Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review

By P. Charlton, Drew A. Birrenkott, T. Bonnici, Marco A. F. Pimentel, Alistair E. W. Johnson, J. Alastruey, Lionel Tarassenko, Peter J. Watkinson, R. Beale, David A. Clifton. IEEE Reviews in Biomedical Engineering, 2017

338 citations recorded by the source corpus.

Breathing rate (BR) is a key physiological parameter used in a range of clinical settings. Despite its diagnostic and prognostic value, it is still widely measured by counting breaths manually. A plethora of algorithms have been proposed to estimate BR from the electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. These BR algorithms provide opportunity for automated, electronic, and unobtrusive measurement of BR in both healthcare and fitness monitoring. This paper presents a review of the literature on BR estimation from the ECG and PPG. First, the structure of BR algorithms and the mathematical techniques used at each stage are described. Second, the experimental methodologies that have been used to assess the performance of BR algorithms are reviewed, and a methodological framework for the assessment of BR algorithms is presented. Third, we outline the most pressing directions for future research, including the steps required to use BR algorithms in wearable sensors, remote video monitoring, and clinical practice.

Subfields: Biomedical Engineering, Cardiology and Cardiovascular Medicine, Surgery

View Paper: https://www.semanticscholar.org/paper/d2c8ff38a2c0052a39e4e2fa8ff9d6b6b406a1c2

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In Biomedical Engineering

1. Sergio Silvestri
2. Emiliano Schena
3. Carlo Massaroni
4. Daniela Lo Presti
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In Surgery

1. Emiliano Schena
2. Carlo Massaroni
3. Massimo Sacchetti
4. Andrea Nicolò

Citations in the corpus

• The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise (2020, methodology): “Given the indirect nature of f R estimation from PPG, signal quality assessment is an important process requiring the assessment of both PPG signal quality and respiratory quality indices [62].”
• IoT-Based Healthcare-Monitoring System towards Improving Quality of Life: A Review (2022, neutral): “A bio-im-pedance sensor can be useful [51,60,61].”
• Contact-Based Methods for Measuring Respiratory Rate (2019, methodology): “The estimation of fR derived from a single-channel ECG wearable device has been demonstrated feasible when tested on 67 subjects during real-life activities (e.g., office, households and sports), with a bias of ∼0.3 ± 3 bpm [244].”