Authors:
Hussein Sharafeddin
1
;
Lama Charafeddine
2
;
Jamila Khalaf
1
;
Ibrahim Kanj
1
and
Fadi Zaraket
2
Affiliations:
1
Lebanese University, Beirut, Lebanon
;
2
American University of Beirut, Beirut, Lebanon
Keyword(s):
Video Database, Neonatal Monitoring Data Set, Noninvasive Monitoring.
Abstract:
Background: The end goal of this project is to detect early signs of physiological disorders in term and preterm babies at the Neonatal Intensive Care Unit using real time camera-based non-contact vital signs monitoring technology. The contact sensors technology currently in use might cause stress, pain, and damage to the fragile skin of extremely preterm infants. Realization of the proposed camera based method might complement and eventually replace current technology. Non-invasive early detection of heart rate variability might allow earlier intervention, improve outcome, and decrease hospital stay. This study constructed a curated set of videos annotated with accurate and reliable measurements of the monitored vital parameters such as heart and respiratory rates so that further analysis of the curated data set lead towards the end goal. Body: The data collection process included 56 total hours of recording in 127 videos of 27 enlisted neonates. The video annotations include (1) vi
tal signs acquired from bedside patient monitors at second based intervals, (2) the neonate state of health entered and manually reviewed by a healthcare provider, (3) region of interest in video frames for heart rate detection extracted semi-automatically, and (4) the anonymized and clipped region of interest videos. Conclusion: The paper presents a curated data set of 127 video recordings of deidentified neonate foreheads annotated with vital signs, and health state in XML format. The paper also presents a utility study that shows accurate results in estimating the heart rate of term and preterm neonates. We hypothesize that the data set we collected is beneficial for improving state of the art monitoring techniques. Its timely dissemination may help lead to techniques that detect anomalies earlier, hence, leading to earlier treatment and improved outcome.
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