TY - GEN
T1 - Automated detection of sleep apnea in infants using minimally invasive sensors
AU - Cohen, Gregory
AU - De Chazal, Philip
PY - 2013
Y1 - 2013
N2 - To address the difficult and necessity of early detection of sleep apnea hypopnea syndrome in infants, we present a study into the effectiveness of pulse oximetry as a minimally invasive means of automated diagnosis of sleep apnea in infants. Overnight polysomnogram data from 328 infants were used to extract time-domain based oximetry features and scored arousal data for each subject. These records were then used to determine apnea events and to train a classifier model based on linear discriminants. Performance of the classifier was evaluated using a leave-one-out cross-validation scheme and an accuracy of 68% was achieved, with a specificity of 68.6% and a sensitivity of 55.9%.
AB - To address the difficult and necessity of early detection of sleep apnea hypopnea syndrome in infants, we present a study into the effectiveness of pulse oximetry as a minimally invasive means of automated diagnosis of sleep apnea in infants. Overnight polysomnogram data from 328 infants were used to extract time-domain based oximetry features and scored arousal data for each subject. These records were then used to determine apnea events and to train a classifier model based on linear discriminants. Performance of the classifier was evaluated using a leave-one-out cross-validation scheme and an accuracy of 68% was achieved, with a specificity of 68.6% and a sensitivity of 55.9%.
UR - http://handle.uws.edu.au:8081/1959.7/533027
UR - http://embc2013.embs.org/
U2 - 10.1109/EMBC.2013.6609834
DO - 10.1109/EMBC.2013.6609834
M3 - Conference Paper
SN - 9781457702167
SP - 1652
EP - 1655
BT - Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 3 - 7 July 2013, Osaka, Japan
PB - IEEE
T2 - IEEE Engineering in Medicine and Biology Society. Annual Conference
Y2 - 30 April 2015
ER -