Machine Learning Approaches to Predict Scoliosis

Ruixin Liang, Joanne Yip, Kai Tsun Michael To, Yunli Fan

    Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

    1 Citation (Scopus)

    Abstract

    Scoliosis seriously affects the physical and mental health of patients. Therefore, machine learning approaches were used to predict whether the subject was scoliosis patient or not by physical characteristics and electromyography (EMG) ratios. One hundred and six subjects, including 33 healthy subjects and 73 subjects with scoliosis, have been involved in this study. However, only about half of the predictions were correct. This may because of the small dataset, and the relatively weak relationship between the features (age, height, weight, gender, and EMG ratios) and the occurrence of scoliosis. This present work served as an initial step for the application of artificial intelligence in scoliosis prediction. However, it is significant and necessary for a greater effort in this topic.

    Original languageEnglish
    Title of host publicationAdvances in Human Factors and Ergonomics in Healthcare and Medical Devices - Proceedings of the AHFE 2021 Virtual Conference on Human Factors and Ergonomics in Healthcare and Medical Devices, 2021
    EditorsJay Kalra, Nancy J. Lightner, Redha Taiar
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages116-121
    Number of pages6
    ISBN (Print)9783030807436
    DOIs
    Publication statusPublished - 25 Jul 2021
    EventAHFE Conference on Human Factors and Ergonomics in Healthcare and Medical Devices, 2021 - Virtual, Online
    Duration: 25 Jul 202129 Jul 2021

    Publication series

    NameLecture Notes in Networks and Systems
    Volume263
    ISSN (Print)2367-3370
    ISSN (Electronic)2367-3389

    Conference

    ConferenceAHFE Conference on Human Factors and Ergonomics in Healthcare and Medical Devices, 2021
    CityVirtual, Online
    Period25/07/2129/07/21

    Keywords

    • Electromyography
    • Machine learning
    • Scoliosis

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Signal Processing
    • Computer Networks and Communications

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