DEVELOPMENT OF NEUROFEEDBACK SYSTEM USING LOW RESOLUTION BRAIN ELECTROMAGNETIC 3D TOMOGRAPHY METHOD FOR EVALUATION OF HANDS REPETITIVE ACTIVITIES MOTOR RESPONSE WITH SOFT-ROBOTIC GLOVE

• Main Author: Nadhifa Nasution, Mutiara
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/65236
• Institution: Institut Teknologi Bandung

Stroke rehabilitation is a means that can be done to restore motoric ability of stroke patients. Repetitive task training (RTT) is a method that can support the stroke rehabilitation process. The limitations of health workers become a barrier in the rehabilitation process that inhibits the effectiveness of the rehabilitation, which must be intensive and repetitive. Soft-robotic glove appears a solution for stroke patients to undertake self rehabilitation. Therefore, it is important to know the brain activation areas of patients while doing the RTT using the soft-robotic glove as a form of feedback and gain informations about the improvement throughout the rehabilitation process. This study will estimate the electrical source activity of the brain by computing source localization of the electrical activity measured on the scalp by electroencephalogram (EEG). Data acquisition is executed with a healthy man as a subject while doing repetitive grasping movements with and without wearing a soft-robotic glove. Obtained EEG data is segmented to focus the data on fitting the movement activity. Then, the data is filtered within 8-13 Hz using the Band-pass Filter (BPF) to obtain the Mu rhythm, which is closely related to motoric activities in Broadmann Area 4 and 6. Independent Component Analysis (ICA) is the initial step for EEG source localization to obtain the independent signal components and eliminate unwanted elements by referring to neuroscience theories related to Event-Related Desynchronization (ERD) and unstable components. Then, exact-Low Resolution Brain Electromagnetic Tomography (eLORETA) is performed by integrating MNI 152 head model for source localizing which results in 3D visualization of the active regions in brain cortices and current density inside the brain. From the statistic calculation of grasping movement on Brodmann area 4 and 6 on left and right hemisphere which compared to the baseline, the drop of current density occurred which is the sign of Event-Related Desynchronization (ERD) of Mu signal or the motoric activity on the brain. This calculation also shows contralateral incident except on the Brodmann area 6 of the left hemisphere which works along with the concept of bilateral. Trough the statistic calculation of hand grasping with and without soft-robotic glove, the usage of soft-robotic glove shows drop in the current density which is similar to the one without soft-robotic glove. It means soft-robotic glove can be wore to support the stroke rehabilitation process. The repetition of the hand grasping movement shows a little trend of current density drop which can be caused by the repetition effect pattern on brain, which is repetition enhancement effect as the brain in the recognition of repetitive movement pattern and repetition suppression effect when brain has recognized the repetitive movement pattern. Therefore, predicted the addition of repetition could transform the trend to repetition suppression.