Prospects of Electrooculography in Human-Computer Interface Based Neural Rehabilitation for Neural Repair Patients

Disable persons are facing a lot of problems in daily life activities. They need some help from others to fulfil their needs every day. To avoid this condition modern technology help such persons to overcome the problem in a natural way like bio signal based-human–computer interaction. In this paper, we focused to study the performance of male subjects compared with female subjects to analyze the performance to design Electrooculographgy-based HCI using periodogram and neural network. Five male subjects and five female subjects are involved in this experiment. From the experimental analysis, we identified that male performance was maximum compared to female performance. From this paper, we analyzed that subject S4 from male subjects and subject S10 from female subjects performance was marginally high compared with other subjects performance took part in this experiment. From the classification accuracy, we conclude that male subject performance was encouraged with 93.67 % and 92.28% for female subjects. The offline test was conducted in the indoor environment to identify the tasks to confirm the performance of individual subjects. From the offline analysis, we conclude that subject S4 performance was high compared to other subjects take part in this paper. Subject S4 took less time to perform the task as per the protocol. Through this paper, we confirm that scheming HCI is achievable.