Enhancing Gait Analysis for Parkinson’s Disease Detection and Severity Staging With a Parallel Conv1D-Efficient Transformer and Bidirectional GRU Hybrid Architecture

Enhancing Gait Analysis for Parkinson’s Disease Detection and Severity Staging With a Parallel Conv1D-Efficient Transformer and Bidirectional GRU Hybrid Architecture

Gait analysis is a critical tool for diagnosing and assessing the severity of Parkinson’s disease (PD). This study introduces a novel parallel hybrid architecture combining Conv1D, Efficient Transformers, and Bidirectional GRU layers to analyze gait data for both PD detection and severity...

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Bibliographic Details
Main Authors: Xiaoli Huan, Hong Zhou, Byungkwan Jung, Long Ma
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Gait analysis
Parkinson’s disease detection
severity staging
Conv1D
efficient transformers
bidirectional GRU
Online Access:https://ieeexplore.ieee.org/document/10892107/
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https://ieeexplore.ieee.org/document/10892107/

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