Noise Immunity-Enhanced Capacitance Readout Circuit for Human Interaction Detection in Human Body Communication Systems

Abstract

Recent healthcare systems based on human body communication (HBC) require human interaction sensors. Due to the conductive properties of the human body, capacitive sensors are most widely known and are applied to many electronic gadgets for communication. Capacitance fluctuations due to the fact of human interaction are typically converted to voltage levels using some analog circuits, and then analog-to-digital converters (ADCs) are used to convert analog voltages into digital codes for further processing. However, signals detected by human touch naturally contain large noise, and an active analog filter that consumes a lot of power is required. In addition, the inclusion of ADCs causes the system to use a large area and amount of power. The proposed structure adopts a digital-based moving average filter (MAF) that can effectively operate as a low-pass filter (LPF) instead of a large-area and high-power consumption analog filter. In addition, the proposed ∆C detection algorithm can distinguish between human interaction and object interaction. As a result, two individual digital signals of touch/release and movement can be generated, and the type and strength of the touch can be effectively expressed without the help of an ADC. The prototype chip of the proposed capacitive sensing circuit was fabricated with commercial 65 nm CMOS process technology, and its functionality was fully verified through testing and measurement. The prototype core occupies an active area of 0.0067 mm2, consumes 7.5 uW of power, and has a conversion time of 105 ms.