Current Sensing Trends and Future Views on Brain Machine Interfaces

Abstract— Brain machine interfaces, or BMIs, are rehabilitation instruments that use feedback to control neurological processes like walking, talking, hearing, and seeing. The feedback is initiated by either decoded external perception or stimulation of the brain. A number of the main obstacles to using BMI as a rehabilitation tool are related to the processing of physiological signals. Signals and sensing devices that can effectively discriminate between different patient states over time and conditions are needed to solve these problems. Features such as implantability, spatiotemporal resolution, and invasiveness are critical for BMI sensing. In BMI, sensing is necessary to either regulate the brain's perception or its actions. Therefore, the focus of this review is on those who use brain activity to control neuro-motor activities in order to improve, attenuate, or restore bodily function in individuals with disabilities. Furthermore, the view proposes future perspectives on BMI sensing. Despite the increase in BMI research, the key obstacle is still getting findings into practical applications. This paper sheds lighter on the limits in sensing technology that have mostly impeded these changes. It is hoped that in the future, BMI applications would use paradigms that integrate electrical activity and metabolic sensors to obtain real-time brain responses. This improves information content and illness identification by increasing spatiotemporal resolution.