Abstract
AbstractDeep brain simulation (DBS) is recently approved by Food and Drug Administration (FDA) in 2018, for treatment of epilepsy. It is a procedure of placing a neurostimulator deep inside the brain that can target specific sections of brain and provide electrical stimulation to brain. DBS is proven to be very effective in the treatment of various brain-related disorders like Parkinson’s, tremors, and movement disorders, with nearly 7.5% of Indian population suffering from one or other type of neurological disorder. It is need of the time to focus on fast and affordable neural disorder diagnosis with the newest method of treatments. DBS works on brain signals processing and stimulation. The advancements in brain signal processing integrated with the predictive models of AI and ultra-low-power VLSI may lead to the next level of human–computer interface (HCI) with complete mobility. Main challenges of any bio-potential sensing are the sensitivity of the bio-electronic sensor array with its integration density, the amplifier array in such low-frequency high-density sensor configuration followed by appropriate transmitter with large data handling capability and signal integration. Conventional methods of neural signal recording are critical in modern-day neuroscience research and emerging neural prosthesis programs. Neural recording requires the use of precise, low-noise amplifier systems to acquire and condition the weak neural signals that are transduced through electrode interfaces. Neural amplifiers and amplifier-based systems are available commercially or can be designed in-house and fabricated using integrated circuit (IC) technologies, resulting in very large-scale integration or application-specific integrated circuit solutions. IC-based neural amplifiers are now used to acquire untethered/portable neural recordings, as they meet the requirements of a miniaturized form factor, lightweight, and low power consumption. Furthermore, such miniaturized and low-power IC neural amplifiers are now being used in emerging implantable neural prosthesis technologies. This review focuses on neural amplifier-based devices and is presented in two interrelated parts. First, neural signal recording is reviewed, and practical challenges are highlighted. Current amplifier designs with increased functionality and performance and without penalties in chip size and power are featured. Second, applications of IC-based neural amplifiers in basic science experiments (e.g., cortical studies using animal models), neural prostheses (e.g., brain/nerve machine interfaces), and treatment of neuronal diseases (e.g., DBS for treatment of epilepsy) are highlighted. This review paper deals with different challenges in neural recorder design from amplifier design to signal processing technique and also the on chi off-chip computation challenges.KeywordsNeural amplifierVLSIEEG
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