Yoon Sewon, Baek Seungjae, Choi Inoh, Kim Soobum, Koo Bontae, Baek Youngseok, Jung Jooho, Park Sanghong, Kim Min
Department of Electronic Engineering, Pukyong National University, 45 Yongso-ro, Nam-gu, Busan 48513, Republic of Korea.
Department of Maritime ICT & Mobility Research, Korea Institute of Ocean Science & Technology, 385, Haeyang-ro, Yeongdo-gu, Busan 49111, Republic of Korea.
Sensors (Basel). 2024 Oct 21;24(20):6765. doi: 10.3390/s24206765.
Various short-range radars, such as impulse-radio ultra-wideband (IR-UWB) and frequency-modulated continuous-wave (FMCW) radars, are currently employed to monitor vital signs, including respiratory and cardiac rates (RRs and CRs). However, these methods do not consider the motion of an individual, which can distort the phase of the reflected signal, leading to inaccurate estimation of RR and CR because of a smeared spectrum. Therefore, motion compensation (MOCOM) is crucial for accurately estimating these vital rates. This paper proposes an efficient method incorporating MOCOM to estimate RR and CR with super-resolution accuracy. The proposed method effectively models the radar signal phase and compensates for motion. Additionally, applying the super-resolution technique to RR and CR separately further increases the estimation accuracy. Experimental results from the IR-UWB and FMCW radars demonstrate that the proposed method successfully estimates RRs and CRs even in the presence of body movement.
目前,各种短程雷达,如脉冲无线电超宽带(IR-UWB)雷达和调频连续波(FMCW)雷达,被用于监测生命体征,包括呼吸率和心率(RRs和CRs)。然而,这些方法没有考虑个体的运动,而个体运动可能会使反射信号的相位失真,由于频谱模糊导致RR和CR的估计不准确。因此,运动补偿(MOCOM)对于准确估计这些生命体征率至关重要。本文提出了一种结合MOCOM的有效方法,以超分辨率精度估计RR和CR。所提出的方法有效地对雷达信号相位进行建模并补偿运动。此外,分别对RR和CR应用超分辨率技术进一步提高了估计精度。来自IR-UWB和FMCW雷达的实验结果表明,即使在存在身体运动的情况下,所提出的方法也能成功估计RRs和CRs。