Objective: This project, funded by the Department of Science and Technology, West Bengal, aims to develop a smartphone-based system for remote screening and monitoring of motor symptoms associated with Parkinson’s disease (PD) without requiring hospital visits.

Background: Parkinson’s disease is a progressive neurological disorder usually diagnosed during brief clinical visits, which may not capture day-to-day symptom variations. Individuals in remote or underserved regions often face limited access to specialists and long travel distances to tertiary care centres. Smartphone technologies with built-in sensors and cameras provide an opportunity to perform remote assessments and collect objective motor data for early screening and monitoring.

Method: A smartphone application with a multilingual interface was developed to record participant details and perform motor assessment tasks. The system uses the phone’s inertial measurement unit (IMU) sensors and camera to capture tremor, gait, and hand movement data. Video recordings are analysed using machine-learning–based landmark detection to track hand and body movements. Data are transmitted to a Unix-based remote server, where automated pipelines trigger Python scripts for module-specific analysis. Users can upload data immediately or store it locally for later upload. After processing, a structured analysis report is automatically generated and shared.

Results: The system includes six assessment modules: (1) reaction time measurement to evaluate response latency; (2) tremor frequency analysis using IMU signals; (3) hand open–close movement evaluation using computer vision; (4) postural sway assessment using frame-by-frame tracking of an augmented reference point; (5) gait analysis using body landmark detection from walking videos; and (6) camera-based tremor analysis using hand landmark tracking and frequency analysis of finger movements. Results are compiled into structured reports supporting objective interpretation of motor performance and monitoring of symptom progression.

Conclusion: This study demonstrates the feasibility of combining smartphone-based sensing with automated server-side analysis for remote screening of motor symptoms associated with Parkinson’s disease. Such systems may support early detection and improved access to neurological assessment in resource-limited settings.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/smartphone-based-multilingual-application-for-remote-screening-and-monitoring-of-motor-symptoms-associated-with-parkinsons-disease/