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OptiBreathe: An Earable-based PPG System for Continuous Respiration Rate, Breathing Phase, and Tidal Volume Monitoring

Authors:

Andrea Ferlini,

Dimitris Spathis,

Katayoun Farrahi,

Alessandro MontanariAuthors Info & Claims

HOTMOBILE '24: Proceedings of the 25th International Workshop on Mobile Computing Systems and Applications

Pages 99 - 106

https://doi.org/10.1145/3638550.3641136

Published: 28 February 2024 Publication History

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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Cited By

Li SJin BWang ZZhang FRen XLiu H(2024)Leveraging Attention-reinforced UWB Signals to Monitor Respiration during SleepACM Transactions on Sensor Networks10.1145/368055020:5(1-28)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3680550
Butkow KFerlini AKawsar FMascolo CMontanari AKostakos VKay JHoang T(2024)EarTune: Exploring the Physiology of Music ListeningCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3680519(644-649)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3680519

Index Terms

OptiBreathe: An Earable-based PPG System for Continuous Respiration Rate, Breathing Phase, and Tidal Volume Monitoring

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cover image ACM Conferences

HOTMOBILE '24: Proceedings of the 25th International Workshop on Mobile Computing Systems and Applications

February 2024

167 pages

ISBN:9798400704970

DOI:10.1145/3638550

Chair:
Nigel Davies,
Program Chair:
Chenren Xu

Copyright © 2024 ACM.

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Published: 28 February 2024

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HOTMOBILE '24: 25th International Workshop on Mobile Computing Systems and Applications

February 28 - 29, 2024

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Cited By

Li SJin BWang ZZhang FRen XLiu H(2024)Leveraging Attention-reinforced UWB Signals to Monitor Respiration during SleepACM Transactions on Sensor Networks10.1145/368055020:5(1-28)Online publication date: 26-Aug-2024
https://dl.acm.org/doi/10.1145/3680550
Butkow KFerlini AKawsar FMascolo CMontanari AKostakos VKay JHoang T(2024)EarTune: Exploring the Physiology of Music ListeningCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3680519(644-649)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3680519

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