Feasibility of facial EMG in gender classification during speech production

Abstract

Gender identification has its unique importance in sports and forensic sciences. However, the social issues are major constraints to identify the gender of a human being. A novel approach for gender classification using facial EMG is presented. The time domain features of facial EMGs are explored towards their robustness in gender identification. A Davies-Bouldin index is calculated to evaluate the features. Anterior belly of digastrics along with Orbicularis Oris Inferior showed the promising classification accuracy of 80% with the reported features. A possible enhancement in accuracy could be possible by a larger dataset.

• Gender identification
• facial EMG
• Davies-Bouldin index

Acknowledgements

The authors highly acknowledge all the participants for co-operation during the study.

Biographical notes

Anoop Kant Godiyal did BTech from Uttarakhand Technical University. Currently he is pursuing MTech in Control System, Department of Electrical and Electronics, Graphic Era University, Dehradun. His areas of interests are biomedical signal processing and biomechanics.

Richa Sharma is currently a Research Scholar (PhD) with the Department of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology, University of Delhi, New Delhi, India. She received her MTech from Department of Electrical Engineering, Deenbandhu Chhotu Ram University of Science and Technology, Murthal (Sonepat), Haryana, India. She received her BE in Biomedical Engineering. Her research area includes biomechanics, rehabilitation, digital signal processing and soft computing.

Deepak Joshi has received his PhD degree from Indian Institute of technology (IIT), Delhi, India. He has worked as a Research Scholar at Centre of Biomedical Engineering, IIT, Delhi, India. He has worked as a Research Engineer at Department of Electrical and Computer Engineering, National University of Singapore (NUS), Singapore. Currently he is working as a faculty in Department of Electrical and Electronics in Graphic Era University. He has contributed more research papers in refereed international journals on prosthetic limbs and many other biomedical researches. His research interests are biomechanics and rehabilitation, biomedical instrumentation, clinical sciences, and signal and image processing.

*Dinesh Bhatia pursued his PhD in Biomechanics and Rehabilitation Engineering from MNNIT, Allahabad, India. He is employed as an Assistant Professor at the Biomedical Engineering Department, Deenbandhu Chhotu Ram University of Science and Technology, Murthal (Sonepat), Haryana, India. He was selected for young scientist award in 2011 to pursue further research at Adaptive Neural Systems Laboratory, Florida International Univ, Maimi, USA. He has research papers in journals with teaching and research experience of more than nine years. His research focuses on understanding muscle mechanics, joint kinematics and dynamics involved in performing locomotion and routine tasks and undermining it effects during an injury or disease.