TY - GEN
T1 - A personalized model for monitoring vital signs using camera of the smart phone
AU - Adibuzzaman, Mohammad
AU - Ahamed, Sheikh Iqbal
AU - Love, Richard
PY - 2014
Y1 - 2014
N2 - Smart phones with optical sensors have created new opportunities for low cost and remote monitoring of vital signs. In this paper, we present a novel approach to find heart rate, perfusion index and oxygen saturation using the video images captured by the camera of the smart phones with mathematical models. We use a technique called principal component analysis (PCA) to find the band that contain most plethysmographic information. Also, we showed a personalized regression model works best for accurately detecting perfusion index and oxygen saturation. Our model has high accuracy of the physiological parameters compared to the traditional pulse oxymeter. Also, an important relationship between frame rate for image capture, minimum peak to peak distance in the pulse wave form and accuracy has been established. We showed that there is an optimal value for minimum peak to peak distance for detecting heart rate accurately. Moreover, we present the evaluation of our personalized models.
AB - Smart phones with optical sensors have created new opportunities for low cost and remote monitoring of vital signs. In this paper, we present a novel approach to find heart rate, perfusion index and oxygen saturation using the video images captured by the camera of the smart phones with mathematical models. We use a technique called principal component analysis (PCA) to find the band that contain most plethysmographic information. Also, we showed a personalized regression model works best for accurately detecting perfusion index and oxygen saturation. Our model has high accuracy of the physiological parameters compared to the traditional pulse oxymeter. Also, an important relationship between frame rate for image capture, minimum peak to peak distance in the pulse wave form and accuracy has been established. We showed that there is an optimal value for minimum peak to peak distance for detecting heart rate accurately. Moreover, we present the evaluation of our personalized models.
KW - Heart Rate
KW - Noninvasive monitoring
KW - Oxygen Saturation
KW - Perfusion Index
KW - Remote monitoring
UR - http://www.scopus.com/inward/record.url?scp=84905640322&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84905640322&partnerID=8YFLogxK
U2 - 10.1145/2554850.2555019
DO - 10.1145/2554850.2555019
M3 - Conference contribution
AN - SCOPUS:84905640322
SN - 9781450324694
T3 - Proceedings of the ACM Symposium on Applied Computing
SP - 444
EP - 449
BT - Proceedings of the 29th Annual ACM Symposium on Applied Computing, SAC 2014
PB - Association for Computing Machinery
T2 - 29th Annual ACM Symposium on Applied Computing, SAC 2014
Y2 - 24 March 2014 through 28 March 2014
ER -