Application of context-dependent interpretation of biosignals recognition to control a bionic multifunctional hand prosthesis

IF 5.3 2区 医学 Q1 ENGINEERING, BIOMEDICAL
Pawel Trajdos, Marek Kurzynski
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引用次数: 0

Abstract

The paper presents an original method for controlling a surface-electromyography-driven (sEMG) prosthesis. A context-dependent recognition system is proposed in which the same class of sEMG signals may have a different interpretation, depending on the context. This allowed the repertoire of performed movements to be increased. The proposed structure of the context-dependent recognition system includes unambiguously defined decision sequences covering the overall action of the prosthesis, i.e. the so-called boxes. Because the boxes are mutually isolated environments, each box has its own interpretation of the recognition result, as well as a separate local-recognition-task-focused classifier.

Due to the freedom to assign contextual meanings to classes of biosignals, the construction procedure of the classifier can be optimised in terms of the local classification quality in a given box or the classification quality of the entire system. In the paper, two optimisation problems are formulated, differing in the adopted constraints on optimisation variables, with the methods of solving the problems based on an exhaustive search and an evolutionary algorithm, being developed.

Experimental studies were conducted using signals from 1 able-bodied person with simulation of amputation and 10 volunteers with transradial amputations. The study compared the classical recognition system and the context-dependent system for various classifier models. An unusual testing strategy was adopted in the research, taking into account the specificity of the considered recognition task, with two original quality measures resulting from this scheme then being applied. The results obtained confirm the hypothesis that the application of the context-dependent classifier led to an improvement in classification quality.

应用生物信号识别的上下文解释来控制仿生多功能假手
本文介绍了一种控制表面肌电图(sEMG)假肢的独创方法。在该系统中,同一类 sEMG 信号可根据上下文的不同而有不同的解释。这样就可以增加所做动作的范围。所提议的上下文相关识别系统结构包括明确定义的决策序列,涵盖假肢的整体动作,即所谓的 "框"。由于箱体是相互隔离的环境,因此每个箱体都有自己对识别结果的解释,以及一个单独的以本地识别任务为重点的分类器。由于可以自由地为生物信号类别赋予上下文含义,因此分类器的构建过程可以根据给定箱体的本地分类质量或整个系统的分类质量进行优化。本文提出了两个优化问题,不同的是对优化变量采用了不同的约束条件,并开发了基于穷举搜索和进化算法的解决问题的方法。研究比较了各种分类器模型的经典识别系统和上下文相关系统。考虑到所考虑的识别任务的特殊性,研究中采用了一种不同寻常的测试策略,并应用了由该方案产生的两种原始质量测量方法。所获得的结果证实了这一假设,即应用与上下文相关的分类器可提高分类质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
16.50
自引率
6.20%
发文量
77
审稿时长
38 days
期刊介绍: Biocybernetics and Biomedical Engineering is a quarterly journal, founded in 1981, devoted to publishing the results of original, innovative and creative research investigations in the field of Biocybernetics and biomedical engineering, which bridges mathematical, physical, chemical and engineering methods and technology to analyse physiological processes in living organisms as well as to develop methods, devices and systems used in biology and medicine, mainly in medical diagnosis, monitoring systems and therapy. The Journal''s mission is to advance scientific discovery into new or improved standards of care, and promotion a wide-ranging exchange between science and its application to humans.
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