The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
A study on the optimum order of autoregressive models for heart rate variability.
Open accessAbstract
Heart rate variability (HRV) has been used as a non-invasive marker of the activity of the autonomic nervous system and its spectrum analysis gives a measure of the sympatho-vagal balance. If short segments are used in an attempt to improve temporal resolution, autoregressive spectral estimation, where the mode] order must be estimated, is preferred. In this paper we compare four criteria for the estimation of the 'optimum' model order for an autoregressive (AR) process applied to short segments of tachograms used for HRV analysis. The criteria used were Akaike's final prediction error, Akaike's information criterion, Parzen's criterion of autoregressive transfer function and Rissanen's minimum description length method, and they were first applied to tachograms to verify (i) the range and distribution of model orders obtained and (ii) if the different techniques suggest the same model order for the same frames. The four techniques were then tested using a true AR process of known order p = 6; this verified the ability of the criteria to estimate the correct order of a true AR process and the effect, on the spectrum, of choosing a wrong model order was also investigated. It was found that all the four criteria underestimate the true AR order; specifying a fixed model order was then looked at and it is recommended that an AR order not less than p = 16, should be used for spectral analysis of short segments of tachograms.
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“The model-order chosen to perform AR should always be indicated (Malik, 1996) and be no shorter than 16 for short-term recordings (Boardman et al., 2002).”
From Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting (2017) · cites this paper as Boardman et al., 2002
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Heart rate variability: A review
Rajendra Acharya, U., Paul Joseph, K., Kannathal, N., Lim, C. M., & Suri, J. S. (2006) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-006-0119-0 · Cited by 2,820
Laborde, S., Mosley, E., & Thayer, J. F. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00213 · Cited by 2,336
“The model-order chosen to perform AR should always be indicated (Malik, 1996) and be no shorter than 16 for short-term recordings (Boardman et al., 2002).”
BackgroundDysautonomia and its underlying mechanisms in the hypermobility type of Ehlers-Danlos syndrome
De Wandele, I., Rombaut, L., Leybaert, L., Van de Borne, P., De Backer, T., Malfait, F., De Paepe, A., & Calders, P. (2014) · Seminars in Arthritis and Rheumatism · doi:10.1016/j.semarthrit.2013.12.006 · Cited by 168
Pichon, A., Roulaud, M., Antoine-Jonville, S., de Bisschop, C., & Denjean, A. (2006) · Journal of Electrocardiology · doi:10.1016/j.jelectrocard.2005.08.001 · Cited by 100
Plaza-Florido, A., Alcantara, J. M. A., Migueles, J. H., Amaro-Gahete, F. J., Acosta, F. M., Mora-Gonzalez, J., Sacha, J., & Ortega, F. B. (2020) · Scientific Reports · doi:10.1038/s41598-020-68197-7 · Cited by 44
Metadata
- Authors
- Boardman, A., Schlindwein, F. S., Rocha, A. P., & Leite, A.
- Affiliations
- University of Leicester (GB)
- Universidade do Porto (PT)
- University of Trás-os-Montes and Alto Douro (PT)
- Venue
- Physiological Measurement
- Publisher
- IOP Publishing
- Published
- 2002-03-08
- Volume
- 23
- Issue
- 2
- Pages
- 325-336
- ISSN
- 0967-3334 (ISSN-L)
- 1361-6579
- OpenAlex
- W2046734432
- Cited by
- 228
- References
- 14
- Citations by year
- 2026: 6 · 2025: 3 · 2024: 4 · 2023: 6 · 2022: 8 · 2021: 7 · 2020: 10 · 2019: 13 · 2018: 18 · 2017: 27 · 2016: 10 · 2015: 18 · 2014: 11 · 2013: 18 · 2012: 13
- FWCI
- 1.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Physiological Measurement (publishedVersion)
- PubMed (publishedVersion)
- Leicester Research Archive (University of Leicester) (submittedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
- Keywords
- heart rate variability, autoregressive model order selection, autoregressive spectral estimation, Akaike information criterion, final prediction error, minimum description length, tachogram, autonomic nervous system, sympathovagal balance, spectral analysis
- MeSH terms
- Adult, Autonomic Nervous System, Heart, Heart Rate, Humans, Models, Cardiovascular
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