Parker S. Ruth

This paper develops deep learning models to detect neuromuscular diseases and quantify movement impairment using video-derived biomechanics data from smartphone recordings.

The paper introduces StaBLE, a digital balance assessment tool validated against clinical scales, showing strong correlations and improved detection of fall risk.

This paper introduces Bayesian pulse deconvolution to improve vascular waveform analysis by jointly solving signal filtering, pulse timing detection, and pulse shape extraction, achieving significant error reductions in simulations and real-world data.

Smartphone-video biomechanics (OpenCap) reproduced four timed function tests (r > 0.98) and separated facioscapulohumeral from myotonic dystrophy better than test times (balanced accuracy 82% vs 50%; 129 participants).