TY - GEN
T1 - Monitoring of Brain Hemodynamics Coupling in Neonates using Updated Tensor Decompositions
AU - Caicedo, A.
AU - Wel, O. De
AU - Vandecappelle, M.
AU - Thewissen, L.
AU - Smits, A.
AU - Allegaert, K.
AU - De Lathauwer, L.
AU - Naulaers, G.
AU - Huffel, S. Van
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - In this paper we explore the use of updated tensor decompositions for the monitoring of brain hemodynamics in neonates. For this study, we used concomitant measurements of heart rate, mean arterial blood pressure, arterial oxygen saturation, EEG, and brain oxygenation - measured using near-infrared spectroscopy. These measurements were obtained from 22 neonates undergoing an INSURE procedure (INtubation, SURfactant and Extubation) and sedation using propofol. To develop the monitoring framework using tensors, we used radial basis kernel function (RBF) to construct a similarity matrix for consecutive segments of the signals. These matrices were concatenated forming a tensor. Updating canonical polyadic decomposition was used to evaluate the impact of propofol in the coupling between the different signals. Results indicate, as previously reported, a drop in the interaction between signals due to propofol administration. This shows that tensor decompositions can be useful in order to monitor the coupling between different physiological signals.
AB - In this paper we explore the use of updated tensor decompositions for the monitoring of brain hemodynamics in neonates. For this study, we used concomitant measurements of heart rate, mean arterial blood pressure, arterial oxygen saturation, EEG, and brain oxygenation - measured using near-infrared spectroscopy. These measurements were obtained from 22 neonates undergoing an INSURE procedure (INtubation, SURfactant and Extubation) and sedation using propofol. To develop the monitoring framework using tensors, we used radial basis kernel function (RBF) to construct a similarity matrix for consecutive segments of the signals. These matrices were concatenated forming a tensor. Updating canonical polyadic decomposition was used to evaluate the impact of propofol in the coupling between the different signals. Results indicate, as previously reported, a drop in the interaction between signals due to propofol administration. This shows that tensor decompositions can be useful in order to monitor the coupling between different physiological signals.
UR - http://www.scopus.com/inward/record.url?scp=85077869753&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2019.8857846
DO - 10.1109/EMBC.2019.8857846
M3 - Conference contribution
C2 - 31945984
AN - SCOPUS:85077869753
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 660
EP - 663
BT - 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Y2 - 23 July 2019 through 27 July 2019
ER -