abstract

Implicit Detection of Motor Impairment in Parkinson's Disease from Everyday Smartphone Interactions

Authors:

Hongan WangAuthors Info & Claims

CHI EA '18: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems

Paper No.: LBW043, Pages 1 - 6

https://doi.org/10.1145/3170427.3188502

Published: 20 April 2018 Publication History

Abstract

In this work, we explored the feasibility and accuracy of detecting motor impairment in Parkinson's disease (PD) via implicitly sensing and analyzing users' everyday interactions with their smartphones. Through a 42 subjects study, our approach achieved an overall accuracy of 88.1% (90.0%/86.4% sensitivity/specificity) in discriminating PD subjects from age-matched healthy controls. The performance was comparable to the alternating-finger-tapping (AFT) test, a well-established PD motor test in clinical settings. We believe that the implicit and transparent nature of our approach can enable and inspire rich design opportunities of ubiquitous, objective, and convenient systems for PD diagnosis as well as post-diagnosis monitoring.

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Cited By

Park BKim YPark JChoi HKim SRyu HSeo K(2024)Exploring the Multimodal Integration of VR and MRI Biomarkers for Enhanced Early Detection of Mild Cognitive ImpairmentExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3651108(1-8)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3651108
He TChen JChen Y(2024)Smartphone-Based Detection of Early Parkinson’s Disease With Tapping Records and a Multimodal-Multiscale Ensemble NetworkIEEE Sensors Journal10.1109/JSEN.2024.345209224:20(33207-33216)Online publication date: 15-Oct-2024
https://doi.org/10.1109/JSEN.2024.3452092
Asan OChoudhury A(2021)Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping ReviewJMIR Human Factors10.2196/282368:2(e28236)Online publication date: 18-Jun-2021
https://doi.org/10.2196/28236
Show More Cited By

Index Terms

Implicit Detection of Motor Impairment in Parkinson's Disease from Everyday Smartphone Interactions
1. Human-centered computing

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Published In

cover image ACM Conferences

CHI EA '18: Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems

April 2018

3155 pages

ISBN:9781450356213

DOI:10.1145/3170427

General Chairs:
Regan Mandryk
University of Saskatchewan, Canada
,
Mark Hancock
University of Waterloo, Canada
,
Program Chairs:
Mark Perry
Brunel University London, UK
,
Anna Cox
University College London, UK

Copyright © 2018 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2018

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Funding Sources

CAS Pioneer Hundred Talents Program
CAS Key Research Program of Frontier Sciences
National Key R&D Program of China
NSFC

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CHI '18

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SIGCHI

CHI '18: CHI Conference on Human Factors in Computing Systems

April 21 - 26, 2018

Montreal QC, Canada

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CHI EA '18 Paper Acceptance Rate 1,208 of 3,955 submissions, 31%;

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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Cited By

Park BKim YPark JChoi HKim SRyu HSeo K(2024)Exploring the Multimodal Integration of VR and MRI Biomarkers for Enhanced Early Detection of Mild Cognitive ImpairmentExtended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3651108(1-8)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613905.3651108
He TChen JChen Y(2024)Smartphone-Based Detection of Early Parkinson’s Disease With Tapping Records and a Multimodal-Multiscale Ensemble NetworkIEEE Sensors Journal10.1109/JSEN.2024.345209224:20(33207-33216)Online publication date: 15-Oct-2024
https://doi.org/10.1109/JSEN.2024.3452092
Asan OChoudhury A(2021)Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping ReviewJMIR Human Factors10.2196/282368:2(e28236)Online publication date: 18-Jun-2021
https://doi.org/10.2196/28236
Lepreux SApedo KOliveira K(2021)Vers une conception centrée sur l’utilisateur ayant un profil évolutif: Une étude de cas avec des personnes atteintes de la maladie de ParkinsonAdjunct Proceedings of the 32nd Conference on l'Interaction Homme-Machine10.1145/3451148.3458646(1-6)Online publication date: 13-Apr-2021
https://dl.acm.org/doi/10.1145/3451148.3458646

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