Classification of Gait Patterns in Patients with Neurodegenerative Disease Using Adaptive Neuro-Fuzzy Inference System.

Authors:
Qiang Ye
Qiang Ye
University of Kansas
United States
Yi Xia
Yi Xia
Wuhan University
China
Zhiming Yao
Zhiming Yao
Beijing Hospital
China

Comput Math Methods Med 2018 30;2018:9831252. Epub 2018 Sep 30.

Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China.

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.

Download full-text PDF

Source
https://www.hindawi.com/journals/cmmm/2018/9831252/
Publisher Site
http://dx.doi.org/10.1155/2018/9831252DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6186329PMC
February 2019
25 Reads

Publication Analysis

Top Keywords

patients
10
inference system
8
neuro-fuzzy inference
8
adaptive neuro-fuzzy
8
patients patients
8
neurodegenerative disease
8
gait dynamics
8
gait
8
anfis model
8
studies demonstrated
8
patients neurodegenerative
8
disease
7
proposed anfis
4
focus extracting
4
disease proposed
4
model combines
4
combines neural
4
identification gait
4
gait patients
4
presented identification
4

References

(Supplied by CrossRef)
Article in Archives of Physical Medicine and Rehabilitation
Archives of Physical Medicine and Rehabilitation 1984

Similar Publications