caa a22 4500 606205063 CHVBK 20210128101005.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s00034-014-9935-x doi (NATIONALLICENCE)springer-10.1007/s00034-014-9935-x A CMOS Micro-power and Area Efficient Neural Recording and Stimulation Front-End for Biomedical Applications [Elektronische Daten] [Sami Rehman, Awais Kamboh] This paper presents an ultra-low power and small area analog front-end for an implantable multichannel neural signal recording and stimulation interface, to be used in wirelessly powered implantable Brain-Machine Interfaces. For a given functionality and performance, area, power, and noise-response are the three critical parameters that define the suitability of a design for implantation. The three main components of a typical neural implant are the analog front-end, the digital processor, and the wireless data and power transceiver. Among them, neural front-end is the most power and area hungry module. This paper presents an 8-channel analog front-end prototype for simultaneous recording and stimulation, employing a novel architecture which significantly improves power and area consumption of the chip over current state of the art. In contrast to published architectures, the multichannel recording path is centered on a single super-performing tunable gain-bandwidth amplifier instead of employing a separate stand-alone amplifier for each electrode. The resulting circuitry requires smaller area and less power compared to all previously published designs. Designed in 0.5 $$\upmu $$ μ m CMOS with VDD of 1.8V, the 8-channel recording path consume a total of 77 $$\upmu $$ μ W of power and a net area of 0.24mm $$^{2}$$ 2 , allowing scalability to a high channel count. The stimulation path utilizes 8 stimulators, each employing an 8-bit multibias DAC with a current amplifier to drive electrode-electrolyte high impedance load. Each stimulator consumes full scale power of 224 $$\upmu $$ μ W and entire stimulation path occupies an area of 0.32mm $$^{2}$$ 2 . Springer Science+Business Media New York, 2014 Filter amplifier nationallicence Dneural recording nationallicence Neural stimulation nationallicence Brain-machine interface nationallicence Electrode potential nationallicence Rehman Sami Department of Electrical Engineering, School of Electrical Engineering and Computer Sciences, National University of Sciences and Technology, Islamabad, Pakistan aut Kamboh Awais Department of Electrical Engineering, School of Electrical Engineering and Computer Sciences, National University of Sciences and Technology, Islamabad, Pakistan aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/6(2015-06-01), 1725-1746 0278-081X 34:6<1725 2015 34 34 https://doi.org/10.1007/s00034-014-9935-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-014-9935-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Rehman Sami Department of Electrical Engineering, School of Electrical Engineering and Computer Sciences, National University of Sciences and Technology, Islamabad, Pakistan aut NATIONALLICENCE 700 1- Kamboh Awais Department of Electrical Engineering, School of Electrical Engineering and Computer Sciences, National University of Sciences and Technology, Islamabad, Pakistan aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/6(2015-06-01), 1725-1746 0278-081X 34:6<1725 2015 34 34