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Review of wearable devices and data collection considerations for connected health

    • Ulster University
    • Altnagelvin Area Hospital

    Research output: Contribution to journalReview articlepeer-review

    368 Citations (Scopus)

    Abstract

    Wearable sensor technology has gradually extended its usability into a wide range of well-known applications. Wearable sensors can typically assess and quantify the wearer’s physiology and are commonly employed for human activity detection and quantified self-assessment. Wearable sensors are increasingly utilised to monitor patient health, rapidly assist with disease diagnosis, and help predict and often improve patient outcomes. Clinicians use various self-report questionnaires and well-known tests to report patient symptoms and assess their functional ability. These assessments are time consuming and costly and depend on subjective patient recall. Moreover, measurements may not accurately demonstrate the patient’s functional ability whilst at home. Wearable sensors can be used to detect and quantify specific movements in different applications. The volume of data collected by wearable sensors during long-term assessment of ambulatory movement can become immense in tuple size. This paper discusses current techniques used to track and record various human body movements, as well as techniques used to measure activity and sleep from long-term data collected by wearable technology devices.

    Original languageEnglish
    Article number5589
    JournalSensors
    Volume21
    Issue number16
    DOIs
    Publication statusPublished - 2 Aug 2021

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Deep learning (DL)
    • Digital healthcare
    • Neural network (NN)
    • Quantified self (QS)
    • Wearable technology

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