test. These results suggest that in the initial development of an action system, the task to which the system pertains is not specified solely by either the goal of the task or the anatomical structures involved. It is suggested that functional specificity and anatomical dependence might equally be outcomes of continuously differentiating activity

    Looking beyond proportional control: The relevance of mode switching in learning to operate multi-articulating myoelectric upper-limb prostheses

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    Objective: Operating a multi-articulating myoelectric prosthetic hand requires both proportional control of surface electromyography (sEMG) signals and accurately producing triggers to switch between grip types. Proportional control, used for hand opening/closing, has been studied extensively but the grip-switching control far less so. Can switching be trained and if so, how early on can improvement be seen? And is the ability to produce precise switches related to proficiency in proportional control? We examined individual learning differences, monitored improvements in switching control, and assessed whether skilful proportional control predicts proficient switching. Methods: Twenty-three unimpaired participants fitted with sEMG electrodes on the wrist flexors/extensors performed two 10-minute tasks: an adaptive virtual catching task (proportional control) and an sEMG- feedback-based switching task, with multiple performance measures being recorded and compared. Results: Most outcome measures revealed large individual differences, with 47–87% of the participants showing improvement in switching and 14% deteriorating. As hypothesized, no correlations were found between mode-switching and proportional-control skills. Conclusion: Learning to generate accurate grip-switching control proved difficult and might not be feasible for all individuals with upper-limb amputations. Unaffected participants showing proficient proportional control were not automatically good at producing well-tuned mode switches. Significance: In rehabilitation, clients with good proportional control are often offered a multi-articulating hand prosthesis. Since we found no clear associations between the proficiency in proportional movements and mode switches, this rationale may warrant reconsideration. Rather, when selecting the most optimal prosthesis, an individual's skills in both control types should be examined separately

    Analyzing sentiment in a large set of web data while accounting for negation

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    As virtual utterances of opinions or sentiment are becoming increasingly abundant on the Web, automated ways of analyzing sentiment in such data are becoming more and more urgent. In this paper, we provide a classification scheme for existing approaches to document sentiment analysis. As the role of negations in sentiment analysis has been explored only to a limited extent, we additionally investigate the impact of taking into account negation when analyzing sentiment. To this end, we utilize a basic sentiment analysis framework – consisting of a wordbank creation part and a document scoring part – taking into account negation. Our experimental results show that by accounting for negation, precision on human ratings increases with 1.17%. On a subset of selected documents containing negated words, precision increases with 2.23%
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