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Accurate Heart Rate and Respiration Rate Detection Based on a Higher-Order Harmonics Peak Selection Method Using Radar Non-Contact Sensors.
Xu, Hongqiang; Ebrahim, Malikeh P; Hasan, Kareeb; Heydari, Fatemeh; Howley, Paul; Yuce, Mehmet Rasit.
Afiliação
  • Xu H; Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia.
  • Ebrahim MP; Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia.
  • Hasan K; Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia.
  • Heydari F; Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia.
  • Howley P; Planet Innovation, Box Hill, VIC 3128, Australia.
  • Yuce MR; Department of Electrical and Computer Systems Engineering, Monash University, Clayton, VIC 3800, Australia.
Sensors (Basel) ; 22(1)2021 Dec 23.
Article em En | MEDLINE | ID: mdl-35009628
ABSTRACT
Vital signs such as heart rate and respiration rate are among the most important physiological signals for health monitoring and medical applications. Impulse radio (IR) ultra-wideband (UWB) radar becomes one of the essential sensors in non-contact vital signs detection. The heart pulse wave is easily corrupted by noise and respiration activity since the heartbeat signal has less power compared with the breathing signal and its harmonics. In this paper, a signal processing technique for a UWB radar system was developed to detect the heart rate and respiration rate. There are four main stages of signal processing (1) clutter removal to reduce the static random noise from the environment; (2) independent component analysis (ICA) to do dimension reduction and remove noise; (3) using low-pass and high-pass filters to eliminate the out of band noise; (4) modified covariance method for spectrum estimation. Furthermore, higher harmonics of heart rate were used to estimate heart rate and minimize respiration interference. The experiments in this article contain different scenarios including bed angle, body position, as well as interference from the visitor near the bed and away from the bed. The results were compared with the ECG sensor and respiration belt. The average mean absolute error (MAE) of heart rate results is 1.32 for the proposed algorithm.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Radar / Taxa Respiratória Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Radar / Taxa Respiratória Idioma: En Ano de publicação: 2021 Tipo de documento: Article