Artifact identification and removal methodologies for intracranial pressure signals: a systematic scoping review
- PMID: 39637554
- DOI: 10.1088/1361-6579/ad9af4
Artifact identification and removal methodologies for intracranial pressure signals: a systematic scoping review
Abstract
Objective. Intracranial pressure measurement (ICP) is an essential component of deriving of multivariate data metrics foundational to improving understanding of high temporal relationships in cerebral physiology. A significant barrier to this work is artifact ridden data. As such, the objective of this review was to examine the existing literature pertinent to ICP artifact management.Methods.A search of five databases (BIOSIS, SCOPUS, EMBASE, PubMed, and Cochrane Library) was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines with the PRISMA Extension for Scoping Review. The search question examined the methods for artifact management for ICP signals measured in human/animals.Results.The search yielded 5875 unique results. There were 19 articles included in this review based on inclusion/exclusion criteria and article references. Each method presented was categorized as: (1) valid ICP pulse detection algorithms and (2) ICP artifact identification and removal methods. Machine learning-based and filter-based methods indicated the best results for artifact management; however, it was not possible to elucidate a single most robust method.Conclusion.There is a significant lack of standardization in the metrics of effectiveness in artifact removal which makes comparison difficult across studies. Differences in artifacts observed on patient neuropathological health and recording methodologies have not been thoroughly examined and introduce additional uncertainty regarding effectiveness.Significance. This work provides critical insights into existing literature pertaining to ICP artifact management as it highlights holes in the literature that need to be adequately addressed in the establishment of robust artifact management methodologies.
Keywords: artifact management; bio-signal analysis; cerebral hemodynamic monitoring; intracranial pressure.
Creative Commons Attribution license.
Similar articles
-
Artifact Management for Cerebral Near-Infrared Spectroscopy Signals: A Systematic Scoping Review.Bioengineering (Basel). 2024 Sep 18;11(9):933. doi: 10.3390/bioengineering11090933. Bioengineering (Basel). 2024. PMID: 39329675 Free PMC article.
-
Artifact removal for intracranial pressure monitoring signals: a robust solution with signal decomposition.Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:797-801. doi: 10.1109/IEMBS.2011.6090182. Annu Int Conf IEEE Eng Med Biol Soc. 2011. PMID: 22254431
-
Characterization of RAP Signal Patterns, Temporal Relationships, and Artifact Profiles Derived from Intracranial Pressure Sensors in Acute Traumatic Neural Injury.Sensors (Basel). 2025 Jan 20;25(2):586. doi: 10.3390/s25020586. Sensors (Basel). 2025. PMID: 39860955 Free PMC article.
-
A supervised, externally validated machine learning model for artifact and drainage detection in high-resolution intracranial pressure monitoring data.J Neurosurg. 2024 Mar 15;141(2):509-517. doi: 10.3171/2023.12.JNS231670. Print 2024 Aug 1. J Neurosurg. 2024. PMID: 38489814
-
Associations between intracranial pressure thresholds and multimodal monitoring in acute traumatic neural injury: a scoping review.Acta Neurochir (Wien). 2023 Jul;165(7):1987-2000. doi: 10.1007/s00701-023-05587-6. Epub 2023 Apr 17. Acta Neurochir (Wien). 2023. PMID: 37067617
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Research Materials