A Power-Efficient Adaptive Fuzzy Resolution Control System for Wireless Body Sensor Networks

With the wide usage of long-term health care, research on wireless sensing system tends to focus on low power consumption. In this paper, a low-power and high-quality adaptive fuzzy resolution control system is created for wireless body sensor networks. The sampling clocks of analog-to-digital converters (ADCs) can be adaptively selected by an adaptive fuzzy resolution controller. The resolution of the detected signals can be adaptively changed according to the immediate feature of the signals. Users can set the regions of two condition-windows to create four adaptive conditions for the resolution control. The adaptive fuzzy resolution controller can produce control signals to select an appropriate sampling rate for the ADC with a fuzzy decision technique. The proposed adaptive fuzzy resolution controller was realized by VLSI implementation. It can operate at 100 MHz with only 539 gate counts, and its core area is 7124 μm², synthesized using a 0.18-μm CMOS process. Compared with the previous work, the work presented in this paper achieved a reduction of 33.3% core area and an improved peak signal-to-noise ratio of 15.47 dB under an abnormal situation in a wireless ECG health care monitoring application.