title: An algorithm for extracting intracranial pressure latency relative to electrocardiogram R wave.
abstract: Intracranial pressure (ICP) latency is defined as the time interval between the peak of the QRS complex of the electrocardiogram (ECG) and the corresponding onset of intracranial pressure (ICP) pulse. Due to its inherent relationship with arterial pulse wave velocity, ICP latency may allow continuous monitoring of pathophysiological changes in the cerebrovasculature. The objective of the present work was to develop and validate a computerized algorithm for extracting ICP latency in a beat-by-beat fashion. The proposed ICP latency extraction algorithm exploits the mature technique of ECG QRS detection and includes a new adaptive peak detection methodology. The results were validated by comparing the performance of two human observers versus the algorithm in terms of locating the onset points of ICP pulses for 59 recordings extracted from 25 adult patients. The average ICP latency was 72.6+/-19.5 ms (range 40.0-159.8). The ICP pulse detection algorithm demonstrated a baseline sensitivity of 0.97 and a positive predictivity of 0.88. No difference was found in the mean location errors from comparing the results obtained by the two observers and those from comparing the results from the algorithm to those from the two observers. Further investigation is needed to demonstrate the role of ICP latency in characterizing dynamic cerebral vascular pathophysiological changes in clinical states such as subarachnoid hemorrhage and traumatic brain injury.
authors: Neural Systems and Dynamics Laboratory, Department of Neurosurgery, The David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
authors: Xiao
authors: X
authors: Hu
authors: Peng
authors: P
authors: Xu
authors: Darrin J
authors: DJ
authors: Lee
authors: Paul
authors: P
authors: Vespa
authors: Kevin
authors: K
authors: Baldwin
authors: Marvin
authors: M
authors: Bergsneider
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003627:Data Interpretation, Statistical; D004562:Electrocardiography / Q000706:statistics & numerical data*; D005260:Female; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D007427:Intracranial Pressure / Q000502:physiology*; D008297:Male; D008875:Middle Aged