Contrast of multi-resolution analysis approach to transhumeral phantom motion decoding

Ejay Nsugbe; Oluwarotimi William Samuel; Mojisola Grace Asogbon; Guanglin Li

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Contrast of multi-resolution analysis approach to transhumeral phantom motion decoding

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In signal processing,multiresolution decomposition techniques allow for the separation of an acquired signal into sub levels,where the optimal level within the signal minimises redundancy,uncertainties,and contains the information required for the characterisation of the sensed phenomena.In the area of physiological signal processing for prosthesis control,scenarios where a signal decomposition analysis are required:the wavelet decomposition(WD)has been seen to be the favoured time-frequency approach for the decomposition of non-stationary signals.From a research perspective,the WD in certain cases has allowed for a more accurate motion intent decoding process following feature extraction and classification.Despite this,there is yet to be a widespread adaptation of the WD in a practical setting due to perceived computational complexity.Here,for neuro-muscular(electromyography)and brainwave(electroencephalography)signals acquired from a transhumeral amputee,a computationally efficient time domain signal decom-position method based on a series of heuristics was applied to process the acquired signals before feature extraction.The results showed an improvement in motion intent decoding prowess for the proposed time-domain-based signal decomposition across four different classifiers for both the neuromuscular and brain wave signals when compared to the WD and the raw signal.

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《智能技术学报》 |2021年第3期|P.360-375|共16页
作者
Ejay Nsugbe; Oluwarotimi William Samuel; Mojisola Grace Asogbon; Guanglin Li;
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作者单位

Independent Scholar;

Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences(CAS) Shenzhen Institutes of Advanced Technology Shenzhen China;

Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences(CAS) Shenzhen Institutes of Advanced Technology Shenzhen China;

Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences(CAS) Shenzhen Institutes of Advanced Technology Shenzhen China;

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原文格式 PDF
正文语种 chi
中图分类 TN9;
关键词
motion; approach; analysis;

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Contrast of multi-resolution analysis approach to transhumeral phantom motion decoding

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