Wearable technologies for early detection and management of Parkinson’s disease in underserved settings:  A narrative review

Pichayapar Euachongprasit; Sujimon Mungkalarungsi

Authors

Pichayapar Euachongprasit Satit Prasarnmit Demonstration School (Secondary)
Sujimon Mungkalarungsi Independent Researcher

Keywords:

Parkinson’s disease, wearable technology, digital health, remote monitoring, early detection

Abstract

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor symptoms such as tremor, bradykinesia, gait disturbances, and postural instability. Early detection is essential for improving disease management; however, diagnosis is often delayed, particularly in rural and resource-limited settings where access to neurological specialists is limited. Wearable technologies have emerged as promising tools for continuous monitoring of motor symptoms and remote assessment of PD progression.

This review aimed to synthesize current evidence on wearable technologies used for the detection and monitoring of Parkinson’s disease and to evaluate their feasibility for implementation in underserved and resource-limited healthcare settings, including Thailand.

A narrative review supported by a systematic literature search was conducted using PubMed, Scopus, and IEEE Xplore databases for studies published between January 2010 and March 2025. Keywords related to Parkinson’s disease and wearable monitoring technologies were applied using Boolean operators. Following duplicate removal and two-stage screening, 16 studies met the inclusion criteria. Data were extracted on device type, sensor placement, monitored symptoms, clinical validation, and technological characteristics.

The reviewed studies identified multiple wearable technologies, including smartwatches, wrist-worn sensors, finger-worn motion trackers, and shoe-based inertial measurement unit systems. These devices primarily utilized accelerometers and gyroscopes to capture movement-related biomarkers associated with PD symptoms. Several studies demonstrated strong correlations between wearable sensor outputs and clinical assessment tools such as the Unified Parkinson’s Disease Rating Scale (UPDRS). Sensor placement influenced symptom detection, with wrist-based devices effectively monitoring tremor and bradykinesia, while lower-body sensors provided more accurate assessment of gait disturbances and balance abnormalities. Wearable monitoring systems also showed potential to support remote patient monitoring and improve access to neurological assessment in underserved regions.

Wearable technologies represent a promising approach for improving early detection and long-term monitoring of Parkinson’s disease. Their integration into digital health systems may help reduce diagnostic delays, enhance remote monitoring capabilities, and improve healthcare accessibility in underserved populations. However, successful implementation in middle-income healthcare systems such as Thailand will require further real-world validation, improved digital health infrastructure, and clear clinical integration strategies.

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