At what data length do cerebral autoregulation measures stabilise?
Journal
Physiological Measurement
Journal Volume
38
Journal Issue
7
Pages
1396-1404
Date Issued
2017
Author(s)
Abstract
Objective: Cerebral autoregulation is commonly assessed through mathematical models that use non-invasive measurements of arterial blood pressure and cerebral blood flow velocity. There is no agreement in the literature as to what is the minimum length of data needed for the cerebral autoregulation coefficients to stabilise. Approach: We introduce a simple empirical tool for studying the minimum length of time series needed to parameterise three popular cerebral autoregulation coefficients ARI, Mx and Phase (in the low frequency range [0.07-0.2] Hz), which can be easily applied in a more general context. We use our recently collected data, from which we select high quality (absence of non-physiological artefacts), baseline ABP-CBFV time series (16 min each). The data were beat-to-beat averaged and downsampled at 10 Hz. Main result: On average, ARI exhibits greater variability than Mx and Phase, when calculated for short intervals; however, it stabilises fastest. Significance: Our results show that values of ARI, Mx and Phase calculated on intervals shorter than 3 min (1800 samples), 6 min (3600 samples) and 5 min (3000 samples), respectively, may be very sensitive to changes in the length of data interval. ? 2017 Institute of Physics and Engineering in Medicine.
Subjects
Blood pressure
Blood vessels
Flow velocity
Arterial blood pressure
Cerebral autoregulation
Cerebral blood flow
Cerebral blood flow velocities
Data length
Low frequency range
Measurements of
Non- invasive measurements
Simple++
Times series
Time series
artifact
brain
brain circulation
female
homeostasis
human
male
metabolism
statistics
time factor
vascularization
young adult
Artifacts
Brain
Cerebrovascular Circulation
Female
Homeostasis
Humans
Male
Statistics as Topic
Time Factors
Young Adult
SDGs
Type
journal article