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Toward Hypertension Prediction Based on PPG-Derived HRV Signals: a Feasibility Study
- Source :
- Journal of medical systems. 42(6)
- Publication Year :
- 2017
-
Abstract
- Heart rate variability (HRV) is often used to assess the risk of cardiovascular disease, and data on this can be obtained via electrocardiography (ECG). However, collecting heart rate data via photoplethysmography (PPG) is now a lot easier. We investigate the feasibility of using the PPG-based heart rate to estimate HRV and predict diseases. We obtain three months of PPG-based heart rate data from subjects with and without hypertension, and calculate the HRV based on various forms of time and frequency domain analysis. We then apply a data mining technique to this estimated HRV data, to see if it is possible to correctly identify patients with hypertension. We use six HRV parameters to predict hypertension, and find SDNN has the best predictive power. We show that early disease prediction is possible through collecting one’s PPG-based heart rate information.
- Subjects :
- Male
medicine.medical_specialty
020205 medical informatics
0206 medical engineering
Medicine (miscellaneous)
Monitoring, Ambulatory
Health Informatics
02 engineering and technology
Electrocardiography
Wearable Electronic Devices
Health Information Management
Heart Rate
Internal medicine
Photoplethysmogram
Heart rate monitoring
Heart rate
0202 electrical engineering, electronic engineering, information engineering
medicine
Heart rate variability
Humans
Photoplethysmography
medicine.diagnostic_test
business.industry
Early disease
Signal Processing, Computer-Assisted
020601 biomedical engineering
Early Diagnosis
Hypertension
Cardiology
Feasibility Studies
Female
sense organs
business
circulatory and respiratory physiology
Information Systems
Subjects
Details
- ISSN :
- 1573689X
- Volume :
- 42
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Journal of medical systems
- Accession number :
- edsair.doi.dedup.....ea22b200cb2904b73ef4580a6f1c529f