Deep Learning–Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach

The reduced computational complexity enables real-time monitoring. Our approach demonstrates substantial improvements in classification results compared to traditional deep learning methods.

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Publication Details

Journal
Brain and Behavior
Published
2024-12-31
DOI
https://doi.org/10.1002/brb3.70206
Citations
11
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
2.03
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article

Deep Learning–Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach

Khosro Rezaee, Sara Abbasi
11 citations
Brain and Behavior
Muscle activation and electromyography studies
2.03
article

Deep Learning–Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach

Khosro Rezaee, Sara Abbasi
article en
11 citations

Abstract

The reduced computational complexity enables real-time monitoring. Our approach demonstrates substantial improvements in classification results compared to traditional deep learning methods.

Brain and BehaviorVol. 15(1)
Islamic Azad University, Mashhad (IR), Mofid University (IR)
Openalex Percentile: Top 13%
Muscle activation and electromyography studies
2.03
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