TY - GEN
T1 - Time-frequency analysis of hemodynamic waveforms to predict the occurrence and severity of periventricular leukomalacia
AU - Jalali, Ali
AU - Licht, Daniel
AU - Nataraj, C.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - This paper is concerned with the prediction of the occur-rence and severity of Periventricular Leukomalacia (PVL), a form of white-matter brain injury that occurs often in neonates after heart surgery. The data which is collected over a period of twelve hours after the cardiac surgery contains vital measure-ments. The fact that the exact cause of the PVL have still not been clearly understood renders a mathematical modeling ap-proach for fault diagnosis impractical, if not impossible. Hence, the decision tree classification technique has been selected for its capacity for discovering rules and novel associations in the data. It classifies groups based on reducing uncertainty in the classi-fied data. From a physiological point of view we know that there are several regulatory mechanisms responsible for fluctuation of the hemodynamic variables at different time scales. To discover the most important active physiological components which might lead to the occurrence of PVL and possibly affect its severity, we focus on the variation in the data in one minute, twenty minute and two hour periods. We calculate the energy of continuous wavelet transform coefficients of vital data at these time scales as a measure of variation in the different time frames. The re-sults obtained from developing decision tree classifiers show that among all variations in all the variables, 2 hour and 20 minute variations in the heart rate, 1 minute and 20 minute variations in Oxygen saturation, and 2 hour variations in the mean arterial pressure are the most important parameters to be able to predict PVL occurrence.
AB - This paper is concerned with the prediction of the occur-rence and severity of Periventricular Leukomalacia (PVL), a form of white-matter brain injury that occurs often in neonates after heart surgery. The data which is collected over a period of twelve hours after the cardiac surgery contains vital measure-ments. The fact that the exact cause of the PVL have still not been clearly understood renders a mathematical modeling ap-proach for fault diagnosis impractical, if not impossible. Hence, the decision tree classification technique has been selected for its capacity for discovering rules and novel associations in the data. It classifies groups based on reducing uncertainty in the classi-fied data. From a physiological point of view we know that there are several regulatory mechanisms responsible for fluctuation of the hemodynamic variables at different time scales. To discover the most important active physiological components which might lead to the occurrence of PVL and possibly affect its severity, we focus on the variation in the data in one minute, twenty minute and two hour periods. We calculate the energy of continuous wavelet transform coefficients of vital data at these time scales as a measure of variation in the different time frames. The re-sults obtained from developing decision tree classifiers show that among all variations in all the variables, 2 hour and 20 minute variations in the heart rate, 1 minute and 20 minute variations in Oxygen saturation, and 2 hour variations in the mean arterial pressure are the most important parameters to be able to predict PVL occurrence.
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U2 - 10.1115/DSCC2012-MOVIC2012-8601
DO - 10.1115/DSCC2012-MOVIC2012-8601
M3 - Conference contribution
AN - SCOPUS:84885939033
SN - 9780791845295
T3 - ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
SP - 561
EP - 566
BT - ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
T2 - ASME 2012 5th Annual Dynamic Systems and Control Conference Joint with the JSME 2012 11th Motion and Vibration Conference, DSCC 2012-MOVIC 2012
Y2 - 17 October 2012 through 19 October 2012
ER -