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A Non-Contact Detection Method for Multi-Person Vital Signs Based on IR-UWB Radar.
Dang, Xiaochao; Zhang, Jinlong; Hao, Zhanjun.
  • Dang X; College of Computer Science & Engineering, Northwest Normal University, Lanzhou 730071, China.
  • Zhang J; Gansu Province Internet of Things Engineering Research Center, Lanzhou 730070, China.
  • Hao Z; College of Computer Science & Engineering, Northwest Normal University, Lanzhou 730071, China.
Sensors (Basel) ; 22(16)2022 Aug 16.
Article in English | MEDLINE | ID: covidwho-2024041
ABSTRACT
With the vigorous development of ubiquitous sensing technology, an increasing number of scholars pay attention to non-contact vital signs (e.g., Respiration Rate (RR) and Heart Rate (HR)) detection for physical health. Since Impulse Radio Ultra-Wide Band (IR-UWB) technology has good characteristics, such as non-invasive, high penetration, accurate ranging, low power, and low cost, it makes the technology more suitable for non-contact vital signs detection. Therefore, a non-contact multi-human vital signs detection method based on IR-UWB radar is proposed in this paper. By using this technique, the realm of multi-target detection is opened up to even more targets for subjects than the more conventional single target. We used an optimized algorithm CIR-SS based on the channel impulse response (CIR) smoothing spline method to solve the problem that existing algorithms cannot effectively separate and extract respiratory and heartbeat signals. Also in our study, the effectiveness of the algorithm was analyzed using the Bland-Altman consistency analysis statistical method with the algorithm's respiratory and heart rate estimation errors of 5.14% and 4.87%, respectively, indicating a high accuracy and precision. The experimental results showed that our proposed method provides a highly accurate, easy-to-implement, and highly robust solution in the field of non-contact multi-person vital signs detection.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Radar / Signal Processing, Computer-Assisted Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: S22166116

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Radar / Signal Processing, Computer-Assisted Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: S22166116