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Tracking Recovery: An Up-to-Date Overview of Wearable Sensors in Healthcare Monitoring for Post-Stroke Patients: A Review

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    Abstract

    Stroke is a major global health challenge with high morbidity rate, high risk of recurrence, and increasing incidence. Post-stroke healthcare monitoring involves different physiological functions and is dependent on caregivers, with a high need for regular, long-term, point-of-care monitoring. Recently, many wearable sensors including inertial measurement units, mechanical sensors (example barometric sensors, force sensors, strain sensors, et cetera), and electrodes have been developed to achieve reliable healthcare monitoring for post-stroke patients. The sensors are incorporated in different forms to make it more compact and wearable without altering its measuring abilities. These sensors detect different functions including cardiovascular, respiratory, and neural activities, whereas the majority were focused on body movement. By analyzing the innovative wearable technologies and application scenarios, the merits and limitations of the state-of-the-art sensors are summarized in this review. Artificial intelligence (AI) including edge AI and cloud AI, machine learning and deep learning, hardware optimization, and internet-of-things offer new potentials for overcoming the current challenges in reliable long-term monitoring and standardized data processing towards clinical applications.
    Original languageEnglish
    Pages (from-to)1449-1464
    Number of pages16
    JournalIEEE Sensors Journal
    Volume26
    Issue number2
    Early online date25 Nov 2025
    DOIs
    Publication statusPublished - 15 Jan 2026

    Bibliographical note

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    This document is the author’s post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

    Funding

    Ph.D Scholarship and ODA funding of Coventry University Grant Number: 14320-04

    FundersFunder number
    Coventry University14320-04

      Keywords

      • Monitoring
      • post stroke
      • rehabilitation
      • wearable device
      • wearable sensor

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