OptiBreathe: an earable-based PPG system for continuous respiration rate, breathing phase, and tidal volume monitoring

Romero, Julia, Ferlini, Andrea, Spathis, Dimitris, Dang, Ting, Farrahi, Katayoun, Kawsar, Fahim and Montanari, Alessandro (2024) OptiBreathe: an earable-based PPG system for continuous respiration rate, breathing phase, and tidal volume monitoring. In, HOTMOBILE 2024 - Proceedings of the 2024 25th International Workshop on Mobile Computing Systems and Applications. (HOTMOBILE 2024 - Proceedings of the 2024 25th International Workshop on Mobile Computing Systems and Applications) pp. 99-106. (doi:10.1145/3638550.3641136).

Abstract

In the continuous quest to push the boundaries of mobile healthcare and fitness tracking, monitoring respiratory biomarkers emerges as a pivotal frontier. In this paper, we present OptiBreathe, a lightweight on-device earable system designed to decode the respiratory modulations within photoplethysmography (PPG) signals. OptiBreathe computes three clinical respiratory biomarkers towards enabling continuous respiratory health monitoring with wearable devices. In our effort to bridge respiratory research and earable computing, we collected a first-of-its-kind dataset that empowers researchers to explore in-ear PPG alongside gold-standard spirometry-based ground truth in order to measure respiration rate, breathing phases, and tidal volume. OptiBreathe employs multiple algorithms to measure each respiratory parameter, achieving a best mean absolute error (MAE) of 1.96 breaths per minute on respiratory rate. When estimating breathing phases and tidal volume, OptiBreathe attains an MAE of 0.48 seconds on inspiratory time, 0.14 on inhalation-exhalation ratio (inhalation duration divided by exhalation duration), and a best mean absolute percentage error (MAPE) of 17% on tidal volume (averaged across subjects) . This work shows that the best performing algorithm depends on individuals’ unique physiology, and that future research should investigate the relationship between physiological factors and algorithm performances. As we look forward, we highlight the challenges and nuances in harnessing PPG sensors for respiratory monitoring, inviting researchers to build upon our work.

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Contributors

Author: Katayoun Farrahi

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