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A smart and home-based telerehabilitation tool for patients with neuromuscular disorder

  • Soumya Manna
  • , Danny Smith
  • , Tasmina Islam
  • , M. A. Hannan
  • , B. Azhar

    Research output: Contribution to conferencePaper

    3 Citations (Scopus)

    Abstract

    More than fourteen million people suffer from neuromuscular diseases, including strokes, spinal cord injuries, Parkinson's disease, etc. To return to normal life sooner, a rigorous rehabilitation process is needed. In hospitals, physiotherapists and neurological experts prescribe specific neurorehabilitation exercises. In most cases, patients need to schedule an appointment to receive treatment in a hospital or to have physiotherapists visit them at home. The number of neuromuscular patients has increased, resulting in longer hospital waiting times. In particular, during COVID-19, patients were not allowed to visit hospitals or have physiotherapists visit them due to government restrictions. Online guides for personalised and custom rehabilitation therapy for joint spasticity and stiffness are also not available. This paper reports the development of an IoT-based prototype system that monitors and records joint movements using sensory footwear (consisting of FSR and IMU sensors) and Kinect sensors. In addition, a prototype web portal is also being developed to record performance data during exercises at home and interact with clinicians remotely. A pilot study has been conducted with six healthy individuals and test results show that there is a strong correlation between Kinect data and FSR data in terms of coordination between joint movements.
    Original languageEnglish
    DOIs
    Publication statusPublished - 7 Dec 2022
    Event7th IEEE-EMBS Conference on Biomedical Engineering and Sciences -
    Duration: 7 Dec 2022 → …

    Conference

    Conference7th IEEE-EMBS Conference on Biomedical Engineering and Sciences
    Period7/12/22 → …

    Keywords

    • Correlation coefficient
    • Kinect sensor
    • Neuromuscular patient
    • Telerehabilitation
    • Wearable sensors

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