A comprehensive review on a brain simulation tool and its applications
Source
AI Enabled Smart Healthcare Using Biomedical Signals
Date Issued
2022-05-27
Author(s)
Raghuvanshi, Ankita
Sarin, Mohit
Shukla, Praveen Kumar
Verma, Shrish
Chaurasiya, Rahul Kumar
Abstract
Brain-computer interface, widely known as BCI, is a relatively new field of research that has emerged as promising field research in the last few decades. It is defined as a combination of software as well as hardware that give us the tool to control external devices by using our brain signals as commands. In this chapter, the authors discuss the various tools that can be used to analyze and perform different functions on the brain signals, create BCI models, simulations, etc. In this study, they compare the tools and tabulate how they might be useful for the user's requirements. Additionally, they have implemented the use of tools for real-time applications. The experimental analysis presented in this work utilizes MAMEM EEG steady-state visually evoked potential (SSVEP) dataset I. Five different frequencies (6.66, 7.50, 8.57, 10.00, and 12.00 Hz) were used for the visual stimulation. The authors have analyzed different parameters like power spectrum density, power spectrum, and inter-trial coherence (ITC) through EEGLAB.
