Schalkamp, Ann-Kathrin, Harrison, Neil A., Peall, Kathryn J. ![]() ![]() |
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Abstract
Monitoring of Parkinson’s disease (PD) has seen substantial improvement over recent years as digital sensors enable a passive and continuous collection of information in the home environment. However, the primary focus of this work has been motor symptoms, with little focus on the non-motor aspects of the disease. To address this, we combined longitudinal clinical non-motor assessment data and digital multi-sensor data from the Verily Study Watch for 149 participants from the Parkinson’s Progression Monitoring Initiative (PPMI) cohort with a diagnosis of PD. We show that digitally collected physical activity and sleep measures significantly relate to clinical non-motor assessments of cognitive, autonomic, and daily living impairment. However, the poor predictive performance we observed, highlights the need for better targeted digital outcome measures to enable monitoring of non-motor symptoms.
Item Type: | Article |
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Date Type: | Published Online |
Status: | Published |
Schools: | Medicine |
Additional Information: | License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/, Type: open-access |
Publisher: | Nature Research |
Date of First Compliant Deposit: | 30 May 2024 |
Date of Acceptance: | 8 May 2024 |
Last Modified: | 30 May 2024 11:46 |
URI: | https://orca.cardiff.ac.uk/id/eprint/169280 |
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