Back to analogue: Self-reporting for Parkinson's Disease

Julio Vega*, Samuel Couth, Ellen Poliakoff, Sonja A. Kotz, Matthew Sullivan, Caroline Jay, Markel Vigo, Simon Harper

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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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.
Original languageEnglish
Title of host publicationCHI 2018
Subtitle of host publicationProceedings of the 2018 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery (ACM)
ISBN (Print)9781450356206, 9781450356213
DOIs
Publication statusPublished - 20 Apr 2018
Event2018 CHI Conference on Human Factors in Computing Systems, CHI 2018 - Palais des Congrès de Montréal, Montreal, Canada
Duration: 21 Apr 201826 Apr 2018
https://chi2018.acm.org/

Conference

Conference2018 CHI Conference on Human Factors in Computing Systems, CHI 2018
Country/TerritoryCanada
CityMontreal
Period21/04/1826/04/18
Internet address

Keywords

  • EMA
  • Paper diary
  • Parkinson's Disease
  • Self-report

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