College of Computer Science & Engineering, Northwest Normal University, Lanzhou 730071, China.
Gansu Province Internet of Things Engineering Research Center, Lanzhou 730070, China.
Sensors (Basel). 2022 Aug 16;22(16):6116. doi: 10.3390/s22166116.
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.
随着无处不在的传感技术的蓬勃发展,越来越多的学者关注非接触式生命体征(如呼吸频率(RR)和心率(HR))检测的研究。由于冲激无线电超宽带(IR-UWB)技术具有非侵入性、高穿透性、精确测距、低功耗和低成本等特点,因此更适合非接触式生命体征检测。因此,本文提出了一种基于 IR-UWB 雷达的非接触式多人体生命体征检测方法。该技术通过使用优化算法 CIR-SS(基于信道冲激响应(CIR)平滑样条方法)解决了现有算法无法有效分离和提取呼吸和心跳信号的问题。此外,我们还使用 Bland-Altman 一致性分析统计方法分析了算法的有效性,算法的呼吸和心率估计误差分别为 5.14%和 4.87%,表明其具有较高的准确性和精度。实验结果表明,我们提出的方法在非接触式多人生命体征检测领域提供了一种高度准确、易于实现和高度稳健的解决方案。