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How measurement artifacts affect cerebral autoregulation outcomes: A technical note on transfer function analysis.

Aisha S S Meel-van den Abeelen¹, Daan L K de Jong², Joep Lagro¹

¹Radboud University Medical Centre, Donders institute for Brain Cognition and Behaviour, Radboud Alzheimer Centre, and Department of Geriatric Medicine, Reinier Postlaan 4, 6525 GC, Nijmegen, the Netherlands.

Medical Engineering & Physics

|March 4, 2016

Summary

Measurement artifacts significantly impact cerebral autoregulation (CA) quantification using transfer function analysis (TFA). Signal loss, motion, and drift distort results, highlighting the need for signal quality validation in CA studies.

Keywords:

Cerebral autoregulation Signal-to-noise ratio Transfer function analysis

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Area of Science:

Neuroscience
Physiology
Biomedical Engineering

Background:

Cerebral autoregulation (CA) maintains stable cerebral blood flow despite blood pressure (BP) fluctuations.
Transfer function analysis (TFA) is widely used to assess CA, but exhibits significant inter-study variability.
Measurement artifacts are hypothesized to contribute to the observed variability in TFA outcomes.

Purpose of the Study:

To investigate the impact of specific measurement artifacts on the reliability of TFA metrics for CA assessment.
To identify thresholds for signal loss and types of artifacts that critically affect TFA outcomes.

Main Methods:

Simulated three types of artifacts: signal loss, motion artifacts, and baseline drifts in BP and cerebral blood flow velocity (CBFV) signals.
Compared TFA metrics derived from artifact-free signals with those from simulated artifact-corrupted signals.
Analyzed the influence of artifact severity (e.g., percentage of signal loss) on TFA outcome variability.

Main Results:

High variability in TFA outcomes was observed with >10% BP signal loss or >8% CBFV signal loss.
Presence of motion artifacts significantly distorted TFA results.
Baseline drift impacted TFA interpretation when BP signal power in the LF band was substantial relative to overall BP power.

Conclusions:

Signal loss in BP and CBFV measurements critically affects the interpretation of TFA outcomes for CA.
Motion artifacts and baseline drift also introduce significant distortions.
Rigorous validation of signal quality against defined standards is essential before interpreting TFA-based CA assessments.