{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T12:03:11Z","timestamp":1780056191071,"version":"3.54.0"},"reference-count":145,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T00:00:00Z","timestamp":1675641600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006041","name":"Innovate UK","doi-asserted-by":"publisher","award":["63382"],"award-info":[{"award-number":["63382"]}],"id":[{"id":"10.13039\/501100006041","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Background: As technology becomes more sophisticated, more accessible methods of interpretating Big Data become essential. We have continued to develop Complexity and Entropy in Physiological Signals (CEPS) as an open access MATLAB\u00ae GUI (graphical user interface) providing multiple methods for the modification and analysis of physiological data. Methods: To demonstrate the functionality of the software, data were collected from 44 healthy adults for a study investigating the effects on vagal tone of breathing paced at five different rates, as well as self-paced and un-paced. Five-minute 15-s recordings were used. Results were also compared with those from shorter segments of the data. Electrocardiogram (ECG), electrodermal activity (EDA) and Respiration (RSP) data were recorded. Particular attention was paid to COVID risk mitigation, and to parameter tuning for the CEPS measures. For comparison, data were processed using Kubios HRV, RR-APET and DynamicalSystems.jl software. We also compared findings for ECG RR interval (RRi) data resampled at 4 Hz (4R) or 10 Hz (10R), and non-resampled (noR). In total, we used around 190\u2013220 measures from CEPS at various scales, depending on the analysis undertaken, with our investigation focused on three families of measures: 22 fractal dimension (FD) measures, 40 heart rate asymmetries or measures derived from Poincar\u00e9 plots (HRA), and 8 measures based on permutation entropy (PE). Results: FDs for the RRi data differentiated strongly between breathing rates, whether data were resampled or not, increasing between 5 and 7 breaths per minute (BrPM). Largest effect sizes for RRi (4R and noR) differentiation between breathing rates were found for the PE-based measures. Measures that both differentiated well between breathing rates and were consistent across different RRi data lengths (1\u20135 min) included five PE-based (noR) and three FDs (4R). Of the top 12 measures with short-data values consistently within \u00b1 5% of their values for the 5-min data, five were FDs, one was PE-based, and none were HRAs. Effect sizes were usually greater for CEPS measures than for those implemented in DynamicalSystems.jl. Conclusion: The updated CEPS software enables visualisation and analysis of multichannel physiological data using a variety of established and recently introduced complexity entropy measures. Although equal resampling is theoretically important for FD estimation, it appears that FD measures may also be usefully applied to non-resampled data.<\/jats:p>","DOI":"10.3390\/e25020301","type":"journal-article","created":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T05:29:05Z","timestamp":1675661345000},"page":"301","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Complexity and Entropy in Physiological Signals (CEPS): Resonance Breathing Rate Assessed Using Measures of Fractal Dimension, Heart Rate Asymmetry and Permutation Entropy"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2199-2091","authenticated-orcid":false,"given":"David","family":"Mayor","sequence":"first","affiliation":[{"name":"School of Health and Social Work, University of Hertfordshire, Hatfield AL10 9AB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tony","family":"Steffert","sequence":"additional","affiliation":[{"name":"MindSpire, Napier House, 14\u201316 Mount Ephraim Rd., Tunbridge Wells TN1 1EE, UK"},{"name":"School of Life, Health and Chemical Sciences, STEM, Walton Hall, The Open University, Milton Keynes MK7 6AA, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6427-2385","authenticated-orcid":false,"given":"George","family":"Datseris","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, University of Exeter, North Park Road, Exeter EX4 4QF, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1206-504X","authenticated-orcid":false,"given":"Andrea","family":"Firth","sequence":"additional","affiliation":[{"name":"University Campus Football Business, Wembley HA9 0WS, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepak","family":"Panday","sequence":"additional","affiliation":[{"name":"School of Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harikala","family":"Kandel","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Systems, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9448-8902","authenticated-orcid":false,"given":"Duncan","family":"Banks","sequence":"additional","affiliation":[{"name":"School of Life, Health and Chemical Sciences, STEM, Walton Hall, The Open University, Milton Keynes MK7 6AA, UK"},{"name":"Department of Physiology, Busitema University, Mbale P.O. Box 1966, Uganda"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12938-019-0650-5","article-title":"EZ Entropy: A Software Application for the Entropy Analysis of Physiological Time-Series","volume":"18","author":"Li","year":"2019","journal-title":"Biomed. Eng. Online"},{"key":"ref_2","unstructured":"Azami, H., Faes, L., Escudero, J., Humeau-Heurtier, A., and Silva, L.E.V. (2020). 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