Universiti Teknologi Malaysia Institutional Repository

Improved gender recognition during stepping activity for rehab application using the combinatorial fusion approach of EMG and HRV

Rosli, N. A. I. M. and Rahman, M. A. A. and Balakrishnan, M. and Komeda, T. and Mazlan, S. A. and Zamzuri, H. (2017) Improved gender recognition during stepping activity for rehab application using the combinatorial fusion approach of EMG and HRV. Applied Sciences (Switzerland), 7 (4). ISSN 2076-3417

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Abstract

Gender recognition is trivial for a physiotherapist, but it is considered a challenge for computers. The electromyography (EMG) and heart rate variability (HRV) were utilized in this work for gender recognition during exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC) function in a combinatorial fusion approach (CFA) (Hsu et al.) was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB), decision tree (J48), k-nearest neighbor (KNN) and support vector machine (SVM). Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient and effective for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Barani's work (90.34%), Nazarloo's work (92.50%), and other classifiers.

Item Type:Article
Uncontrolled Keywords:Data fusion, Electromyography (EMG), Feature fusion, Feature selection, Gender recognition, Heart Rate Variability (HRV), Sensor fusion, Signal processing, Stepper
Subjects:T Technology > T Technology (General)
Divisions:Malaysia-Japan International Institute of Technology
ID Code:75345
Deposited By: Widya Wahid
Deposited On:22 Mar 2018 11:03
Last Modified:22 Mar 2018 11:03

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