Monitoring respiratory pattern in adult and infant via contactless detection of thorax and abdomen movements through SoC UWB pulse radar sensor

A new system-on-a-chip radar sensor for next-generation wearable wireless interface applied to the human health care and safeguard is presented. The system overview is provided and the feasibility study of the radar sensor is presented. In detail, the overall system consists of a radar sensor for detecting the heart and breath rates and a low-power IEEE 802.15.4 ZigBee radio interface, which provides a wireless data link with remote data acquisition and control units. In particular, the pulse radar exploits 3.1–10.6 GHz ultra-wideband signals which allow a significant reduction of the transceiver complexity and then of its power consumption. The operating principle of the radar for the cardiopulmonary monitoring is highlighted and the results of the system analysis are reported. Moreover, the results obtained from the building-blocks design, the channel measurement, and the ultra-wideband antenna realization are reported.

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Planar Differential Antenna for Short-Range UWB Pulse Radar Sensor

IEEE Antennas and Wireless Propagation Letters ◽

10.1109/lawp.2013.2291957 ◽

2013 ◽

Vol 12 ◽

pp. 1527-1530 ◽

Cited By ~ 6

Author(s):

Domenico Pepe ◽

Luigi Vallozzi ◽

Hendrik Rogier ◽

Domenico Zito

Keyword(s):

Short Range ◽

Radar Sensor ◽

Pulse Radar

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SoC CMOS UWB Pulse Radar Sensor for Contactless Respiratory Rate Monitoring

IEEE Transactions on Biomedical Circuits and Systems ◽

10.1109/tbcas.2011.2176937 ◽

2011 ◽

Vol 5 (6) ◽

pp. 503-510 ◽

Cited By ~ 106

Author(s):

Domenico Zito ◽

Domenico Pepe ◽

Martina Mincica ◽

Fabio Zito ◽

Alessandro Tognetti ◽

...

Keyword(s):

Respiratory Rate ◽

Radar Sensor ◽

Pulse Radar

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Arteriovenous Fistula Flow Dysfunction Surveillance: Early Detection Using Pulse Radar Sensor and Machine Learning Classification

Biosensors ◽

10.3390/bios11090297 ◽

2021 ◽

Vol 11 (9) ◽

pp. 297

Author(s):

Cheng-Hsu Chen ◽

Teh-Ho Tao ◽

Yi-Hua Chou ◽

Ya-Wen Chuang ◽

Tai-Been Chen

Keyword(s):

Arteriovenous Fistula ◽

Classification Algorithm ◽

Support Vector ◽

Svm Classifier ◽

High Morbidity ◽

Radar Sensor ◽

Svm Classification ◽

Ultrasound Dilution ◽

Machine Learning Classification ◽

Pulse Radar

Vascular Access (VA) is often referred to as the “Achilles heel” for a Hemodialysis (HD)-dependent patient. Both the patent and sufficient VA provide adequacy for performing dialysis and reducing dialysis-related complications, while on the contrary, insufficient VA is the main reason for recurrent hospitalizations, high morbidity, and high mortality in HD patients. A non-invasive Vascular Wall Motion (VWM) monitoring system, made up of a pulse radar sensor and Support Vector Machine (SVM) classification algorithm, has been developed to detect access flow dysfunction in Arteriovenous Fistula (AVF). The harmonic ratios derived from the Fast Fourier Transform (FFT) spectrum-based signal processing technique were employed as the input features for the SVM classifier. The result of a pilot clinical trial showed that a more accurate prediction of AVF flow dysfunction could be achieved by the VWM monitor as compared with the Ultrasound Dilution (UD) flow monitor. Receiver Operating Characteristic (ROC) curve analysis showed that the SVM classification algorithm achieved a detection specificity of 100% at detection thresholds in the range from 500 to 750 mL/min and a maximum sensitivity of 95.2% at a detection threshold of 750 mL/min.

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