A 65-nm CMOS Low-Power Impulse Radar System for Human Respiratory Feature Extraction and Diagnosis on Respiratory Diseases

TY - JOUR

T1 - A 65-nm CMOS Low-Power Impulse Radar System for Human Respiratory Feature Extraction and Diagnosis on Respiratory Diseases

AU - Tseng, Shao Ting

AU - Kao, Yu Hsien

AU - Peng, Chun Chieh

AU - Liu, Jinn Yann

AU - Chu, Shao Chang

AU - Hong, Guo Feng

AU - Hsieh, Chi Hsuan

AU - Hsu, Kung Tuo

AU - Liu, Wen Te

AU - Huang, Yuan Hao

AU - Huang, Shi Yu

AU - Chu, Ta Shun

PY - 2016/4/1

Y1 - 2016/4/1

N2 - 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.

AB - 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.

KW - Biomedical applications

KW - CMOS

KW - digital signal processing (DSP)

KW - radar systems

KW - Sensors

UR - http://www.scopus.com/inward/record.url?scp=84960540662&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84960540662&partnerID=8YFLogxK

U2 - 10.1109/TMTT.2016.2536029

DO - 10.1109/TMTT.2016.2536029

M3 - Article

AN - SCOPUS:84960540662

VL - 64

SP - 1029

EP - 1041

JO - IEEE Transactions on Microwave Theory and Techniques

JF - IEEE Transactions on Microwave Theory and Techniques

SN - 0018-9480

IS - 4

M1 - 7432046

ER -