The aim is to evaluate a deep learning method for detecting events to better estimate parameters during complex walking in Parkinson's disease.
Developed a deep learning-based system for event detection.
Applied the method to analyze complex walking tasks.
Evaluated performance in home and community settings.
Provided reliable quantification of complex walking tasks.
Enhanced understanding of mobility in diverse environments.
Abstract
The proposed method provides a reliable way to quantify complex walking tasks, allowing for a more complete understanding of mobility in home and community environments.
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Nagle-Christensen et al. (2026) studied this question.