The DOI matches its Crossref record; 106 of the 106 references it cites were found in a registry or an index.
Review and classification of variability analysis techniques with clinical applications
Open accessAbstract
Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.
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Cites
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Laborde, S., Mosley, E., & Thayer, J. F. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00213 · Cited by 2,336
“…Article 213 HRV Variables to Assess The first question that the researcher wants to answer is the following: out of the more than 70 variables that can be calculated from HRV analysis (Bravi et al., 2011; Smith et al., 2013a,b) – what are the variables of interest for psychophysiological research?”
Quintana, D. S., Alvares, G. A., & Heathers, J. A. J. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.73 · Cited by 420
Northoff, G., & Lamme, V. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.07.019 · Cited by 247
Statistical considerations for reporting and planning heart rate variability case‐control studies
Quintana, D. S. (2017) · Psychophysiology · doi:10.1111/psyp.12798 · Cited by 192
Ellis, R. J., Zhu, B., Koenig, J., Thayer, J. F., & Wang, Y. (2015) · Physiological Measurement · doi:10.1088/0967-3334/36/9/1827 · Cited by 85
Metadata
- Authors
- Bravi, A., Longtin, A., & Seely, A. J.
- Venue
- BioMedical Engineering OnLine
- Published
- 2011
- Volume
- 10
- Issue
- 1
- Pages
- 90
- ISSN
- 1475-925X (ISSN-L)
- OpenAlex
- W2167263515
- Cited by
- 265
- References
- 106
- FWCI
- 12.71
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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