Session: 07-01-02: Injury Sensing and Mitigation

Paper Number: 173743

3d Source Localization Using Simulated Eeg Signals Under Dynamic Environment 

Traumatic Brain injury (TBI) is one of the leading causes of death in the United States. Most common sources of TBI include blast impact, concussion encountered during sports, fall and accidents. According to the Brain Injury Facts and Statistics, over 64 million people have experienced one or more TBIs in their lifetime. Brain injury and trauma are also linked to neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Seizures, etc. However, these statistics do not fully capture the full extent of TBI, as many cases go unreported or are only treated in the emergency department. Neuron cells of the human brain exchange information with neighboring cells by transmitting electrical and chemical signals. The electrical activity of the human brain arises from the motion of ions across the cell membrane. Therefore, a healthy human brain generates brain signals of distinct patterns, frequencies, and amplitudes. Any deviation from the normal signal pattern in the brain waves can be an indication of TBI or underlying neurological disorders within the brain. Electroencephalography (EEG) electrodes are used to record the brain signal data that can be analyzed further to identify any abnormalities in the brain. The primary objective of this source localization study is to determine the origin of abnormal signals inside the brain. Precise identification of the affected brain region responsible for irregular signals could significantly enhance diagnostic and treatment strategies in the medical field. In this study, a three-dimensional (3D) hemispherical experimental bucket is designed and 3D printed to mimic the cranial geometry of the human head, providing a realistic experimental condition to validate the source localization technique. Two layers of EEG electrodes (16 electrodes at each layer) are placed equidistantly around the circumference of the experimental bucket at elevations of z = 36.4 mm and 66.4 mm, respectively. NaCl solution was used as a conductive medium to provide 4.65 mS/cm electrical conductivity for uniform signal dispersion. An oscillatory sine wave with 10 mV voltage at 10 Hz and 40 Hz frequency was generated as an artificial low voltage signal using LabView. The 781442-01|NI USB-6361, x series multifunctional I/O DAQ module from National Instruments was used to transmit the signal from the control computer to the AgCl stick. The artificial signal-generating AgCl stick was positioned between four sensors, two at the upper layer (sensor no. 20 and 21) and two at the bottom layer (sensor no. 4 and 5) at coordinates x=-78.6191 mm, y=15.3111 mm, and z=50.3277 mm. The electrical signal received by the sensors was transmitted to the control computer by the A/D converter. Biosemi ActiView 810-Betal software was employed to collect and record the signal. The highest signal strength was observed in sensors adjacent to the signal generator stick. A mathematical model was developed to determine the specific location of the source signal based on the recorded signal properties. This determined the source signal position at coordinates x=-76.988 mm, y=10.6828 mm and z=47.0828 mm. Ongoing research focuses on comparing the effectiveness of EEG signal source localization in static and dynamic environments. A dynamic environment includes simulated motion conditions similar to walking, running, riding a land/water vehicle, and so on. 

Presenting Author: Nafisa Ibnat Tasfee University of Texas at Arlington, Arlington TX 76019

Presenting Author Biography: Nafisa is a graduate student.

Authors:

Nafisa Ibnat Tasfee University of Texas at Arlington, Arlington TX 76019
Vi Pham University of Texas at Arlington
Ashfaq Adnan University of Texas at Arlington