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Heart rate estimation using facial video: A review
- Source :
- Biomedical Signal Processing and Control, Biomedical Signal Processing and Control, Elsevier, 2017, 38, pp.346-360. 〈http://www.sciencedirect.com/science/article/pii/S1746809417301362?via%3Dihub〉. 〈10.1016/j.bspc.2017.07.004〉, Biomedical Signal Processing and Control, 2017, 38, pp.346-360. ⟨10.1016/j.bspc.2017.07.004⟩, Biomedical Signal Processing and Control, Elsevier, 2017, 38, pp.346-360. ⟨10.1016/j.bspc.2017.07.004⟩
- Publication Year :
- 2017
- Publisher :
- HAL CCSD, 2017.
-
Abstract
- International audience; Photoplethysmography and Ballistocardiography are two concepts that are used to measure heart rate from human, by using facial videos. Heart rate estimation is essential to determine the physiological and pathological state of a person. This paper presents a critical review of digital camera based heart rate estimating method on facial skin. This review extends the investigation on to the principles and theory behind photoplethysmography and ballistocardiography. The article contains reviews on the significance of the methods and contributions to overcome challenges such as; poor signal strength, illumination variance, and motion variance. The experiments were conducted to validate the state of the art methods on a challenging database that is available publicly. The implemented methods were validated using the database, on 27 subjects for a range of skin tones from pearl white, fair, olive to black. The results were computed using statistical methods such as: mean error, standard deviation, the root mean square error, Pearson correlation coefficient, and Bland-Altman analysis. The results derived from the experiments showed the reliability of the state of the art methods and provided direction to improve for situations involving illumination variance and motion variance. (C) 2017 Elsevier Ltd. All rights reserved.
- Subjects :
- System
Pearl white
Consensus
Mean squared error
Computer science
Speech recognition
0206 medical engineering
Facial imaging
Health Informatics
02 engineering and technology
Standard deviation
Ballistocardiography
symbols.namesake
0202 electrical engineering, electronic engineering, information engineering
Range (statistics)
medicine
[ SDV.IB ] Life Sciences [q-bio]/Bioengineering
Noncontact
Photoplethysmography
Reliability (statistics)
medicine.diagnostic_test
business.industry
Rppg
Non-contact
Pattern recognition
Variance (accounting)
020601 biomedical engineering
Pearson product-moment correlation coefficient
film.actor
Webcam
film
Signal Processing
symbols
020201 artificial intelligence & image processing
[SDV.IB]Life Sciences [q-bio]/Bioengineering
Artificial intelligence
Ppg
Camera
business
Heart rate measurement
Subjects
Details
- Language :
- English
- ISSN :
- 17468094
- Database :
- OpenAIRE
- Journal :
- Biomedical Signal Processing and Control, Biomedical Signal Processing and Control, Elsevier, 2017, 38, pp.346-360. 〈http://www.sciencedirect.com/science/article/pii/S1746809417301362?via%3Dihub〉. 〈10.1016/j.bspc.2017.07.004〉, Biomedical Signal Processing and Control, 2017, 38, pp.346-360. ⟨10.1016/j.bspc.2017.07.004⟩, Biomedical Signal Processing and Control, Elsevier, 2017, 38, pp.346-360. ⟨10.1016/j.bspc.2017.07.004⟩
- Accession number :
- edsair.doi.dedup.....680483958e27ead64e6a24b3c633eddf
- Full Text :
- https://doi.org/10.1016/j.bspc.2017.07.004〉