TY - GEN
T1 - Sleep-quality assessment from full night audio recordings of sleep apnea patients
AU - Dafna, E.
AU - Tarasiuk, A.
AU - Zigel, Y.
PY - 2012/12/14
Y1 - 2012/12/14
N2 - In this work, a novel system (method) for sleep quality analysis is proposed. Its purpose is to assist an alternative non-contact method for detecting and diagnosing sleep related disorders based on acoustic signal processing. In this work, audio signals of 145 patients with obstructive sleep apnea were recorded (more than 1000 hours) in a sleep laboratory and analyzed. The method is based on the assumption that during sleep the respiratory efforts are more periodically patterned and consistent relative to a waking state; furthermore, the sound intensity of those efforts is higher, making the pattern more noticeable relative to the background noise level. The system was trained on 50 subjects and validated on 95 subjects. The system accuracy for detecting sleep/wake state is 82.1% (epoch by epoch), resulting in 3.9% error (difference) in detecting sleep latency, 11.4% error in estimating total sleep time, and 11.4% error in estimating sleep efficiency.
AB - In this work, a novel system (method) for sleep quality analysis is proposed. Its purpose is to assist an alternative non-contact method for detecting and diagnosing sleep related disorders based on acoustic signal processing. In this work, audio signals of 145 patients with obstructive sleep apnea were recorded (more than 1000 hours) in a sleep laboratory and analyzed. The method is based on the assumption that during sleep the respiratory efforts are more periodically patterned and consistent relative to a waking state; furthermore, the sound intensity of those efforts is higher, making the pattern more noticeable relative to the background noise level. The system was trained on 50 subjects and validated on 95 subjects. The system accuracy for detecting sleep/wake state is 82.1% (epoch by epoch), resulting in 3.9% error (difference) in detecting sleep latency, 11.4% error in estimating total sleep time, and 11.4% error in estimating sleep efficiency.
KW - Audio Signal Processing
KW - Obstructive Sleep Apnea
KW - Sleep Quality Estimation
KW - Snore Detection
UR - https://www.scopus.com/pages/publications/84870857750
U2 - 10.1109/EMBC.2012.6346760
DO - 10.1109/EMBC.2012.6346760
M3 - Conference contribution
C2 - 23366721
AN - SCOPUS:84870857750
SN - 9781424441198
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3660
EP - 3663
BT - 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
T2 - 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
Y2 - 28 August 2012 through 1 September 2012
ER -