DocumentCode :
2099451
Title :
Utilization of temporal information for intracranial pressure development trend forecasting in traumatic brain injury
Author :
Mengling Feng ; Zhuo Zhang ; Cuntai Guan ; Hardoon, D.R. ; King, N.K.K. ; Boon Chuan Pang ; Beng Ti Ang
Author_Institution :
Inst. for Infocomm Res., Singapore, Singapore
fYear :
2012
fDate :
Aug. 28 2012-Sept. 1 2012
Firstpage :
3930
Lastpage :
3934
Abstract :
Objective. Our primary objective is to demonstrate and statistically justify that forecasting models that utilize temporal information of the historical readings of ICP and related parameters are superior, in terms of performance, compared with models that do not make use of temporal information. Material & Method. 82 traumatic brain injuries patients, who were admitted between 2002 to 2007 and were continuously monitored on ICP for more than 24 hours, are selected for the study. Together with ICP, MAP and PbtO2 were also monitored, and PRx was calculated as a moving correlation between ICP and MAP. The development trends of ICP and the related parameters are measured by first segmenting the time-series data into multiple periodic windows. The development trend of each periodic window is then discretized into three classes - elevate, stay or reduce - based on the concept of “trend line”. A systematic framework is developed to compare the forecast performance between the temporal and non-temporal models. Findings. Experimental results demonstrate that the utilization of temporal information directly leads to a considerable boost in trend forecasting performance (on average 20% relative performance gain was achieved). Moreover, the performance gain is confirmed to be statistically significant (p-value <; 0.0001) based on a paired t-test.
Keywords :
biomedical measurement; blood vessels; brain; forecasting theory; injuries; medical signal processing; patient monitoring; pressure measurement; statistical analysis; time series; ICP; MAP; PbtO2; brain tissue oxygenation; historical readings; intracranial pressure development trend forecasting model; mean arterial pressure; moving correlation; multiple periodic windows; nontemporal models; paired t-test; performance gain; pressure reactivity index; statistics; temporal information utilization; time-series data segmentation; traumatic brain injured patients; Forecasting; Iterative closest point algorithm; Machine learning algorithms; Market research; Monitoring; Predictive models; Vectors; Algorithms; Brain Injuries; Humans; Intracranial Pressure; Monitoring, Physiologic; Time Factors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2012.6346826
Filename :
6346826
Link To Document :
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