TY - JOUR
T1 - Millimeter-Wave Radar Vital Signs Measurement With Random Body Movement Using Missing Data Model
AU - Qiao, Xingshuai
AU - Su, Yaobin
AU - Li, Xiuping
AU - Shan, Tao
N1 - Publisher Copyright:
© 2025 IEEE. All rights reserved.
PY - 2025
Y1 - 2025
N2 - Radar has gained increasing interest in medical and health monitoring due to its noncontact nature and privacy protection. However, the measurement of respiratory and heartbeat is influenced not only by clutter and noise, but also by human random body movement (RBM). RBM often confuses the phase information of respiratory and heartbeat echoes, making frequency estimation difficult, especially for heartbeat rate. This article addresses the problem of accurately measuring vital signs in the existence of RBM, and proposes a measurement method using the missing data model. The approach first derives and determines the pulse repetition frequency (PRF) suitable for radar transmit signals in the presence of RBM to ensure that the phase of adjacent pulses does not jump. Then, the missing data model of echo phase, reflecting variations in respiration and heartbeat, is established using a RBM recognition technique. Finally, respiration and heartbeat information is measured from the missing data. Simulation and measurement verify that the proposed method can accurately estimate respiratory and heartbeat rates even with a large RBM. Multiple experiments in different scenarios show that the root mean square error of the proposed method are 0.013 and 0.039 for respiratory and heart frequencies, respectively. That is, the respiratory and heartbeat frequencies had errors of 0.78 beats per minute (bpm) and 2.34 bpm, respectively.
AB - Radar has gained increasing interest in medical and health monitoring due to its noncontact nature and privacy protection. However, the measurement of respiratory and heartbeat is influenced not only by clutter and noise, but also by human random body movement (RBM). RBM often confuses the phase information of respiratory and heartbeat echoes, making frequency estimation difficult, especially for heartbeat rate. This article addresses the problem of accurately measuring vital signs in the existence of RBM, and proposes a measurement method using the missing data model. The approach first derives and determines the pulse repetition frequency (PRF) suitable for radar transmit signals in the presence of RBM to ensure that the phase of adjacent pulses does not jump. Then, the missing data model of echo phase, reflecting variations in respiration and heartbeat, is established using a RBM recognition technique. Finally, respiration and heartbeat information is measured from the missing data. Simulation and measurement verify that the proposed method can accurately estimate respiratory and heartbeat rates even with a large RBM. Multiple experiments in different scenarios show that the root mean square error of the proposed method are 0.013 and 0.039 for respiratory and heart frequencies, respectively. That is, the respiratory and heartbeat frequencies had errors of 0.78 beats per minute (bpm) and 2.34 bpm, respectively.
KW - Compressed sensing (CS)
KW - frequency-modulated continuous wave (FMCW) radar
KW - missing data
KW - random body movement (RBM)
KW - vital signs measurement
UR - http://www.scopus.com/inward/record.url?scp=105001207237&partnerID=8YFLogxK
U2 - 10.1109/TIM.2025.3547495
DO - 10.1109/TIM.2025.3547495
M3 - Article
AN - SCOPUS:105001207237
SN - 0018-9456
VL - 74
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
M1 - 4003814
ER -