Recently, the research group helmed by Assistant Professor Huan from the Shenzhen-Hong Kong College of Microelectronics at the Southern University of Science and Technology (SUSTech) has made significant strides in the design of low-power sensor readout circuits. Their related paper was published in the IEEE Journal of Solid-State Circuits (JSSC), a premier journal in the realm of chip design.

Traditional resistive sensor readout circuits have long been plagued by high power consumption and a limited readout range. To tackle these issues, this research introduces a Voltage-Controlled Delay Line (VCDL)-based Pulse-Width Locked Loop (PWLL) time-domain Wheatstone bridge sensor readout circuit, specifically tailored for flexible wearable strain sensor systems. By ingeniously incorporating a Voltage-Controlled Oscillator (VCO) integrator as a loop error amplifier, the design attains infinite gain at the DC point, thereby minimizing errors. Moreover, it facilitates a high degree of system digitization, enabling support for low-voltage power supplies. In comparison to traditional VCO architectures, the VCDL offers substantial improvements in both power consumption and clock jitter performance.

Furthermore, the research team has developed a 10-bit pipelined Time-to-Digital Converter (TDC) based on delay ratios. This innovation simplifies the design process and reduces chip area by utilizing error ratios instead of conventional time amplifiers. When integrated with a high-performance strain sensor based on laser-induced graphene (LIG), this system forms a comprehensive wearable sensing solution. It is capable of accurately capturing human joint movement signals, with potential applications in health monitoring, electronic skin, and various other fields.

Test results reveal that the system operates on a mere 4.8 microwatts of power and achieves an energy efficiency of 0.38-pJ/step, placing it at the forefront of international standards. The paper's primary affiliation is the Shenzhen-Hong Kong College of Microelectronics at SUSTech, with Assistant Professor Huan serving as the corresponding author and Xu Siyuan, a 2023 undergraduate graduate, as the first author. This research received support from the National Natural Science Foundation of China.