Physiological parameter monitoring from optical recordings with a mobile phone
Open accessAbstract
We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor. We confirm the accuracy of measurements of breathing rate, cardiac R-R intervals, and blood oxygen saturation, by comparisons to standard methods for making such measurements (respiration belts, ECGs, and pulse-oximeters, respectively). Measurement of respiratory rate uses a previously reported algorithm developed for use with a pulse-oximeter, based on amplitude and frequency modulation sequences within the light signal. We note that this technology can also be used with recently developed algorithms for detection of atrial fibrillation or blood loss.
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Papers that have developed health monitoring systems have mostly used their own data gathering experiments to design, model and test the data analysis step.
“The papers which have developed the health monitoring systems have mostly used their own data gathering experiments to design, model and test the data analysis step [26,38,88].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [88]
Some research has been done on unlabeled data to consider uncontrolled situations, especially for experimental data sets.
“Some researches have been done on unlabeled data in order to consider uncontrolled situations for especially experimental data sets [39,44,88].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [88]
Monitoring cardiorespiratory activities using a PPG signal is a well-established non-invasive technique.
“Monitoring cardiorespiratory activities using a PPG signal is a well-established non-invasive technique [44,93].”
From The Current State of Optical Sensors in Medical Wearables (2022) · cites this paper as [93]
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- Authors
- Scully, C. G., Lee, J., Meyer, J., Gorbach, A. M., Granquist-Fraser, D., Mendelson, Y., & Chon, K. H.
- Affiliations
- Worcester Polytechnic Institute (US)
- National Institutes of Health (US)
- Corresponding author
- Chon, K. H.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2012-02
- Volume
- 59
- Issue
- 2
- Pages
- 303-306
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- PMC
- PMC3476722
- OpenAlex
- W2060642847
- Cited by
- 452
- References
- 15
- Citations by year
- 2026: 5 · 2025: 15 · 2024: 19 · 2023: 23 · 2022: 28 · 2021: 26 · 2020: 31 · 2019: 32 · 2018: 38 · 2017: 38 · 2016: 37 · 2015: 57 · 2014: 44 · 2013: 36 · 2012: 22
- FWCI
- 19.29
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Institute of Biomedical Imaging and Bioengineering (ZICEB000059, ZICEB000077)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Keywords
- smartphone sensing, fingertip photoplethysmography, physiological monitoring, respiratory rate estimation, RR interval, oxygen saturation, pulse oximetry, atrial fibrillation detection
- MeSH terms
- Algorithms, Heart Rate, Humans, Monitoring, Physiologic, Oximetry, Signal Processing, Computer-Assisted, Cell Phone, Respiratory Rate, Remote Sensing Technology
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