Accuracy of smartphone video for contactless measurement of hand tremor frequency

Background Computer vision can measure movement from video without the time and access limitations of hospital accelerometry / electromyography, or the requirement to hold or strap a smartphone accelerometer.
Objective To compare computer vision measurement of hand tremor frequency from smartphone video with a gold standard measure, accelerometer.
Methods 37 smartphone videos of hands at rest and in posture, were recorded from 15 participants with tremor diagnoses (9 Parkinson’s, 5 Essential Tremor, 1 Functional Tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier Transform and Bland-Altman analysis were applied. Tremor amplitude was scored by two clinicians.
Results Bland-Altman analysis of dominant tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement -0.38 Hz to +0.35Hz. In 36 out of 37 videos (97%) there was <0.5 Hz difference between computer vision and accelerometer measurement. There was no significant correlation between the level of agreement and tremor amplitude.
Conclusion The study suggests a potential new, contactless ‘point and press’ measure of tremor frequency within standard clinical settings or telemedicine.