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March 15, 2026IEEE Transactions on Biomedical Engineering

Evaluation of Deep Learning-Based Event Detection for Parameter Estimation During Complex Walking in Parkinson's Disease

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Authors

ANAvocet Nagle-ChristensenAAAnthony AndersonMGMichael Gonzalez

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Overview

Evaluation of a deep learning method quantifies complex walking tasks in Parkinson's disease, indicating improved mobility understanding.

Key Points

  • 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.

Cite This Study

Nagle-Christensen et al. (2026) studied this question.

synapsesocial.com/papers/69b64c67b42794e3e660db87https://doi.org/10.1109/tbme.2026.3673610
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