Brain Waves Signal Modeling for Object Classification Using Random Forest Method
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Brain Signal, Signal Processing, Machine Learning, Human Vision
Abstract
In this research, the connection between human vision information and simultaneous brain signal is studied; to this end, an experiment has been made. Clearly, brain wave signals are captured in the situation that the participants are looking at the specific object. More precisely, the brain signals of 9 shapes are recorded for each participant. Also, 9 participants voluntarily have been involved in the experiment. Then, the collected signals are organised into training and testing groups. After that Random Forest classifier is used to classify the signals.
The accuracy results demonstrate a connection between human vision information and simultaneous brain signal. Overall accuracy for all shapes as separated as per cases is 20.48%, and for shapes, numbers 6 and 8 are 55.34% 36.57%, respectively. It can be concluded that human brain signals can be categorised based on human vision inputs.
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Copyright (c) 2022 Younus H. Mala, Mahmud A. Mohammad
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