ANN based Joint Time and frequency analysis of EEG for detection of driver drowsiness

Suman Dabbu; M. Malini; B. Ram Reddy; Yashwanth Sai Reddy Vyza

doi:10.14429/dlsj.2.10370

Suman Dabbu Department of Biomedical Engineering, University College of Engineering (A), Osmania University, Hyderabad
M. Malini Department of Biomedical Engineering, University College of Engineering (A), Osmania University, Hyderabad
B. Ram Reddy Department of Physiology, Apollo Institute of Medical Sciences, Hyderabad
Yashwanth Sai Reddy Vyza Microelectronics, Delft University of Technology

DOI: https://doi.org/10.14429/dlsj.2.10370

Keywords: Drowsiness, PSG (Power within Spectrogram), PRMSD (power within the Root Mean Square Deviation)

Abstract

Drowsiness detection plays a vital role in accidents avoidance systems, thereby saving many precious lives. According to the World Health Organization, Drowsiness has been the radical contributor of road fatalities. Electroencephalogram (EEG) is a physiological signal which relays the functioning of Brain and widely used in the diagnosis of Neurological Disorders. This study extrapolates the EEG signal analysis to examine several cognitive tasks. In this report, the EEG signal is processed to detect the behavioural patterns of the brain and drowsiness state of the drivers while performing monotonous driving for long distances. An eight-channel EEG data acquisition system is used to acquire the EEG data from 20 male volunteers. The EEG signal is pre-processed and decomposed into various rhythms by applying Digital filter in MATLAB 2007b (Mathworks, Inc., USA). Time-Frequency Domain analysis has been done to extract certain features PSG and PRMSD which are statistically significant (ρ < 0.05) in the detection of drowsiness. The driving profile is classified into Active and Drowsy by a threshold, and linear regression analysis has been performed on the features extracted. A Drowsiness index is proposed stating a positive correlation (0.8-0.9) between the Total mean and the drowsy mean of the subject.

Author Biographies

Suman Dabbu, Department of Biomedical Engineering, University College of Engineering (A), Osmania University, Hyderabad

Mr Suman Dabbu obtained his BE and ME in Bio Medical Engineering, from the Dept. of BME, University College of Engineering, Osmania University. Currently working as an Assistant Professor, Dept.of BME, UCE(A), OU and carrying pursuing his PhD from same department. He has 10 years of teaching and 6 years of research experience in the field of Bio signal acquisition and feature extraction. His research interests are to study the physiological parameters and their behaviour with relevant to different diseases, development of indigenous instruments for medical applications.

M. Malini, Department of Biomedical Engineering, University College of Engineering (A), Osmania University, Hyderabad

Dr M. Malini obtained BE in Biomedical engineering, from the University College of Engineering, Osmania University, Hyderabad, in 1988. MTech in Biomedical Engineering from IIT-Bombay, and PhD in Biomedical Engineering from Osmania University. She is currently the Professor at the Department of Biomedical Engineering, University College of Engineering (A), Osmania University, Hyderabad, India. She has 25 years of teaching experience and 15 years of research experience. Her research interests include : Biomedical signal processing, medical instrumentation, brain computer interface, and embedded based medical instrumentation. She has published over 25 papers in journals and conferences.

B. Ram Reddy, Department of Physiology, Apollo Institute of Medical Sciences, Hyderabad

Prof. B. Ram Reddy obtained his MBBS and MD in Physiology from the Osmania Medical College. Currently he is the Professor & Head, Department of Physiology, Apollo Institute of Medical Sciences, Hyderabad. He has 35 years of teaching and Research experience in the
field of Neuro Physiology.

Yashwanth Sai Reddy Vyza, Microelectronics, Delft University of Technology

Mr Yashwanth Sai Reddy Vyza obtained his Bachelor from NIT Rourkela in 2017 in electronics and instrumentation engineering and is currently pursuing master’s in microelectronics at Delft University of Technology, The Netherlands. His research interests include bioelectronics and brain computer interfaces for rehabilitative applications.