Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature...

Area of Science:

• Neurology and Digital Health
• Biomedical Engineering and Sensor Technology
• Rehabilitation and Motor Function Assessment

Background:

• Smart sensing technology, including mobile and wearable devices, enables continuous and objective monitoring of motor function outcomes.
• Assessing motor function is crucial for diagnosing, monitoring, and managing various neurological conditions.

Approach:

• A systematic literature review was conducted, searching major databases (Embase, MEDLINE, CENTRAL) and clinical trial registries.
• Included studies focused on wearable and mobile technologies for assessing motor functions in adults, both healthy and mobility-impaired.
• Data extraction and quality assessment were performed by two independent reviewers following predefined criteria.

Key Points:

• 91 publications representing 87 unique studies were analyzed, with Parkinson disease being the most studied condition.
• 42 distinct motion-detecting devices were identified, including healthcare-specific devices, personal electronics (smartphones, watches), and entertainment consoles.
• Sensor-derived motion data demonstrated good accuracy (mean accuracy 0.90) in discriminating between diseased and healthy individuals, with a mean validity coefficient of 0.52 relative to clinical measures.

Conclusions:

• Sensor-derived motion data show potential for classifying and quantifying disease status in neurological conditions.
• Current research is largely based on proof-of-concept studies with methodological variations; clinical validation is more common than analytical validation.
• Future research is essential to establish robust digital measurements for predicting, diagnosing, and tracking neurological disease progression.