A Clinical Applicable Smartwatch Application for Measuring Hyperkinetic Movement Disorder Severity.

Area of Science:

• Neurology
• Biomedical Engineering
• Wearable Technology

Background:

• Quantifying hyperkinetic movement disorders (e.g., tremor, myoclonus) is clinically challenging.
• Existing accelerometers often lack real-time analysis and therapeutic adjustment capabilities.
• Deep brain stimulation (DBS) requires precise, real-time feedback for optimal parameter titration.

Purpose of the Study:

• To develop and validate a smartwatch/smartphone application for real-time analysis of movement disorder severity.
• To enable real-time adjustment of therapies such as DBS based on movement quantification.
• To assess the accuracy and reliability of the developed application compared to existing methods.

Main Methods:

• Integrated acceleration, velocity, and distance calculations within a smartwatch/smartphone application.
• Validated the application against a clinical accelerometer for movement disorder quantification.
• Assessed performance using simulated movement disorders in healthy volunteers and real-time DBS titration in patients.

Main Results:

• The application achieved 96% accuracy in distance measurement, comparable to validated clinical accelerometers (p = 0.76).
• Successfully classified simulated movement disorder severity with 93% accuracy.
• Effectively distinguished between effective and non-effective DBS parameters in two patients with movement disorders.

Conclusions:

• The developed application provides an instantaneous and reliable estimation of movement disorder severity.
• This tool can significantly assist in the real-time titration of therapies like DBS.
• Offers a novel approach for objective, real-time assessment in hyperkinetic movement disorders.