Improved Gender Recognition during Stepping Activity for Rehab Application Using the Combinatorial Fusion Approach of EMG and HRV

Improved Gender Recognition during Stepping Activity for Rehab Application Using the Combinatorial Fusion Approach of EMG and HRV

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 s...

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Bibliographic Details
Main Authors: Nor Aziyatul Izni Mohd Rosli, Mohd Azizi Abdul Rahman, Malarvili Balakrishnan, Takashi Komeda, Saiful Amri Mazlan, Hairi Zamzuri
Format: Article
Language:English
Published: MDPI AG 2017-03-01
Series:Applied Sciences
Subjects:
signal processing
feature selection
feature fusion
data fusion
gender recognition
sensor fusion
Heart Rate Variability (HRV), Electromyography (EMG)
Stepper
Online Access:http://www.mdpi.com/2076-3417/7/4/348

Internet

http://www.mdpi.com/2076-3417/7/4/348

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