A novel heart rate monitoring method using a smartphone

Accurate heart rate detection is important in healthcare and exercise monitoring. Recently, heart rate monitoring using a smartphone has been highlighted due to its convenience and accuracy. In this paper, we hypothesize that our smartphone-based heart rate detection algorithm reliably detects heart rate based on fingertip image changes. Here, we have used successive video camera fingertip images with edge detection and smoothing techniques to process the fingertip images and to find out the heart rate of the subject. To investigate the capability of our proposed algorithm, we recruited 3 subjects and collected 2-min video data from each subject. We evaluated the performance of our proposed method by comparing it to the previous average intensity-based method [1]. Test results show that our proposed and previous methods give similar heart rate detection performance.

[1]  Jo Woon Chong,et al.  Arrhythmia Discrimination Using a Smart Phone , 2013, IEEE Journal of Biomedical and Health Informatics.

[2]  K. Shirai,et al.  Character Shape Restoration of Binarized Historical Documents by Smoothing via Geodesic Morphology , 2013, 2013 12th International Conference on Document Analysis and Recognition.

[3]  Monson H. Hayes,et al.  Statistical Digital Signal Processing and Modeling , 1996 .

[4]  Jo Woon Chong,et al.  Motion and Noise Artifact-Resilient Atrial Fibrillation Detection Using a Smartphone , 2016, 2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE).

[5]  R. Deriche,et al.  Anisotropic Diffusion Partial Differential Equations in Multi-Channel Image Processing : Framework and Applications. , 2007 .

[6]  Alfred M. Bruckstein,et al.  Sub-pixel distance maps and weighted distance transforms , 1996, Journal of Mathematical Imaging and Vision.

[7]  Jo Woon Chong,et al.  Photoplethysmograph Signal Reconstruction based on a Novel Motion Artifact Detection-Reduction Approach. Part II: Motion and Noise Artifact Removal , 2014, Annals of Biomedical Engineering.

[8]  Rory A. Fisher,et al.  Statistical Methods for Research Workers. , 1956 .

[9]  Alfred M. Bruckstein,et al.  Analyzing and Synthesizing Images by Evolving Curves with the Osher-Sethian Method , 1997, International Journal of Computer Vision.

[10]  Jo Woon Chong,et al.  Motion and noise artifact-resilient atrial fibrillation detection algorithm for a smartphone , 2016, 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

[11]  Jo Woon Chong,et al.  Photoplethysmograph Signal Reconstruction Based on a Novel Hybrid Motion Artifact Detection–Reduction Approach. Part I: Motion and Noise Artifact Detection , 2014, Annals of Biomedical Engineering.

[12]  Fatemehsadat Tabei,et al.  Motion and Noise Artifact-Resilient Atrial Fibrillation Detection Using a Smartphone , 2018, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.