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Automatic Musculoskeletal and Neurological Disorder Diagnosis with Relative Joint Displacement from Human Gait

Worasak Rueangsirarak, Jingtian Zhang, Nauman Aslam and Hubert P. H. Shum
IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE), 2018

REF 2021 Submitted Output Impact Factor: 4.9 Citation: 19#

Automatic Musculoskeletal and Neurological Disorder Diagnosis with Relative Joint Displacement from Human Gait
# According to Google Scholar 2023"

Abstract

Musculoskeletal and neurological disorders are common devastating companions of ageing, leading to a reduction in quality of life and increased mortality. Gait analysis is a popular method for diagnosing these disorders. However, manually analysing the motion data is a labour-intensive task, and the quality of the results depends on the experience of the doctors. In this paper, we propose an automatic framework for classifying musculoskeletal and neurological disorders among older people based on 3D motion data. We also propose two new features to capture the relationship between joints across frames, known as 3D Relative Joint Displacement (3DRJDP) and 6D Symmetric Relative Joint Displacement (6DSymRJDP), such that relative movement between joints can be analyzed. To optimize the classification performance, we adapt feature selection methods to choose an optimal feature set from the raw feature input. Experimental results show that we achieve a classification accuracy of 84.29% using the proposed relative joint features, outperforming existing features that focus on the movement of individual joints. Considering the limited open motion database for gait analysis focusing on such disorders, we construct a comprehensive, openly accessible 3D full-body motion database from 45 subjects.

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Citations

BibTeX

@article{rueangsirarak18automatic,
 author={Rueangsirarak, Worasak and Zhang, Jingtian and Aslam, Nauman and Shum, Hubert P. H.},
 journal={IEEE Transactions on Neural Systems and Rehabilitation Engineering},
 title={Automatic Musculoskeletal and Neurological Disorder Diagnosis with Relative Joint Displacement from Human Gait},
 year={2018},
 volume={26},
 number={12},
 pages={2387--2396},
 numpages={10},
 doi={10.1109/TNSRE.2018.2880871},
 issn={1534-4320},
 publisher={IEEE},
}

RIS

TY  - JOUR
AU  - Rueangsirarak, Worasak
AU  - Zhang, Jingtian
AU  - Aslam, Nauman
AU  - Shum, Hubert P. H.
T2  - IEEE Transactions on Neural Systems and Rehabilitation Engineering
TI  - Automatic Musculoskeletal and Neurological Disorder Diagnosis with Relative Joint Displacement from Human Gait
PY  - 2018
VL  - 26
IS  - 12
SP  - 2387
EP  - 2396
DO  - 10.1109/TNSRE.2018.2880871
SN  - 1534-4320
PB  - IEEE
ER  - 

Plain Text

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, vol. 26, no. 12, pp. 2387-2396, IEEE, 2018.

Supporting Grants

Erasmus Mundus
Sustainable Green Economies through Learning, Innovation, Networking and Knowledge Exchange (gLink)
Erasmus Mundus Action 2 Programme (Ref: 2014-0861/001-001): €3.03 million, Co-Investigator, Northumbria University Funding Management Leader (PI: Prof. Nauman Aslam)
Received from Erasmus Mundus, 2015-2018
Project Page
Northumbria University

Postgraduate Research Scholarship (Ref: ): £65,000, Principal Investigator ()
Received from Faculty of Engineering and Environment, Northumbria University, UK, 2015-2018
Project Page
The Engineering and Physical Sciences Research Council
Interaction-based Human Motion Analysis
EPSRC First Grant Scheme (Ref: EP/M002632/1): £123,819, Principal Investigator ()
Received from The Engineering and Physical Sciences Research Council, UK, 2014-2016
Project Page

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Last updated on 17 February 2024
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