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Extra info for Brain-Machine Interface: Circuits and Systems
The architecture as described above is not limited to two stages. Because the inter-stage sample and hold circuit decouples the individual stages, there is no difference in conversion speed whether one single stage or an arbitrary number of stages follow the first one. 4 [34–55]. 4 Multi-stage pipeline A/D converter architecture nm A=2n2 A D 3 Neural Signal Quantization Circuits 38 amplifier. The conversion mechanism is similar to that of sub-ranging conversion in each stage. Now the amplified residue is sampled by the next S/H, instead of being fed to the following stage.
A. P. Xu, A multi-channel neural-recording amplifier system with 90 dB CMRR employing CMOS-inverter-based OTAs with CMFB through supply rails in 65 nm CMOS, in IEEE International Solid-State Circuits Conference, pp. 206–207, 2015 Chapter 3 Neural Signal Quantization Circuits Abstract Integrated neural implant interface with the brain using biocompatible electrodes provides high yield cell recordings, large channel counts, and access to spike data and/or field potentials with high signal-to-noise ratio.
Parramon, E. Sanchez-Sinencio, A micropower low-noise neural recording frontend circuit for epileptic seizure detection. IEEE J. F. Bahmani, E. Sánchez-Sinencio, A highly linear pseudo-differential transconductance, in Proceedings of IEEE European Solid-State Circuits Conference, 2004, pp. K. Arfin, Low power circuits and systems for wireless neural stimulation. G. Nicollini, P. Confalonieri, D. Senderowicz, A fully differential sample-and-hold circuit for high-speed applications. IEEE J. K.
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