Research Article
Using Wearable Devices to Mitigate Bias in Patient Reported Outcomes for Aging Populations
@INPROCEEDINGS{10.1007/978-3-031-32029-3_30, author={John Michael Templeton and Christian Poellabauer and Sandra Schneider}, title={Using Wearable Devices to Mitigate Bias in Patient Reported Outcomes for Aging Populations}, proceedings={Wireless Mobile Communication and Healthcare. 11th EAI International Conference, MobiHealth 2022, Virtual Event, November 30 -- December 2, 2022, Proceedings}, proceedings_a={MOBIHEALTH}, year={2023}, month={5}, keywords={Digital Biomarkers Neurocognitive Assessment Wearable Devices Parkinson’s Disease}, doi={10.1007/978-3-031-32029-3_30} }- John Michael Templeton
Christian Poellabauer
Sandra Schneider
Year: 2023
Using Wearable Devices to Mitigate Bias in Patient Reported Outcomes for Aging Populations
MOBIHEALTH
Springer
DOI: 10.1007/978-3-031-32029-3_30
Abstract
Wearable devices are increasingly used in health monitoring due to the provision of objective and longitudinal measures of physiological functions. The purpose of this work was to assess variability of perceived functionality for autonomic function, sleep, and physical activity, compared to objective physiological measures collected via device sensors. Further, this work assessed disparities between healthy aging populations and those with confirmed neurodegenerative conditions (e.g., Parkinson’s Disease (PD)). 30 participants ((n=20)PD;(n=10)control) wore a smart tracker to collect objective features for autonomic function, sleep, and activity. Further, all participants completed daily questionnaires to depict perceived physiologic functionality. While previous studies note the importance of patient reported outcomes (PROs), these may be subject to variability. PROs of the control group were higher than sensor-based values across all functions; where sleep and heart rate yielded statistical significance ((p=0.002);(p=0.012); respectively). Conversely, PROs of populations with PD were significantly lower for sleep quality, heart rate, and activity ((p=0.018);(p=0.009);(p=0.007); respectively) compared to sensor-based values. Finally, significant differences ((p<<0.01)) were present for all functions between groups. Although PROs are commonly used to monitor health, digital health systems should be used to increase reliability and accuracy via the collection of objective sensor-based measures.
