This article presents a neural-recording IC with automatic gain control (AGC) according to the input signal level. AGC enhances the dynamic range (DR) of the recording IC by more than 30 dB and allows it to take the benefits of the front-end amplification-based and direct-conversion-based recording structures concurrently. By adaptively controlling the analog front-end (AFE) gain, the input-referred noise (IRN) of the overall system is greatly reduced while ensuring a wide DR. A continuous-time (CT) dynamic-zoom $\Delta \Sigma $ ADC (CT-Zoom-ADC) is used for power-efficient two-step conversion. The coarse conversion output is reused for AGC, and the fine conversion resolution is adjusted adaptively by modifying the oversampling ratio according to the varying AFE gain. The presented neural-recording IC achieves 99.5-dB DR and 6.1- $\mu \text{V}_{\textrm {rms}}$ IRN over 5-kHz bandwidth, resulting in FoM _DR of 185.2 dB, the effective number of bits (ENOB) of 11.4 bits, and tolerance against artifacts with differential voltage amplitudes up to 1.6 $\text{V}_{\text {pp}}$ . Measurements with pulsatile artifacts and experiments in vivo validate that the proposed IC is applicable to the closed-loop neural interface.

Chronic monitoring of bladder activity and urine volume is essential for patients suffering from urinary dysfunctions. However, due to the anatomy and dynamics of the bladder, chronic and precise monitoring of bladder activity remains a challenge. Here, we propose a new sensing mechanism that measures the bladder volume using a resistive ladder network with contact switches. Instead of measuring the impedance between the electrode continuously, the proposed sensor provides a digitized output (‘on’ or ‘off’) when the bladder volume reaches a certain threshold value. We present simple proof-of-concept sensors which compare the discrete-mode operation to the continuous-mode operation. In addition, by using multiple pairs of this contact-mode switch in a resistor ladder structure, we demonstrate monitoring of the bladder volume in four discrete steps using an idealized balloon and an ex vivo pig’s bladder. We implemented the resistive ladder network using a conductive polypyrrole/agarose hydrogel composite which exhibits a Young’s modulus comparable to that of the bladder wall. Compared to the continuous-mode operation, the proposed sensing mechanism is less susceptible to drift due to material degradation and environmental factors.

In this work, we present an 8-channel reconfigurable multimodal neural-recording IC, which provides improved availability and usability of recording channels in various experiment scenarios. Each recording channel changes its configuration depending on whether the channel is assigned to record voltage or current signal. As a result, although the total number of channels is fixed by design, the channels utilized for voltage and current recording can be set freely and optimally for given experiment targets, scenarios, and circumstances, maximizing the availability and usability of recording channels.The proposed concept was demonstrated by fabricating the IC using a standard 180-nm CMOS process.Using the IC, we successfully performed an in vivo experiment from the hippocampal area of a mouse brain. The measured input noise of the reconfigurable front-end is 4.75 μV _rms at voltage-recording mode and 7.4 pA _rms at current-recording mode while consuming 5.72 μW/channel.