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A Vision-Based Algorithm for Assessing Head and Hand Tremor: Development and Validation Against IMU Sensors.
Slavka Netukova1, Jan Tesař1, Tereza Hubená1,2
1Department of Biomedical Informatics, Faculty of Biomedical Engineering, Czech Technical University in Prague, 272 01 Kladno, Czech Republic.
This study introduces a new video analysis method for tremor detection, offering a contactless alternative to traditional sensors. The findings suggest video assessment is a viable tool for tremor quantification in clinical and research settings.
Area of Science:
- Neurology
- Biomedical Engineering
- Medical Technology
Background:
- Tremor is a common movement disorder requiring accurate assessment for diagnosis and management.
- Current accelerometry methods necessitate sensor attachment, limiting practicality in certain scenarios.
- Developing non-contact tremor assessment tools is crucial for broader accessibility.
Purpose of the Study:
- To develop and validate a novel algorithm for tremor detection using video recordings.
- To implement this algorithm in open-source software (TremAn3) for public use.
- To evaluate the efficacy of video analysis as a contactless alternative to accelerometry for tremor quantification.
Main Methods:
- Motion data extracted from 2D video of hands and head.
- Spectral analysis to quantify tremor by peak power (PP) and peak power frequency (PPF).
- Comparison with gold-standard inertial measurement units (IMUs) using ICC and MAE.
Main Results:
- Video analysis showed moderate-to-good agreement with IMUs for peak power (ICC: 0.70-0.80).
- Moderate agreement was found for peak power frequency in hands (ICC: 0.60-0.67), but poor for the head (ICC: 0.08).
- The developed algorithm, TremAn3, provides a viable contactless method for tremor assessment.
Conclusions:
- Video-based tremor analysis is a promising, non-contact alternative to traditional accelerometry.
- This method has significant potential for remote patient monitoring (telemedicine) and research.
- Further refinement may improve accuracy for head tremor analysis.
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