This paper is in the following e-collection/theme issue:

mHealth for Data Collection and Research (1065) Respiratory Medicine (116) Machine Learning (1692) Novel Sensors and Data Acquisition Methods in Cardiology (211)

Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13737, first published .
Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology

Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology

Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology

Authors of this article:

Joseph Prinable1 Author Orcid Image ;   Peter Jones1 Author Orcid Image ;   David Boland1 Author Orcid Image ;   Cindy Thamrin2 Author Orcid Image ;   Alistair McEwan1 Author Orcid Image
Article Authors Cited by (9) Tweetations (3) Metrics

Journals

  1. Prinable J, Jones P, Boland D, McEwan A, Thamrin C. Derivation of Respiratory Metrics in Health and Asthma. Sensors 2020;20(24):7134 View
  2. Hejjel L, Béres S. Comment on ‘Pulse rate variability in cardiovascular health: a review on its applications and relationship with heart rate variability’. Physiological Measurement 2021;42(1):018001 View
  3. Tsang K, Pinnock H, Wilson A, Shah S. Application of Machine Learning Algorithms for Asthma Management with mHealth: A Clinical Review. Journal of Asthma and Allergy 2022;Volume 15:855 View
  4. Reali P, Lolatto R, Coelli S, Tartaglia G, Bianchi A. Information Retrieval from Photoplethysmographic Sensors: A Comprehensive Comparison of Practical Interpolation and Breath-Extraction Techniques at Different Sampling Rates. Sensors 2022;22(4):1428 View
  5. Natarajan A, Su H, Heneghan C, Blunt L, O’Connor C, Niehaus L. Measurement of respiratory rate using wearable devices and applications to COVID-19 detection. npj Digital Medicine 2021;4(1) View
  6. Kumar A, Ritam M, Han L, Guo S, Chandra R. Deep learning for predicting respiratory rate from biosignals. Computers in Biology and Medicine 2022;144:105338 View
  7. Kavitha K, Monisha M, Nischitha M, Nisha M, Raksitha A. Asthma prediction and monitoring. Indian Journal of Allergy, Asthma and Immunology 2023;37(2):33 View

Conference Proceedings

  1. Romero J, Ferlini A, Spathis D, Dang T, Farrahi K, Kawsar F, Montanari A. Proceedings of the 25th International Workshop on Mobile Computing Systems and Applications. OptiBreathe: An Earable-based PPG System for Continuous Respiration Rate, Breathing Phase, and Tidal Volume Monitoring View
  2. Du Y, Sun C, Ma Y, Liu S, Zhang M. 2024 International Conference on Microelectronics (ICM). Design of a PPG-Based Respiratory Sensor View