Advancements in wearable sensor technology for enhanced diagnosis and management of Parkinson’s disease
Year: 2025
Type: article
Abstract: Parkinson’s disease (PD) is a progressive neurological disorder that gradually impairs bodily movements, making early diagnosis critical for slowing symptom progression and improving patients’ quality of life. As initial symptoms can be subtle, modern wearable sensor technologies play a vital role in monitoring patient movement and behavior. This review explores the applications of wearable sensors in diagnosing and managing Parkinson’s disease, drawing from 35 relevant studies published between 2015 and 2024. Findings indicate that 60%–80% of early-stage PD patients exhibit both motor and non-motor symptoms that can be effectively detected using motion sensors and electrophysiological methods, achieving approximately 90% accuracy in monitoring movement patterns. The incorporation of the Internet of Things (IoT) and machine learning has significantly enhanced the performance of these devices. Overall, wearable sensors are recognized as effective tools for early diagnosis and ongoing management of Parkinson’s disease, with the potential to improve patients’ quality of life and facilitate treatment processes. Future advancements should focus on developing smarter sensors and utilizing advanced algorithms for data analysis to maximize their clinical utility.
Source: Wearable Technology
DOI: 10.54517/wt3212
Authors: Hajar Danesh, Hamidreza Shirzadfar, Atefeh Abedi
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408310171