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Remote Vital Sign Monitoring with IMU Assisted Handheld IR-UWB Radar Sensor
Author(s) -
Seongkwon Yoon,
Shahzad Ahmed,
Sohaib Abdullah,
Sung Ho Cho
Publication year - 2025
Publication title -
ieee sensors journal
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.681
H-Index - 121
eISSN - 1558-1748
pISSN - 1530-437X
DOI - 10.1109/jsen.2025.3587432
Subject(s) - signal processing and analysis , communication, networking and broadcast technologies , components, circuits, devices and systems , robotics and control systems
Radar-based remote vital signs sensing and measurement has recently gained substantial attention due to its non-contact and non-invasive nature. Currently, a considerable amount of research is being carried out to measure human vital signs under the influence of random body movements. However, previous studies consider radar sensors to be fixed and stationary. Handheld radar-based vital signs measurement can significantly expand the practical usefulness of radar in healthcare, and search and rescue applications. This paper presents a novel handheld vital signs measurement system using impulse-radio ultra-wideband (IR-UWB) radar equipped with inertial measurement unit (IMU) sensor. The movements caused by holding the radar while performing measurements are recorded using an IMU sensor, and their effects on the radar range point are evaluated to perform range-calibration. A controlled preliminary experiment was conducted using a static wall target, demonstrating that IMU-based calibration significantly reduces spectral noise induced by handheld vibrations. The iterative method continuously observes two consecutive radar frames to track the hand movement and the movement higher than the radar range resolution are compensated accordingly. The results suggest that by applying range calibration using an IMU sensor, the handheld radar can effectively measure human vital signs with a mean absolute error of 2.01 breaths per minute (BrPM) for the breathing rate and 2.72 beats per minute (BPM) for heart rate. Contrary to that, without range-calibration, handheld radars are unable to extract vital signs. Correlation analysis between radar and reference sensor was also performed before and after calibration, which further confirmed the effectiveness of the proposed calibration framework. Furthermore, vital sign measurements before and after exercise are also measured, which validate the robustness of proposed algorithm under extreme physiological conditions.

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