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A Fast Non-Contact Vital Signs Detection Method Based on Regional Hidden Markov Model in A 77ghz Lfmcw Radar System

机译:77ghz Lfmcw雷达系统中基于区域隐马尔可夫模型的快速非接触生命体征检测方法

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The technologies of vital signs detection have been proven of great use while it is still limited by several challenges. One of the major challenges in vital signs detection is strong interferences, such as multiple targets in continuous wave radar system and random body movement (RBM), which significantly degrade the accuracy of the measurement. In this paper, a 77GHz linear frequency modulated continuous-wave (LFMCW) radar system is investigated to mitigate multiple-targets interferences. Furthermore, a novel regional hidden Markov model (RHMM) is proposed to acquire accurate estimates of the respiration rate (RR) and heart rate (HR) by exploiting the underlying slow-variant characteristics of these vital signs in the RBM environment. Experiments demonstrate the error rates of the proposed method are less than 9% for RR and less than 3% for HR in the multi-targets RBM environment.
机译:生命体征检测技术已被证明具有很大的用途,尽管它仍然受到一些挑战的限制。生命体征检测的主要挑战之一是强烈的干扰,例如连续波雷达系统中的多个目标以及随机的人体运动(RBM),这会严重降低测量的准确性。本文研究了一种77GHz线性调频连续波(LFMCW)雷达系统,以减轻多目标干扰。此外,提出了一种新颖的区域隐式马尔可夫模型(RHMM),以通过利用RBM环境中这些生命体征的潜在慢变特征来获取呼吸速率(RR)和心率(HR)的准确估计。实验表明,在多目标RBM环境中,该方法的误差率对于RR小于9%,对于HR小于3%。

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