Abstract
This paper presents a radar system for extracting human respiratory features. The proposed radar chip comprises three major components: a digital-to-time converter (DTC), a transmitter, and a receiver. The all-digital standard cell-based DTC achieves a timing resolution of 10 ps on a 100-ns time scale, supporting a range-gated sensing process. The transmitter is composed of a digital pulse generator. The receiver comprises a direct-sampling passive frontend for achieving high linearity, an integrator for enhancing the signal-to-noise ratio, and a successive approximation register analog-to-digital converter for signal quantization. A fully integrated CMOS impulse radar chip was fabricated using 65-nm CMOS technology, and the total power consumption is 21 mW. In the backend, a real-time digital signal-processing platform captures human respiratory waveforms via the radar chip and processes the waveforms by applying a human respiratory feature extraction algorithm. Furthermore, a clinical trial was conducted for establishing a new diagnosis workflow for identifying respiratory diseases by the proposed wireless sensor system. The proposed system was validated by applying an adaptive network-based fuzzy inference system and support vector machine algorithm to the clinical trial results. These algorithms confirmed the effectiveness of the proposed system in diagnosing respiratory diseases.