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  • Review Article
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Artefacts in continuous neuromonitoring

Nature Reviews Bioengineering (2026)Cite this article

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Abstract

Continuous neuromonitoring is essential in neurocritical care units, providing real-time insights into dynamic cerebral physiology for patients with neurological conditions, such as stroke and neurotrauma. Multiple modalities such as intracranial pressure, arterial blood pressure and near-infrared spectroscopy enable high-resolution dynamic tracking of cerebral perfusion pressure, and related variables critical for life-saving decisions. However, inherent, commonly unavoidable artefacts obscure insights into patient states and complicate treatment decisions. In this Review, we explore primary sources of artefacts in continuous neuromonitoring modalities, including clinical procedure activities, patient-related physiology, technical equipment properties and environmental factors, and their impacts on data integrity and clinical implications. We discuss emerging artefact management strategies, including domain knowledge and data-driven methods to mitigate impact and enhance data reliability. Additionally, we identify key translational challenges, indications for neurosensor design, harmonization and future artificial intelligence pathways, highlighting the need for robust, automated, real-time artefact management to enable precise, individualized patient care.

Key points

  • Continuous neuromonitoring integrates invasive and non-invasive high-resolution techniques for real-time multimodal assessment of neural function.

  • Continuous neuromonitoring data inherently contain artefacts arising from clinical procedures, patient physiology, technical limitations and environmental factors.

  • Artefacts can cumulatively compound and interactively interfere with clinical interpretation and, potentially, diagnosis and treatment decisions, and prognosis.

  • Effective artefact management requires close clinical collaboration, robust domain knowledge and data-driven methods.

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Fig. 1: Continuous neuromonitoring modalities.
Fig. 2: Mechanisms and primary sources of signal interference in neuromonitoring.
Fig. 3: The impact of artefacts in the clinical workflow.
Fig. 4: Artefact management strategies in continuous neuromonitoring signals.

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Acknowledgements

X.C. thanks the Cambridge Trust and the China Scholarship Council for PhD financial support. S.G. acknowledges the National Natural Science Foundation of China (award ID: 62171014). The authors thank M. Czosnyka for valuable feedback on the structure and content of the manuscript.

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Authors and Affiliations

  1. Brain Physics Laboratory, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK

    Xuhang Chen, Stefan Yu Bögli, Ihsane Olakorede, Wenhao Xu, Erta Beqiri & Peter Smielewski

  2. Department of Neurology and Neurocritical Care Unit, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland

    Stefan Yu Bögli

  3. Department of Engineering, University of Cambridge, Cambridge, UK

    Chenyu Tang & Luigi Giuseppe Occhipinti

  4. School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China

    Shuo Gao

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  1. Xuhang Chen
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Contributions

X.C. researched data, contributed to content discussion, and wrote and edited the manuscript. S.Y.B. and I.O. researched data and contributed to discussion of content. W.X., E.B., C.T., L.G.O., S.G. and P.S. contributed to content discussion. All authors reviewed and approved the final manuscript.

Corresponding authors

Correspondence to Xuhang Chen, Shuo Gao or Peter Smielewski.

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Chen, X., Bögli, S.Y., Olakorede, I. et al. Artefacts in continuous neuromonitoring. Nat Rev Bioeng (2026). https://doi.org/10.1038/s44222-025-00378-3

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