A Multi-Channel Ultrasound System for Non-Contact Heart Rate Monitoring

• Published in: IEEE sensors journal Vol. 20; no. 4; pp. 2064 - 2074
• Main Authors: Ambrosanio, Michele, Franceschini, Stefano, Grassini, Giuseppe, Baselice, Fabio
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.02.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; bio-radar; Biomedical measurement; Cost analysis; Echoes; Elastic waves; Electrocardiography; Heart beat; Heart rate; heart rate monitoring; HR variability; Monitoring; Remote monitoring; Sensors; Skin; Transducers; Ultrasonic imaging; Ultrasound; Ultrasound system
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2019.2949435

The monitoring of vital signs represents an important measure in several fields which also go beyond the clinical environment. Nowadays, different technologies are employed to fulfil this aim, and among them, remote monitoring devices are becoming more and more popular. Following this trend, here we present an in-house, experimental ultrasound system for heartbeat detection which does not require any contact with the subject and allows remote monitoring of heart rate and its variability. The system works by transmitting ultrasound waves and receiving the echoes after the reflection on subject's pit of the neck. By comparing the phases of transmitted and received waves, it measures distances with high accuracy, and thus it can detect the sub-millimetre movements of the skin due to the pressure waves produced by heart contractions. Conversely from other existing ultrasound systems, the novelty proposed in this paper is in the multi-channel strategy to address the null point issue and selecting the best one per each measure, and in the use of an adaptive heartbeat detection algorithm. Due to the adopted transducers and electronics, the proposed system is characterised by a low cost of production. Performance analyses were carried out both in case of phantoms and volunteers to test the system. The results look promising as it was able to detect the heartbeats with reliability close to standard electrocardiography, achieving good performance also in measuring the heart rate variability. An average mean absolute error (MAE) of 0.02 beats per minute (bpm) is assessed on real data.