The Fusion of HRV and EMG Signals for Automatic Gender Recognition during Stepping Exercise

Nor Aziyatul Izni Mohd Rosli, Mohd Azizi Abdul Rahman, Malarvili Balakrishnan, Saiful Amri Mazlan, Hairi Zamzuri

Abstract


In this paper, a new gender recognition approach in accordance with the fusion of features extracted from electromyogram (EMG) and heart rate variability (HRV) during stepping activity using a stair stepper device is proposed. The fusion of EMG and HRV is investigated based on feature fusion approach. The feature fusion is carried out by chaining the feature vector extracted from the EMG and HRV signals. A proposed approach comprises of a sequence of processing steps which are preprocessing, feature extraction, feature selection and the feature fusion. The results demonstrated that the fusion approach had enhanced the performance of gender recognition compared to solely on EMG or HRV for the gender recognition.


Keywords


gender recognition; feature fusion; heart rate variability (HRV); electromyography (EMG); Sstepper;

Full Text:

PDF


DOI: http://dx.doi.org/10.12928/telkomnika.v15i2.6113

Article Metrics

Abstract view : 178 times
PDF - 38 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2017 Universitas Ahmad Dahlan

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

View TELKOMNIKA Stats