TY - JOUR
T1 - Novel fingertip image-based heart rate detection methods for a smartphone
AU - Zaman, Rifat
AU - Cho, Chae Ho
AU - Hartmann-Vaccarezza, Konrad
AU - Phan, Tra Nguyen
AU - Yoon, Gwonchan
AU - Chong, Jo Woon
N1 - Publisher Copyright:
© 2017 by the authors; licensee MDPI, Basel, Switzerland.
PY - 2017/2/12
Y1 - 2017/2/12
N2 - 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.
AB - 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.
KW - Health monitoring
KW - Heart rate detection
KW - Smartphone discipline
UR - http://www.scopus.com/inward/record.url?scp=85012916760&partnerID=8YFLogxK
U2 - 10.3390/s17020358
DO - 10.3390/s17020358
M3 - Article
C2 - 28208678
AN - SCOPUS:85012916760
SN - 1424-8220
VL - 17
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 2
M1 - 358
ER -