Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis
The contactless recording of a photoplethysmography (PPG) signal with a Red-Green-Blue (RGB) camera is known as remote photoplethysmography (rPPG). Studies have reported on the positive impact of using this technique, particularly in heart rate estimation, which has led to increased research on this...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/9/10/485 |
| _version_ | 1797475202093809664 |
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| author | Fridolin Haugg Mohamed Elgendi Carlo Menon |
| author_facet | Fridolin Haugg Mohamed Elgendi Carlo Menon |
| author_sort | Fridolin Haugg |
| collection | DOAJ |
| description | The contactless recording of a photoplethysmography (PPG) signal with a Red-Green-Blue (RGB) camera is known as remote photoplethysmography (rPPG). Studies have reported on the positive impact of using this technique, particularly in heart rate estimation, which has led to increased research on this topic among scientists. Therefore, converting from RGB signals to constructing an rPPG signal is an important step. Eight rPPG methods (plant-orthogonal-to-skin (POS), local group invariance (LGI), the chrominance-based method (CHROM), orthogonal matrix image transformation (OMIT), GREEN, independent component analysis (ICA), principal component analysis (PCA), and blood volume pulse (PBV) methods) were assessed using dynamic time warping, power spectrum analysis, and Pearson’s correlation coefficient, with different activities (at rest, during exercising in the gym, during talking, and while head rotating) and four regions of interest (ROI): the forehead, the left cheek, the right cheek, and a combination of all three ROIs. The best performing rPPG methods in all categories were the POS, LGI, and OMI methods; each performed well in all activities. Recommendations for future work are provided. |
| first_indexed | 2024-03-09T20:41:50Z |
| format | Article |
| id | doaj.art-62a031bae2c843dbb246ad2f67d0ef22 |
| institution | Directory Open Access Journal |
| issn | 2306-5354 |
| language | English |
| last_indexed | 2024-03-09T20:41:50Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Bioengineering |
| spelling | doaj.art-62a031bae2c843dbb246ad2f67d0ef222023-11-23T22:56:43ZengMDPI AGBioengineering2306-53542022-09-0191048510.3390/bioengineering9100485Effectiveness of Remote PPG Construction Methods: A Preliminary AnalysisFridolin Haugg0Mohamed Elgendi1Carlo Menon2Biomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, SwitzerlandBiomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, SwitzerlandBiomedical and Mobile Health Technology Lab, ETH Zurich, 8008 Zurich, SwitzerlandThe contactless recording of a photoplethysmography (PPG) signal with a Red-Green-Blue (RGB) camera is known as remote photoplethysmography (rPPG). Studies have reported on the positive impact of using this technique, particularly in heart rate estimation, which has led to increased research on this topic among scientists. Therefore, converting from RGB signals to constructing an rPPG signal is an important step. Eight rPPG methods (plant-orthogonal-to-skin (POS), local group invariance (LGI), the chrominance-based method (CHROM), orthogonal matrix image transformation (OMIT), GREEN, independent component analysis (ICA), principal component analysis (PCA), and blood volume pulse (PBV) methods) were assessed using dynamic time warping, power spectrum analysis, and Pearson’s correlation coefficient, with different activities (at rest, during exercising in the gym, during talking, and while head rotating) and four regions of interest (ROI): the forehead, the left cheek, the right cheek, and a combination of all three ROIs. The best performing rPPG methods in all categories were the POS, LGI, and OMI methods; each performed well in all activities. Recommendations for future work are provided.https://www.mdpi.com/2306-5354/9/10/485Imaging PPGimaging photoplethysmogramcamera-based photoplethysmographyremote health monitoringlight interaction with tissuevasomotor reactivity |
| spellingShingle | Fridolin Haugg Mohamed Elgendi Carlo Menon Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis Bioengineering Imaging PPG imaging photoplethysmogram camera-based photoplethysmography remote health monitoring light interaction with tissue vasomotor reactivity |
| title | Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis |
| title_full | Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis |
| title_fullStr | Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis |
| title_full_unstemmed | Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis |
| title_short | Effectiveness of Remote PPG Construction Methods: A Preliminary Analysis |
| title_sort | effectiveness of remote ppg construction methods a preliminary analysis |
| topic | Imaging PPG imaging photoplethysmogram camera-based photoplethysmography remote health monitoring light interaction with tissue vasomotor reactivity |
| url | https://www.mdpi.com/2306-5354/9/10/485 |
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