Noncontact Monitoring of Heart Rate and Heart Rate Variability in Geriatric Patients Using Photoplethysmography Imaging
| Autor: | Xinchi Yu, Steffen Leonhardt, Thea Laurentius, Christoph Hoog Antink, Cornelius Bollheimer |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
0206 medical engineering 02 engineering and technology Correlation Health Information Management Heart Rate Photoplethysmogram Heart rate 0202 electrical engineering electronic engineering information engineering medicine Heart rate variability Humans Computer vision Electrical and Electronic Engineering Photoplethysmography Measure heart rate Aged Geriatrics business.industry Signal Processing Computer-Assisted Healthy elderly 020601 biomedical engineering Computer Science Applications RGB color model 020201 artificial intelligence & image processing Artificial intelligence business Artifacts Algorithms Biotechnology |
| Zdroj: | IEEE journal of biomedical and health informatics. 25(5) |
| ISSN: | 2168-2208 |
| Popis: | Objective: Geriatric patients, especially those with dementia or in a delirious state, do not accept conventional contact-based monitoring. Therefore, we propose to measure heart rate (HR) and heart rate variability (HRV) of geriatric patients in a noncontact and unobtrusive way using photoplethysmography imaging (PPGI). Methods: PPGI video sequences were recorded from 10 geriatric patients and 10 healthy elderly people using a monochrome camera operating in the near-infrared spectrum and a colour camera operating in the visible spectrum. PPGI waveforms were extracted from both cameras using superpixel-based regions of interests (ROI). A classifier based on bagged trees was trained to automatically select artefact-free ROIs for HR estimation. HRV was calculated in the time-domain and frequency-domain. Results: an RMSE of 1.03 bpm and a correlation of 0.8 with the reference was achieved using the NIR camera for HR estimation. Using the RGB camera, RMSE and correlation improved to 0.48 bpm and 0.95, respectively. Correlation for HRV in the frequency-domain (LF/HF-ratio) was 0.50 using the NIR camera and 0.70 using the RGB camera. Conclusion: We were able to demonstrate that PPGI is very suitable to measure HR and HRV in geriatric patients. We strongly believe that PPGI will become clinically relevant in monitoring of geriatric patients. Significance: we are the first group to measure both HR and HRV in awake geriatric patients using PPGI. Moreover, we systematically evaluate the effects of the spectrum (near-infrared vs. visible), ROI, and additional motion artefact reduction algorithms on the accuracy of estimated HR and HRV. |
| Databáze: | OpenAIRE |
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