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Morphological Feature Extraction From a Continuous Intracranial Pressure Pulse via a Peak Clustering Algorithm.

Hack-Jin Lee, Eun-Jin Jeong, Hakseung Kim

    IEEE Transactions on Bio-Medical Engineering
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    PubMed
    Summary

    Continuous analysis of intracranial pressure (ICP) pulse waveforms using a new algorithm offers a better assessment of brain injury compensatory reserve in traumatic brain injury (TBI) patients.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Critical Care Medicine

    Background:

    • Elevated intracranial pressure (ICP) is common in severe traumatic brain injury (TBI).
    • Assessing the brain's compensatory reserve is crucial for TBI patient management.
    • Mean ICP trends alone are insufficient for evaluating brain compensatory reserve.

    Purpose of the Study:

    • To develop and validate an algorithm for morphological analysis of ICP pulse waveforms.
    • To assess the compensatory reserve of the injured brain through continuous ICP waveform analysis.

    Main Methods:

    • Continuous arterial blood pressure (ABP) and ICP data from 292 TBI patients were analyzed.
    • An algorithm was developed to extract morphological landmarks (peaks, troughs, flats) from ICP waveforms.
    • ICP peaks (P1, P2, P3) were identified using peak clustering and validated against manual identification.

    Main Results:

    • The algorithm accurately identified P1, P2, and P3 peaks of the ICP waveform with 95.3%, 87.8%, and 87.5% accuracy, respectively.
    • High accuracy was achieved even with minimally filtered raw signals.
    • Morphological features from both ABP and ICP signals were extracted with high precision.

    Conclusions:

    • The developed algorithm enables real-time, simultaneous analysis of ABP and ICP pulse waveforms.
    • Extracted morphological features can potentially enhance continuous patient care for individuals with TBI.