Capacitive sensing is commonly employed to measure a wide range of physical quantities, including displacement, humidity, and pressure. Readout accuracy, speed, and power consumption are among the key performance characteristics during the design process for meeting the specific demands of the sensor application. Minimum parasitic effects in capacitance-to-time converters offer high suitability in precise, high-resolution applications that demand low sensitivity to environmental effects, such as in biomedical sensing devices. However, the design tradeoffs in the measurement range, resolution, and speed often limit device performance and require manual adjustment of the sensing front-end. This paper describes a low-power readout circuit for high-resolution capacitance sensing across a wide input range of up to 200 pF. A pulse-width-modulation-based, capacitance-to-time (C-T) converter is presented in 65-nm CMOS technology for miniaturised applications. Real-time monitoring of the output enables automatic adjustment of the sensing parameters that determine range, resolution, and speed, providing a flexible solution to the application needs. The system provides rapid conversion of single- and differential-mode capacitors with a 50-μs readout time while consuming 25 μW from a 1-V supply.

High-density neural electrodes in microchannel interfaces require in-situ amplification of the neural signals and rejection of high-voltage stimulus pulses leaking to the channel in order to adequately detect neural signals in the presence of concurrent stimulation. This paper presents the design of an active microchannel neural interface in 0.18 μm CMOS employing neural recording and stimulation. To reduce stimulus artifacts, a novel method is proposed that disconnects the recording module during concurrent channel stimulation and automatically applies detection and reduction of stimulus artifacts from adjacent channels using a tunable filter. Simulations show that the method provides at least 54 dB artifact attenuation.

This paper presents a prototype integrated bidirectional stimulator ASIC capable of mixed opto-electro stimulation and electrophysiological signal recording. The development is part of the research into a fully implantable device for treating motor neurone disease using optogenetics and stem cell technology. The ASIC consists of 4 stimulator units, each featuring 16-channel optical and electrical stimulation using arbitrary current waveforms with an amplitude up to 16 mA and a frequency from 1.5 Hz to 50 kHz, and a recording front-end with a programmable bandwidth of 1 Hz to 4 kHz, and a programmable amplifier gain up to 74 dB. The ASIC was implemented in a 0.18μm CMOS technology. Simulated performance in stimulation and recording is presented.

A wearable multi-sensory platform for closed-loop optical stimulation control will be demonstrated. The system is developed for restoring hand grasp movement to patients suffering from muscle paralysis, for example, amyotrophic lateral sclerosis (ALS), by optical stimulating engrafted stem cell-derived motor neurons that reinnervate the extensor and flexor muscles. Movements induced by the stimulation will be monitored by using electrical impedance tomography (EIT) to detect the impedance variation caused by muscle contraction, and using inertial measurement units (IMUs) to measure the finger movements. Learning algorithms are employed for pattern recognition and the results are used for closed-loop stimulation control. During the live demonstration, visitors can control a multi-LED stimulator via a number of different hand movements with a wearable EIT system on their forearm and IMUs on their fingers.