13 - An insight into the hardware and software aspects of a BCI system with focus on ultra-low power bulk driven OTA and Gm-C based filter design, and a detailed review of the recent AI/ML techniques

Abstract

Over the last few years, Brain Computer Interface (BCI) systems have been developed for assisting disabled or paralyzed people. The BCI systems operate as communication systems that interact with their surroundings using brain activity rather than physical control. Generally, the BCI systems have four different components. This chapter addresses various methods and algorithms related to each process of this system in a reader friendly way. The brain signals are generally embedded with physiological noise and power supply interference. The Signal preprocessing module removes these noise and artifact such as eye movement, eye blinks, and muscular movement. The signal preprocessing module has different subcircuits in which the filter section is particularly important unit. Design of a good filter will boost the signal to noise ratio (SNR) of the signals. This chapter also addresses the design and working of an operational transconductance amplifier (OTA) based filter for electroencephalography (EEG) signal processing.