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Matthew Sullivan

dblp:217/9430 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 44% Health and well-being technologies · 44% Ubiquitous computing and smart environments · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies
parkinson's disease
0.312018
Back to Analogue: Self-Reporting for Parkinson's Disease · CHI 2018
Usability and user experience research › evaluation methodology
self-report measures
0.312018
Back to Analogue: Self-Reporting for Parkinson's Disease · CHI 2018

Methods — techniques the papers use, named apart from their topics

prototype testing · 0.3design implications · 0.3
YearPublicationVenuePosition
2018 Back to Analogue: Self-Reporting for Parkinson's Disease
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.
Julio Vega, Samuel Couth, Ellen Poliakoff, Sonja Kotz, Matthew Sullivan, Caroline Jay, Markel Vigo, Simon Harper
CHI5