Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation
Our digital phenotyping approach using passive sensors on smartphones and fitness trackers may help patients with real-world, continuous self-monitoring of common symptoms in their own environment and assist clinicians with better triage of patient needs for timely interventions in MS and potentially other chronic neurological disorders.
Authors
- Prerna Chikersal (ORCID: https://orcid.org/0000-0002-0961-6210)
- Elizabeth Walker (ORCID: https://orcid.org/0000-0002-6294-1098)
- Mayank Goel (ORCID: https://orcid.org/0000-0003-1237-7545)
- Anind K. Dey (ORCID: https://orcid.org/0000-0002-3004-0770)
- Shruthi Venkatesh (ORCID: https://orcid.org/0000-0001-9113-0502)
- Zongqi Xia (ORCID: https://orcid.org/0000-0003-1500-2589)
Institutions
- University of Pittsburgh (US)
- University of Washington (US)
- Carnegie Mellon University (US)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-04-23
- DOI
- https://doi.org/10.2196/70871
- Citations
- 2
- Primary Topic
- Digital Mental Health Interventions
- Type
- article
- Field-Weighted Citation Impact
- 3.09