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Noncontact Detection of Heartbeat and Respiratory Rate via 77GHz Radar Based on Adaptive Double Sliding-Time Window Algorithm

机译:基于自适应双滑动时间窗算法的77GHz雷达非接触式心跳和呼吸频率检测

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In radar-based vital sign monitoring, it's a challenge to keep the trade-off between high accuracy and real-time processing capability. To offer an effective approach towards this challenge and achieve noncontact detection of human heartbeat and respiratory rate, this paper proposes a joint time-frequency detection algorithm. This algorithm bases on adaptive double sliding-time window (ADSW) technology using both fast Fourier transform (FFT) and time domain searching-peak (TSP) methods to perform preliminary detection. Then adaptive weighting is utilized to adjust the lengths of next data sliding windows dynamically and obtain the final output from previous detection results. In the meanwhile, the chosen weighting factors are determined by signal characteristics such as the short average energy (SAE) and zero-crossing rate (SAZC), which can improve the real-time capability as well as maintain good accuracy. Finally an experiment was carried out and the proposed algorithm achieved good results.
机译:在基于雷达的重要标志监测中,在高精度和实时处理能力之间保持权衡的挑战是一项挑战。为此挑战提供了有效的方法,实现了人类心跳和呼吸速率的不接触检测,提出了一种关节时频检测算法。该算法基于快速傅里叶变换(FFT)和时域搜索 - 峰值(TSP)方法的自适应双滑动时间窗口(ADSW)技术基于进行初步检测。然后,利用自适应加权来动态地调整下一个数据滑动窗的长度,并从先前的检测结果获得最终输出。同时,所选择的加权因子由诸如短的平均能量(SAE)和零交叉率(SAZC)的信号特性来确定,这可以提高实时能力以及保持良好的精度。最后进行了实验,并且所提出的算法取得了良好的效果。

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