e-space
Manchester Metropolitan University's Research Repository

    Back to Analogue: Self-Reporting for Parkinson’s Disease.

    Vega, J, Couth, S, Poliakoff, E, Kotz, S, Sullivan, M, Jay, C, Vigo, M and Harper, S (2018) Back to Analogue: Self-Reporting for Parkinson’s Disease. In: CHI Conference on Human Factors in Computing Systems (CHI ’18), 21 April 2018 - 26 April 2018, Montreal, Canada.

    [img]
    Preview

    Available under License In Copyright.

    Download (3MB) | Preview

    Abstract

    We report the process used to create artefacts for self-reporting Parkinson's Disease symptoms. Our premise was that a technology-based approach would provide participants with an effective, flexible, and resilient technique. After testing four prototypes using Bluetooth, NFC, and a microcontroller we accomplished almost full compliance and high acceptance using a paper diary to track day-to-day fluctuations over 49 days. This diary is tailored to each patient's condition, does not require any handwriting, allows for implicit reminders, provides recording flexibility, and its answers can be encoded automatically. We share five design implications for future Parkinson's self-reporting artefacts: reduce participant completion demand, design to offset the effect of tremor on input, enable implicit reminders, design for positive and negative consequences of increased awareness of symptoms, and consider the effects of handwritten notes in compliance, encoding burden, and data quality.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    450Downloads
    6 month trend
    283Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record