Non-Contact SpO2 Prediction System Based on a Digital Camera
Patients with the COVID-19 condition require frequent and accurate blood oxygen saturation (SpO2) monitoring. The existing pulse oximeters, however, require contact-based measurement using clips or otherwise fixed sensor units or need dedicated hardware which may cause inconvenience and involve addi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/9/4255 |
| _version_ | 1797534955076583424 |
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| author | Ali Al-Naji Ghaidaa A. Khalid Jinan F. Mahdi Javaan Chahl |
| author_facet | Ali Al-Naji Ghaidaa A. Khalid Jinan F. Mahdi Javaan Chahl |
| author_sort | Ali Al-Naji |
| collection | DOAJ |
| description | Patients with the COVID-19 condition require frequent and accurate blood oxygen saturation (SpO2) monitoring. The existing pulse oximeters, however, require contact-based measurement using clips or otherwise fixed sensor units or need dedicated hardware which may cause inconvenience and involve additional appointments with the patient. This study proposes a computer vision-based system using a digital camera to measure SpO2 on the basis of the imaging photoplethysmography (iPPG) signal extracted from the human’s forehead without the need for restricting the subject or physical contact. The proposed camera-based system decomposes the iPPG obtained from the red and green channels into different signals with different frequencies using a signal decomposition technique based on a complete Ensemble Empirical Mode Decomposition (EEMD) technique and Independent Component Analysis (ICA) technique to obtain the optical properties from these wavelengths and frequency channels. The proposed system is convenient, contactless, safe and cost-effective. The preliminary results for 70 videos obtained from 14 subjects of different ages and with different skin tones showed that the red and green wavelengths could be used to estimate SpO2 with good agreement and low error ratio compared to the gold standard of pulse oximetry (SA210) with a fixed measurement position. |
| first_indexed | 2024-03-10T11:37:49Z |
| format | Article |
| id | doaj.art-b7b8ff4facc34ce18522ef7eb0f0ffa3 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T11:37:49Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b7b8ff4facc34ce18522ef7eb0f0ffa32023-11-21T18:45:05ZengMDPI AGApplied Sciences2076-34172021-05-01119425510.3390/app11094255Non-Contact SpO2 Prediction System Based on a Digital CameraAli Al-Naji0Ghaidaa A. Khalid1Jinan F. Mahdi2Javaan Chahl3Electrical Engineering Technical College, Middle Technical University, Baghdad 10022, IraqElectrical Engineering Technical College, Middle Technical University, Baghdad 10022, IraqElectrical Engineering Technical College, Middle Technical University, Baghdad 10022, IraqSchool of Engineering, University of South Australia, Mawson Lakes, SA 5095, AustraliaPatients with the COVID-19 condition require frequent and accurate blood oxygen saturation (SpO2) monitoring. The existing pulse oximeters, however, require contact-based measurement using clips or otherwise fixed sensor units or need dedicated hardware which may cause inconvenience and involve additional appointments with the patient. This study proposes a computer vision-based system using a digital camera to measure SpO2 on the basis of the imaging photoplethysmography (iPPG) signal extracted from the human’s forehead without the need for restricting the subject or physical contact. The proposed camera-based system decomposes the iPPG obtained from the red and green channels into different signals with different frequencies using a signal decomposition technique based on a complete Ensemble Empirical Mode Decomposition (EEMD) technique and Independent Component Analysis (ICA) technique to obtain the optical properties from these wavelengths and frequency channels. The proposed system is convenient, contactless, safe and cost-effective. The preliminary results for 70 videos obtained from 14 subjects of different ages and with different skin tones showed that the red and green wavelengths could be used to estimate SpO2 with good agreement and low error ratio compared to the gold standard of pulse oximetry (SA210) with a fixed measurement position.https://www.mdpi.com/2076-3417/11/9/4255COVID-19pandemicnon-contact SpO2 monitoringSpO2face detectionimaging photoplethysmography (iPPG) |
| spellingShingle | Ali Al-Naji Ghaidaa A. Khalid Jinan F. Mahdi Javaan Chahl Non-Contact SpO2 Prediction System Based on a Digital Camera Applied Sciences COVID-19 pandemic non-contact SpO2 monitoring SpO2 face detection imaging photoplethysmography (iPPG) |
| title | Non-Contact SpO2 Prediction System Based on a Digital Camera |
| title_full | Non-Contact SpO2 Prediction System Based on a Digital Camera |
| title_fullStr | Non-Contact SpO2 Prediction System Based on a Digital Camera |
| title_full_unstemmed | Non-Contact SpO2 Prediction System Based on a Digital Camera |
| title_short | Non-Contact SpO2 Prediction System Based on a Digital Camera |
| title_sort | non contact spo2 prediction system based on a digital camera |
| topic | COVID-19 pandemic non-contact SpO2 monitoring SpO2 face detection imaging photoplethysmography (iPPG) |
| url | https://www.mdpi.com/2076-3417/11/9/4255 |
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