title: Multi-resolution Convolution Methodology for ICP Waveform Morphology Analysis.
abstract: Intracranial pressure (ICP) monitoring is a key clinical tool in the assessment and treatment of patients in neurointensive care. ICP morphology analysis can be useful in the classification of waveform features.A methodology for the decomposition of an ICP signal into clinically relevant dimensions has been devised that allows the identification of important ICP waveform types. It has three main components. First, multi-resolution convolution analysis is used for the main signal decomposition. Then, an impulse function is created, with multiple parameters, that can represent any form in the signal under analysis. Finally, a simple, localised optimisation technique is used to find morphologies of interest in the decomposed data.A pilot application of this methodology using a simple signal has been performed. This has shown that the technique works with performance receiver operator characteristic area under the curve values for each of the waveform types: plateau wave, B wave and high and low compliance states of 0.936, 0.694, 0.676 and 0.698, respectively.This is a novel technique that showed some promise during the pilot analysis. However, it requires further optimisation to become a usable clinical tool for the automated analysis of ICP signals.
authors.affiliation: Department of Clinical Physics, Glasgow University, Glasgow, UK. martin.shaw@nhs.net.|NHS Greater Glasgow and Clyde, Anaesthesia and Intensive Care, Glasgow, UK. martin.shaw@nhs.net.|Academic Unit of Anaesthesia, Pain & Critical Care Medicine, University of Glasgow, Level 4, Walton Building, Glasgow Royal Infirmary, 84 Castle Street, Glasgow, G4 OSF, UK. martin.shaw@nhs.net.
authors.forename: Martin
authors.initials: M
authors.lastname: Shaw
authors.affiliation: Department of Clinical Physics, Glasgow University, Glasgow, UK.|NHS Greater Glasgow and Clyde, Anaesthesia and Intensive Care, Glasgow, UK.
authors.forename: Ian
authors.initials: I
authors.lastname: Piper
authors.affiliation: Academic Unit of Anaesthesia, Pain and Critical Care Medicine, University of Glasgow, Level 4, Walton Building, Glasgow Royal Infirmary, 84 Castle Street, Glasgow, G4 OSF, UK.
authors.forename: Christopher
authors.initials: C
authors.lastname: Hawthorne
mesh_terms: D019540:Area Under Curve; D006801:Humans; D007427:Intracranial Pressure; D008991:Monitoring, Physiologic / Q000379:methods*; D010865:Pilot Projects; D012372:ROC Curve; D012815:Signal Processing, Computer-Assisted
keywords: ICP; Morphology analysis; Multi-resolution convolution; Neurointensive care