Morphological feature extraction from a continuous intracranial pressure pulse via a peak clustering algorithm

Hack Jin Lee, Eun Jin Jeong, Hakseung Kim, Marek Czosnyka, Dong Ju Kim

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Objective: An increase in intracranial pressure (ICP) is frequently observed in patients with severe traumatic brain injury (TBI). The information derived from the observation of temporal changes in the mean ICP is insufficient for assessment of the compensatory reserve of the injured brain. This assessment can be achieved via continuous morphological analysis of the pulse waveform of the ICP. Methods: Continuous arterial blood pressure (ABP) and ICP recordings from 292 TBI patients were analyzed. The algorithm extracted morphological landmarks (peaks, troughs, and flats) from the ICP. Among the extracted peaks, P1, P2, and P3 were assigned through peak clustering. The performance of the proposed method was validated through a comparison of the algorithm-defined peaks and those manually identified by experienced observers. Results: The proposed algorithm successfully identified the three distinguishing peaks of the ICP with satisfactory accuracy (95.3%, 87.8%, and 87.5% for P1, P2, and P3, respectively), even from minimally filtered raw signals. Conclusion: The algorithm extracted the morphological features from both ABP and ICP recordings with high accuracy. Significance: The ABP and ICP pulse waveforms can be simultaneously analyzed in real time using the proposed algorithm. The morphological features from these signals may aid the continuous care of patients with TBI.

Original languageEnglish
Article number7365433
Pages (from-to)2169-2176
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Volume63
Issue number10
DOIs
Publication statusPublished - 2016 Oct 1

Keywords

  • Biomedical signal processing
  • Intracranial pressure
  • Pulse morphology
  • Traumatic brain injury

ASJC Scopus subject areas

  • Biomedical Engineering

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