Radar-based Monitoring of Vital Signs: A Tutorial Overview

Paterniani, Giacomo; Sgreccia, Daria; DAVOLI, ALESSANDRO; Guerzoni, Giorgio; Viesti, Pasquale Di; Valenti, Anna Chiara; Vitolo, Marco; Vitetta, G.M.; Boriani, Giuseppe

doi:10.36227/techrxiv.19212918.v1

Cited by 5 publications

(1 citation statement)

References 7 publications

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“…Another attractive solution for non-invasive vital sign detection is the impulse radio ultra-wideband (IR-UWB) technology [9,10], due to its unique capabilities, such as high resolution, good penetration, low power requirement and simple hardware design. IR-UWB radar has been used in various applications such as multi-human localization [11], human computer interaction [12], gesture recognition [13][14][15] and vital sign monitoring [16][17][18][19][20][21]. Recently, many research works are focused on improving the accuracy of vital sign detection by either employing novel signal processing algorithms and/or by using specific experimental design setup for signal acquisition.…”

Section: Introductionmentioning

confidence: 99%

IR-UWB Radar-Based Robust Heart Rate Detection Using a Deep Learning Technique Intended for Vehicular Applications

et al. 2022

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This paper deals with robust heart rate detection intended for the in-car monitoring of people. There are two main problems associated with radar-based heart rate detection. Firstly, the signal associated with the human heart is difficult to separate from breathing harmonics in the frequency domain. Secondly, the vital signal is affected by any interference signal from hand gestures, lips motion during speech or any other random body motions (RBM). To handle the problem of the breathing harmonics, we propose a novel algorithm based on time series data instead of the conventionally used frequency domain technique. In our proposed method, a deep learning classifier is used to detect the pattern of the heart rate signal. To deal with the interference mitigation from the random body motions, we identify an optimum location for the radar sensor inside the car. In this paper, a commercially available Novelda Xethru X4 radar is used for signal acquisition and vital sign measurement of 5 people. The performance of the proposed algorithm is compared with and found to be superior to that of the conventional frequency domain technique.

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