The key requirements of a reliable neural signal recording system include low power to support long-term monitoring, low noise, minimum tissue damage, and wireless transmission. The neural spikes are also detected and sorted on-chip/off-chip to implement closed-loop neuromodulation in a high channel count setup. All these features together constitute an empirical neural recording system for neuroscience research. In this prospectus, we propose to develop a neural signal acquisition system with wireless transmission and feature extraction. We start by designing a prototype entirely built with commercial-off-the-shelf components, which includes recording and wireless transmission of synthetic neural data and feature extraction. We then conduct the CMOS implementation of the low-power multi-channel neural signal recording read-out circuit, which enables the in-vivo recording with a small form factor. Another direction of this thesis is to design a self-powered motion tracking read-out circuit for wearable sensors. As the wearable industry continues to advance, the need for self-powered medical devices is growing significantly. In this line of research, we propose a self-powered motion sensor based on reverse electrowetting-on-dielectric (REWOD) with low-power integrated electronics for remotely monitoring health conditions. We design the low-power read-out circuit for a wide range of input charges, which is generated from the REWOD sensor.

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An accurate, high-speed, fully differential difference amplifier for current sensing utilizing the chopper approach was implemented in a 0.18 μm complementary metal-oxide-semiconductor (CMOS) technology. Unlike state-of-the-art solutions, we use a higher chopping frequency in the MHz range due to the bandwidth requirements of the introduced circuits for the latter application, namely, low-side phase-current measurement in motor control circuits. Except the low-pass filter (LPF) effect of the output stage, no additional LPF was integrated in hardware at the output of the circuits. We show that on the other hand a digital LPF, which can be integrated in the field-programmable gate-array (FPGA) logic or microcontroller used for the motor control, offers a higher flexibility in terms of filter design. Weak input signals of only few mV can be reconstructed with a high accuracy. This is demonstrated for a 500 kHz rectangular signal and a chopping frequency of 20 MHz. Note that an input-signal frequency of several hundreds of kHz with harmonics in the MHz region is very challenging for chopper amplifiers. Still, a significant decrease of the input-referred noise is demonstrated, especially cancelling out the 1/f-noise achieving a remaining noise floor of approximately 8.5 nV/√Hz. Overall, the input-referred noise level can be pushed far below 50 μV (root mean square). Moreover, using a quite relaxed second-order Butterworth filter with a 3 dB corner frequency of 1 MHz, input-referred noise levels of 10 μV (root mean square) can be easily achieved at the costs of reduced bandwidth. The lowest achieved input offset is 50 μV. The gain is adjusted by resistive feedback and is approximately 40 dB. Hence, the amplifier is suitable for current sensing in motor control circuits, and a significant reduction of the shunt resistance typically used for this purpose will be possible.

The objective of this research is to develop and design front-end analog circuits for Capacitive Micromachined Ultrasound Transducers (CMUTs) and optical grating MEMS microphone. This work is motivated by the fact that with micro-scaling, MEMS sense capacitance gets smaller in a CMUT array element for intravascular ultrasound imaging, which has dimensions of 70um x 70um and sub pico-farad capacitance. Smaller sensors lead to a lower active-to-parasitic ratio and thus, degrads sensitivity. Area and power requirements are also very stringent, such as the case of intravascular catheter implementations with CMOS-First CMUT fabrication approach. In this implementation, capacitive feedback charge amplifier is an alternative approach to resistive feedback amplifiers. Capacitive feedback charge amplifier provides high sensitivity, small area, low distortion and saving power. This approach of charge amplifiers is also suitable in capacitive microphones where it provides low power and high sensitivity. Another approach to overcome capacitive detection challenges is to implement optical detection. In the case of biomimetic microphone structure, optical detection overcomes capacitive detection's thermal noise issues. Also with micro-scaling, optical detection overcomes the increased parasitics without any sensitivity degradation, unlike capacitive detection. For hearing aids, along with sensitivity, battery life is another challenge. We propose the use of 1-bit front-end sigma-delta ADC for overall improved hearing aid power efficiency. Front-end interface based on envelope detection and synchronous detection schemes have also been designed. These interface circuits consume currents in microampere range from a 1.5V battery. Circuit techniques are used for maximizing linear range and signal handling with low supplies. The entire front end signal processing with Vertical Cavity Surface Emitting Laser (VCSEL) drivers, photodiodes, filters and detectors is implemented on a single chip in 0.35um CMOS process.