We review integrated circuits for low-frequency noise and offset rejection as a motivation for the presented digitally-assisted neural amplifier design methodology. Conventional AC-coupled neural amplifiers inherently reject input DC offset but have key limitations in area, linearity, DC drift, and spectral accuracy. Their chopper stabilization reduces low-frequency intrinsic noise at the cost of degraded area, input impedance and design complexity. DC-coupled implementations with digital high-pass filtering yield improved area, linearity, drift, and spectral accuracy and are inherently suitable for simple chopper stabilization. As a design example, a 56-channel 0.13 μm CMOS intracranial EEG interface is presented. DC offset of up to ±50 mV is rejected by a digital low-pass filter and a 16-bit delta-sigma DAC feeding back into the folding node of a folded-cascode LNA with CMRR of 65 dB. A bank of seven column-parallel fully differential SAR ADCs with ENOB of 6.6 are freely moving ratsshared among 56 channels resulting in 0.018 mm2effective channel area. Compensation-free direct input chopping yields integrated input-referred noise of 4.2 μVrmsover the bandwidth of 1 Hz to 1 kHz. The 8.7 mm2chip dissipating 1.07 mW has been validated in vivo in online intracranial EEG monitoring in freely moving rats.
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Bagheri et al. (2016) studied this question.