title: Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone.
abstract: We hypothesize that our smartphone-based fingertip image-based heart rate detection methods reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.
authors.affiliation: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. rifat.zaman@ttu.edu.
authors.forename: Rifat
authors.initials: R
authors.lastname: Zaman
authors.affiliation: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. backjoe@gmail.com.
authors.forename: Chae Ho
authors.initials: CH
authors.lastname: Cho
authors.affiliation: Instituto de Ingenieria Biológica y Médica, Pontificia Universidad Católica de Chile, Santiago 7820436, Chile. kthartmann@uc.cl.
authors.forename: Konrad
authors.initials: K
authors.lastname: Hartmann-Vaccarezza
authors.affiliation: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. tra.phan@ttu.edu.
authors.forename: Tra Nguyen
authors.initials: TN
authors.lastname: Phan
authors.affiliation: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. gwonchanyoon@gmail.com.
authors.forename: Gwonchan
authors.initials: G
authors.lastname: Yoon
authors.affiliation: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. J.Chong@ttu.edu.
authors.forename: Jo Woon
authors.initials: JW
authors.lastname: Chong
mesh_terms: D005385:Fingers; D006339:Heart Rate; D006801:Humans; D000068997:Smartphone
keywords: health monitoring; heart rate detection; smartphone discipline