Digital Technologies for Symptom Monitoring in Parkinson Disease
Research studies have demonstrated that DHT can accurately and reliably monitor both motor and non-motor symptoms of PD, surpassing the limitations of subjective and episodic traditional clinical assessments. Digital measures show promise in predicting PD before clinical diagnosis, differentiating between individuals with and without PD, and detecting subtle symptom changes over time. Portable and non-invasive technologies-such as mobile applications, wearable sensors, and radio wave activity trackers-offer the opportunity to assess symptoms remotely, capturing day-to-day changes and real-world experiences. DHT have the potential to optimize monitoring of PD symptoms in clinical and research settings, which may help advance therapeutic development and tailor treatment interventions. As DHT continue evolving, standardization of the collection methods and selection of clinically relevant digital measures will be crucial for their wide-scale implementation.
Authors
- Natalia Chunga (ORCID: https://orcid.org/0000-0001-8450-7121)
- Venkat N. Reddy
- Jamie L. Adams
- William Barbosa
Institutions
- Louisiana State University in Shreveport (US)
- University of Rochester (US)
- Louisiana State University Health Sciences Center Shreveport (US)
Publication Details
- Journal
- Current Neurology and Neuroscience Reports
- Published
- 2026-03-04
- DOI
- https://doi.org/10.1007/s11910-026-01481-7
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00