Research Article
HeartSense: Estimating Heart Rate from Smartphone Photoplethysmogram Using Adaptive Filter and Interpolation
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@INPROCEEDINGS{10.1007/978-3-319-19656-5_29, author={Anirban Choudhury and Aditi Misra and Arpan Pal and Rohan Banerjee and Avik Ghose and Aishwarya Visvanathan}, title={HeartSense: Estimating Heart Rate from Smartphone Photoplethysmogram Using Adaptive Filter and Interpolation}, proceedings={Internet of Things. User-Centric IoT. First International Summit, IoT360 2014, Rome, Italy, October 27-28, 2014, Revised Selected Papers, Part I}, proceedings_a={IOT360}, year={2015}, month={7}, keywords={Photoplethysmography Heart rate Adaptive filtering Noise removal Interpolation}, doi={10.1007/978-3-319-19656-5_29} }- Anirban Choudhury
Aditi Misra
Arpan Pal
Rohan Banerjee
Avik Ghose
Aishwarya Visvanathan
Year: 2015
HeartSense: Estimating Heart Rate from Smartphone Photoplethysmogram Using Adaptive Filter and Interpolation
IOT360
Springer
DOI: 10.1007/978-3-319-19656-5_29
Abstract
In recent days, physiological sensing using smartphones is gaining attention everywhere for preventive health-care. In this paper, we propose a 2-stage approach for robust heart rate (HR) calculation from photoplethysmogram (PPG) signal, captured using smartphones. Firstly, Normalized Least Mean Square (NLMS) based adaptive filter is used to clean up the noisy PPG signal. Then, heart rate is calculated from the frequency spectrum, which is further fine-tuned using different interpolation techniques. Experimental results, show that the overall HR calculation improves significantly due to the proposed 2-stage approach.
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