Breathing Rate Estimation from Head-Worn Photoplethysmography Sensor Data Using Machine Learning

10Citations
Citations of this article
37Readers
Mendeley users who have this article in their library.

Abstract

Breathing rate is considered one of the fundamental vital signs and a highly informative indicator of physiological state. Given that the monitoring of heart activity is less complex than the monitoring of breathing, a variety of algorithms have been developed to estimate breathing activity from heart activity. However, estimating breathing rate from heart activity outside of laboratory conditions is still a challenge. The challenge is even greater when new wearable devices with novel sensor placements are being used. In this paper, we present a novel algorithm for breathing rate estimation from photoplethysmography (PPG) data acquired from a head-worn virtual reality mask equipped with a PPG sensor placed on the forehead of a subject. The algorithm is based on advanced signal processing and machine learning techniques and includes a novel quality assessment and motion artifacts removal procedure. The proposed algorithm is evaluated and compared to existing approaches from the related work using two separate datasets that contains data from a total of 37 subjects overall. Numerous experiments show that the proposed algorithm outperforms the compared algorithms, achieving a mean absolute error of 1.38 breaths per minute and a Pearson’s correlation coefficient of 0.86. These results indicate that reliable estimation of breathing rate is possible based on PPG data acquired from a head-worn device.

Cite

CITATION STYLE

APA

Stankoski, S., Kiprijanovska, I., Mavridou, I., Nduka, C., Gjoreski, H., & Gjoreski, M. (2022). Breathing Rate Estimation from Head-Worn Photoplethysmography Sensor Data Using Machine Learning. Sensors, 22(6). https://doi.org/10.3390/s22062079

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free