An LDA-Based Approach for Real-Time Simultaneous Classification of Movements Using Surface Electromyography

Chris Wilson Antuvan*, Lorenzo Masia

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    6 Citations (Scopus)

    Abstract

    Myoelectric-based decoding strategies offer significant advantages in the areas of human-machine interactions because they are intuitive and require less cognitive effort from the users. However, a general drawback in using machine learning techniques for classification is that the decoder is limited to predicting only one movement at any instant and hence restricted to performing the motion in a sequential manner, whereas human motor control strategy involves simultaneous actuation of multiple degrees of freedom (DOFs) and is considered to be a natural and efficient way of performing tasks. Simultaneous decoding in the context of myoelectric-based movement control is a challenge that is being addressed recently and is increasingly popular. In this paper, we propose a novel classification strategy capable of decoding both the individual and combined movements, by collecting data from only the individual motions. Additionally, we exploit low-dimensional representation of the myoelectric signals using a supervised decomposition algorithm called linear discriminant analysis, to simplify the complexity of control and reduce computational cost. The performance of the decoding algorithm is tested in an online context for the two DOFs task comprising the hand and wrist movements. Results indicate an overall classification accuracy of 88.02% for both the individual and combined motions.

    Original languageEnglish
    Article number8649712
    Pages (from-to)552-561
    Number of pages10
    JournalIEEE transactions on neural systems and rehabilitation engineering
    Volume27
    Issue number3
    DOIs
    Publication statusPublished - Mar 2019

    Keywords

    • Electromyography
    • linear discriminant analysis
    • real-time myoelectric control
    • simultaneous motion decoding

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