Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography
With the rise of modern healthcare monitoring, heart rate (HR) estimation using remote photoplethysmography (rPPG) has gained attention for its non-contact, continuous tracking capabilities. However, most HR estimation methods rely on stable, fixed sampling intervals, while practical image capture o...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/2/588 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832587530668605440 |
|---|---|
| author | Chun-Chi Chen Song-Xian Lin Hyundoo Jeong |
| author_facet | Chun-Chi Chen Song-Xian Lin Hyundoo Jeong |
| author_sort | Chun-Chi Chen |
| collection | DOAJ |
| description | With the rise of modern healthcare monitoring, heart rate (HR) estimation using remote photoplethysmography (rPPG) has gained attention for its non-contact, continuous tracking capabilities. However, most HR estimation methods rely on stable, fixed sampling intervals, while practical image capture often involves irregular frame rates and missing data, leading to inaccuracies in HR measurements. This study addresses these issues by introducing low-complexity timing correction methods, including linear, cubic, and filter interpolation, to improve HR estimation from rPPG signals under conditions of irregular sampling and data loss. Through a comparative analysis, this study offers insights into efficient timing correction techniques for enhancing HR estimation from rPPG, particularly suitable for edge-computing applications where low computational complexity is essential. Cubic interpolation can provide robust performance in reconstructing signals but requires higher computational resources, while linear and filter interpolation offer more efficient solutions. The proposed low-complexity timing correction methods improve the reliability of rPPG-based HR estimation, making it a more robust solution for real-world healthcare applications. |
| format | Article |
| id | doaj-art-d719f81d3fd443c5a329ae56b133b72b |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-d719f81d3fd443c5a329ae56b133b72b2025-01-24T13:49:27ZengMDPI AGSensors1424-82202025-01-0125258810.3390/s25020588Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote PhotoplethysmographyChun-Chi Chen0Song-Xian Lin1Hyundoo Jeong2Electrical Engineering Department, National Chiayi University, Chiayi 600355, TaiwanElectrical Engineering Department, National Chiayi University, Chiayi 600355, TaiwanDepartment of Biomedical and Robotics Engineering, Incheon National University, Incheon 22012, Republic of KoreaWith the rise of modern healthcare monitoring, heart rate (HR) estimation using remote photoplethysmography (rPPG) has gained attention for its non-contact, continuous tracking capabilities. However, most HR estimation methods rely on stable, fixed sampling intervals, while practical image capture often involves irregular frame rates and missing data, leading to inaccuracies in HR measurements. This study addresses these issues by introducing low-complexity timing correction methods, including linear, cubic, and filter interpolation, to improve HR estimation from rPPG signals under conditions of irregular sampling and data loss. Through a comparative analysis, this study offers insights into efficient timing correction techniques for enhancing HR estimation from rPPG, particularly suitable for edge-computing applications where low computational complexity is essential. Cubic interpolation can provide robust performance in reconstructing signals but requires higher computational resources, while linear and filter interpolation offer more efficient solutions. The proposed low-complexity timing correction methods improve the reliability of rPPG-based HR estimation, making it a more robust solution for real-world healthcare applications.https://www.mdpi.com/1424-8220/25/2/588remote photoplethysmography (rPPG)remote heart rate estimationtiming correction |
| spellingShingle | Chun-Chi Chen Song-Xian Lin Hyundoo Jeong Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography Sensors remote photoplethysmography (rPPG) remote heart rate estimation timing correction |
| title | Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography |
| title_full | Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography |
| title_fullStr | Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography |
| title_full_unstemmed | Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography |
| title_short | Low-Complexity Timing Correction Methods for Heart Rate Estimation Using Remote Photoplethysmography |
| title_sort | low complexity timing correction methods for heart rate estimation using remote photoplethysmography |
| topic | remote photoplethysmography (rPPG) remote heart rate estimation timing correction |
| url | https://www.mdpi.com/1424-8220/25/2/588 |
| work_keys_str_mv | AT chunchichen lowcomplexitytimingcorrectionmethodsforheartrateestimationusingremotephotoplethysmography AT songxianlin lowcomplexitytimingcorrectionmethodsforheartrateestimationusingremotephotoplethysmography AT hyundoojeong lowcomplexitytimingcorrectionmethodsforheartrateestimationusingremotephotoplethysmography |