A Real-Time Framework to Monitor the Heart Rate Based on Photoplethysmography (PPG) Sensors at All Possible Conditions
Journal Title: Biosensors & Bioelectronics - Year 2021, Vol 12, Issue 10
Abstract
Heart Rate (HR) is one of the vital parameters in health care monitoring. Many methods are being proposed to estimate the HR in different cases, which are not compatible with real-time applications. The main objective of this work is to develop a framework for determining HR under all possible conditions using the PPG signal. The proposed work is the combination of time domain, frequency domain, and tracking using accelerometer data. This real-time framework is being developed and tested in real-time with cortex M4 board using the Keil µ vision 4 IDE. This framework detects HR under rest and motion conditions with minimum hardware resources and the accuracy of the HR in real time environment is 98.6 %. The Mean Absolute Percentage Error (MAPE) is 1.67 %, the Mean Absolute Error (MAE) is 1.18 BPM and the Reference Closeness Factor (RCF) is 0.987. The hardware implementation of the algorithm requires total of 47KB memory which runs at a speed of 5.7 MIPS.
Authors and Affiliations
P Madhan Mohan, S Naresh, G Viswanathan and CH Sai Mahesh
Keywords
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- EP ID EP741762
- DOI 10.37421/jbsbe.2021.12.298
- Views 23
- Downloads 0
A Real-Time Framework to Monitor the Heart Rate Based on Photoplethysmography (PPG) Sensors at All Possible Conditions
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