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.
This paper presents a wireless sensor system for monitoring human respiratory activities. The sensor is composed of a fully-integrated CMOS impulse radar chip and a DSP platform that is used for ...human respiratory feature extraction. The proposed and implemented radar chip was fabricated using in the TSMC 65nm CMOS technology. It can achieve the 1.5mm scanning resolution over the 15m scanning range with total 21mW power consumption. Moreover, the timing circuitry supporting range gated sensing and the pulse generator are all digital standard cell-based design which is very favorable to the technology scaling. The real-time DSP platform captures the wireless data via the CMOS radar chip and processes that through a human respiratory feature extraction algorithm. The entire system can fully operate to validate the performance of the wireless sensor system. Furthermore, the clinical trial was carried on and the system was proved helpful in rapid screen for respiratory diseases.
碩士
國立清華大學
電機工程學系
104
In recent years, the air pollution and the change of lifestyle enhance the probability of suffering lung disease. Because most of measuring instruments are expensive and placed ...in hospitals, which are operated with the assistance of the professional.
Measuring respiration information by radar system were able to provide the convenience for subject and save the travel time to hospital. In this study, we added the automatic position into the FPGA. It can accelerate the measurement time for the subject. First, we record the subject's process of respiration, then extracted respiratory feature by FSLW model. We can use the feature to estimate and judge the condition of the respiratory system.
Until now, pulmonary spirometer is one of the main instruments to measure respiratory indexes. We set the indexes as standard value, which are extracted by pulmonary spirometer, and set FSLW's indexes as the input conditions to classify respiratory ability and predict respiratory indexes. Where we use the support vector machine (SVM) to learn and classify respiratory ability, and use the adaptive neuro-fuzzy inference system (ANFIS) to learn and predict respiratory indexes. Through the results of the experiment, it indicated that the proposed the respiratory index extracted by radar system is reliable.
We combine the gait system to increase input conditions of SVM and ANFIS. According to the results, the cooperation with gait system has improved the classification accuracy and correlation with pulmonary spirometer.
