Classification of Gait Patterns in Patients with Neurodegenerative Disease Using Adaptive Neuro-Fuzzy Inference System
Joint Authors
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-30
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
A common feature that is typical of the patients with neurodegenerative (ND) disease is the impairment of motor function, which can interrupt the pathway from cerebrum to the muscle and thus cause movement disorders.
For patients with amyotrophic lateral sclerosis disease (ALS), the impairment is caused by the loss of motor neurons.
While for patients with Parkinson’s disease (PD) and Huntington’s disease (HD), it is related to the basal ganglia dysfunction.
Previously studies have demonstrated the usage of gait analysis in characterizing the ND patients for the purpose of disease management.
However, most studies focus on extracting characteristic features that can differentiate ND gait from normal gait.
Few studies have demonstrated the feasibility of modelling the nonlinear gait dynamics in characterizing the ND gait.
Therefore, in this study, a novel approach based on an adaptive neuro-fuzzy inference system (ANFIS) is presented for identification of the gait of patients with ND disease.
The proposed ANFIS model combines neural network adaptive capabilities and the fuzzy logic qualitative approach.
Gait dynamics such as stride intervals, stance intervals, and double support intervals were used as the input variables to the model.
The particle swarm optimization (PSO) algorithm was utilized to learn the parameters of the ANFIS model.
The performance of the system was evaluated in terms of sensitivity, specificity, and accuracy using the leave-one-out cross-validation method.
The competitive classification results on a dataset of 13 ALS patients, 15 PD patients, 20 HD patients, and 16 healthy control subjects indicated the effectiveness of our approach in representing the gait characteristics of ND patients.
American Psychological Association (APA)
Ye, Qiang& Xia, Yi& Yao, Zhiming. 2018. Classification of Gait Patterns in Patients with Neurodegenerative Disease Using Adaptive Neuro-Fuzzy Inference System. Computational and Mathematical Methods in Medicine،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1132280
Modern Language Association (MLA)
Ye, Qiang…[et al.]. Classification of Gait Patterns in Patients with Neurodegenerative Disease Using Adaptive Neuro-Fuzzy Inference System. Computational and Mathematical Methods in Medicine No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1132280
American Medical Association (AMA)
Ye, Qiang& Xia, Yi& Yao, Zhiming. Classification of Gait Patterns in Patients with Neurodegenerative Disease Using Adaptive Neuro-Fuzzy Inference System. Computational and Mathematical Methods in Medicine. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1132280
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132280