As power consumption is one of the major issues in biomedical implantable devices, in this paper, a novel quantization method is proposed for successive approximation register (SAR) analog-to-digital converters (ADCs) which can save 80% power consumption in contrast to conventional structure for electroencephalogram (EEG) signal recording systems. According to the characteristics of neural signals, the principle of the proposed power saving technique was inspired such that only the difference between current input sample and the previous one is quantized, using a power efficient SAR ADC with fewer resolutions. To verify the proposed quantization scheme, the ADC is systematically modeled in Matlab and designed and simulated in circuit level using 0.18[Formula: see text][Formula: see text]m CMOS technology. When applied to neural signal acquisition, spice simulations show that at sampling rate of 25[Formula: see text]kS/s, the proposed 8-bit ADC consumes 260[Formula: see text]nW of power from 1.8[Formula: see text]V supply voltage while achieving 7.1 effective number of bits.
A High-Accuracy and Power-Efficient Self-Optimizing Wireless Water Level Monitoring IoT Device for Smart City
