TY - GEN
T1 - Motion and Noise Artifact-Resilient Atrial Fibrillation Detection Using a Smartphone
AU - Zaman, Rifat
AU - Chong, Jo Woon
AU - Cho, Chae Ho
AU - Esa, Nada
AU - McManus, David D.
AU - Chon, Ki H.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/8/16
Y1 - 2016/8/16
N2 - Smartphone signals corrupted by motion and noise artifacts (MNAs) are often misclassified into atrial fibrillation (AF) by our previous smartphone AF detection application [1]. We developed an MNA-tolerant AF detection algorithm for smartphones, which first detects MNAs in the smartphone signals, removes them, and finally detects AF from the MNA-free smartphone signals. To detect MNAs, we used time and frequency-domain parameters: high-pass filtered signal amplitude, successive pulse amplitude ratio, and successive maximum dominant frequency. AFs are detected using our previous AF detection algorithm based on root mean square of successive RR difference (RMSSD) and Shannon Entropy (ShE) values [1]. The clinical results show that the accuracy, sensitivity and specificity of the proposed AF algorithm are 0.9632, 0.9341, and 0.9899, respectively.
AB - Smartphone signals corrupted by motion and noise artifacts (MNAs) are often misclassified into atrial fibrillation (AF) by our previous smartphone AF detection application [1]. We developed an MNA-tolerant AF detection algorithm for smartphones, which first detects MNAs in the smartphone signals, removes them, and finally detects AF from the MNA-free smartphone signals. To detect MNAs, we used time and frequency-domain parameters: high-pass filtered signal amplitude, successive pulse amplitude ratio, and successive maximum dominant frequency. AFs are detected using our previous AF detection algorithm based on root mean square of successive RR difference (RMSSD) and Shannon Entropy (ShE) values [1]. The clinical results show that the accuracy, sensitivity and specificity of the proposed AF algorithm are 0.9632, 0.9341, and 0.9899, respectively.
UR - https://www.scopus.com/pages/publications/84987650959
U2 - 10.1109/CHASE.2016.75
DO - 10.1109/CHASE.2016.75
M3 - Conference contribution
AN - SCOPUS:84987650959
T3 - Proceedings - 2016 IEEE 1st International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016
SP - 366
EP - 369
BT - Proceedings - 2016 IEEE 1st International Conference on Connected Health
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2016
Y2 - 27 June 2016 through 29 June 2016
ER -