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A Two-Stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction

Manli Zhu, Qianhui Men, Edmond S. L. Ho, Howard Leung and Hubert P. H. Shum
Journal of Medical Systems (JMS), 2022

 Impact Factor: 5.3 Top 25% Journal in Health Care Sciences & Services#

A Two-Stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction

Abstract

Musculoskeletal and neurological disorders are the most common causes of walking problems among older people, and they often lead to diminished quality of life. Analyzing walking motion data manually requires trained professionals and the evaluations may not always be objective. To facilitate early diagnosis, recent deep learning-based methods have shown promising results for automated analysis, which can discover patterns that have not been found in traditional machine learning methods. We observe that existing work mostly applies deep learning on individual joint features such as the time series of joint positions. Due to the challenge of discovering inter-joint features such as the distance between feet (i.e. the stride width) from generally smaller-scale medical datasets, these methods usually perform sub-optimally. As a result, we propose a solution that explicitly takes both individual joint features and inter-joint features as input, relieving the system from the need of discovering more complicated features from small data. Due to the distinctive nature of the two types of features, we introduce a two-stream framework, with one stream learning from the time series of joint position and the other from the time series of relative joint displacement. We further develop a mid-layer fusion module to combine the discovered patterns in these two streams for diagnosis, which results in a complementary representation of the data for better prediction performance. We validate our system with a benchmark dataset of 3D skeleton motion that involves 45 patients with musculoskeletal and neurological disorders, and achieve a prediction accuracy of 95.56\%, outperforming state-of-the-art methods.

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BibTeX

@article{zhu22twostream,
 author={Zhu, Manli and Men, Qianhui and Ho, Edmond S. L. and Leung, Howard and Shum, Hubert P. H.},
 journal={Journal of Medical Systems},
 title={A Two-Stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction},
 year={2022},
 volume={46},
 number={11},
 pages={76},
 numpages={12},
 doi={10.1007/s10916-022-01857-5},
 issn={1573-689X},
 publisher={Springer},
}

RIS

TY  - JOUR
AU  - Zhu, Manli
AU  - Men, Qianhui
AU  - Ho, Edmond S. L.
AU  - Leung, Howard
AU  - Shum, Hubert P. H.
T2  - Journal of Medical Systems
TI  - A Two-Stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction
PY  - 2022
VL  - 46
IS  - 11
SP  - 76
EP  - 76
DO  - 10.1007/s10916-022-01857-5
SN  - 1573-689X
PB  - Springer
ER  - 

Plain Text

Manli Zhu, Qianhui Men, Edmond S. L. Ho, Howard Leung and Hubert P. H. Shum, "A Two-Stream Convolutional Network for Musculoskeletal and Neurological Disorders Prediction," Journal of Medical Systems, vol. 46, no. 11, pp. 76, Springer, 2022.

Supporting Grants

Northumbria University

Postgraduate Research Scholarship (Ref: ): £65,000, Principal Investigator ()
Received from Faculty of Engineering and Environment, Northumbria University, UK, 2020-2022
Project Page

Similar Research

Manli Zhu, Qianhui Men, Edmond S. L. Ho, Howard Leung and Hubert P. H. Shum, "Interpreting Deep Learning Based Cerebral Palsy Prediction with Channel Attention", Proceedings of the 2021 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2021
Worasak Rueangsirarak, Jingtian Zhang, Nauman Aslam and Hubert P. H. Shum, "Automatic Musculoskeletal and Neurological Disorder Diagnosis with Relative Joint Displacement from Human Gait", IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), 2018
Haozheng Zhang, Hubert P. H. Shum and Edmond S. L. Ho, "Cerebral Palsy Prediction with Frequency Attention Informed Graph Convolutional Networks", Proceedings of the 2022 International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2022
Haozheng Zhang, Edmond S. L. Ho, Francis Xiatian Zhang and Hubert P. H. Shum, "Pose-Based Tremor Classification for Parkinson’s Disease Diagnosis from Video", Proceedings of the 2022 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022
Kevin D. McCay, Edmond S. L. Ho, Hubert P. H. Shum, Gerhard Fehringer, Claire Marcroft and Nicholas Embleton, "Abnormal Infant Movements Classification with Deep Learning on Pose-Based Features", IEEE Access, 2020
Kevin D. McCay, Pengpeng Hu, Hubert P. H. Shum, Wai Lok Woo, Claire Marcroft, Nicholas D. Embleton, Adrian Munteanu and Edmond S. L. Ho, "A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants", IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), 2022
Haozheng Zhang, Edmond S. L. Ho and Hubert P. H. Shum, "CP-AGCN: Pytorch-Based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy", Software Impacts (SIMPAC), 2022

 

 

Last updated on 17 February 2024
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