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Validation of the Comprehensive Augmented Reality Testing Platform to Quantify Parkinson's Disease Fine Motor
Andrew Bazyk1, Ryan D Kaya1, Colin Waltz2
1Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave., Cleveland, OH 44195, USA.
Journal of Clinical Medicine
|June 13, 2025
Summary
A new custom algorithm (CART-MMC) using augmented reality accurately assesses fine motor skills in people with Parkinson's disease (PwPD). This technology offers precise, data-driven insights for improved diagnosis and monitoring of Parkinson's disease.
Area of Science:
- Biomechanical analysis
- Neuroscience
- Medical technology
Background:
- Objective motor function assessment is crucial for managing Parkinson's disease (PwPD).
- Markerless motion capture (MMC) offers a promising, non-invasive method for biomechanical analysis in clinical settings.
- Current MMC systems require validation for clinical utility in PwPD.
Purpose of the Study:
- To evaluate a commercial MMC system for assessing fine motor function.
- To develop and validate a custom MMC data processing algorithm (CART-MMC).
- To assess CART-MMC's ability to differentiate motor performance between PwPD and healthy controls (HCs).
Main Methods:
- 58 PwPD and 25 HCs performed finger-tapping tasks recorded via an augmented reality headset.
- Fine motor performance was assessed using the headset's native software (Native-MMC) and the custom CART-MMC algorithm.
- Both MMC methods were compared against a gold-standard motion capture system (Traditional-MC) for equivalence and known-group validity.
Main Results:
- CART-MMC demonstrated statistical equivalence (within 5%) to Traditional-MC for key metrics like tap count, frequency, and amplitude.
- Native-MMC showed significant deviation (24%) from Traditional-MC, failing to meet equivalence.
- CART-MMC identified significant differences in motor performance variability between PwPD and HCs.
Conclusions:
- A custom algorithm (CART-MMC) effectively analyzes biomechanical data from augmented reality devices.
- This approach accurately characterizes fine motor performance in people with Parkinson's disease.
- CART-MMC shows potential for objective, data-driven assessment in Parkinson's disease management.
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