Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics
Respiratory sinus arrhythmia (RSA) is largely mediated by the autonomic nervous system through its modulating influence on the heartbeat. We propose an algorithm for quantifying instantaneous RSA as applied to heart beat interval and respiratory recordings under dynamic respiration conditions. The b...
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| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers
2012
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| Online Access: | http://hdl.handle.net/1721.1/69876 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0002-6166-448X |
| _version_ | 1811096803107405824 |
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| author | Kodituwakku, Sandun Lazar, Sara W. Indic, Premananda Brown, Emery N. Barbieri, Riccardo |
| author2 | Harvard University--MIT Division of Health Sciences and Technology |
| author_facet | Harvard University--MIT Division of Health Sciences and Technology Kodituwakku, Sandun Lazar, Sara W. Indic, Premananda Brown, Emery N. Barbieri, Riccardo |
| author_sort | Kodituwakku, Sandun |
| collection | MIT |
| description | Respiratory sinus arrhythmia (RSA) is largely mediated by the autonomic nervous system through its modulating influence on the heartbeat. We propose an algorithm for quantifying instantaneous RSA as applied to heart beat interval and respiratory recordings under dynamic respiration conditions. The blood volume pressure derived heart beat series (pulse intervals, PI) are modeled as an inverse gaussian point process, with the instantaneous mean PI modeled as a bivariate regression incorporating both past PI and respiration values observed at the beats. A point process maximum likelihood algorithm is used to estimate the model parameters, and instantaneous RSA is estimated by a frequency domain transfer function approach. The model is statistically validated using Kolmogorov-Smirnov (KS) goodness-of-fit analysis, as well as independence tests. The algorithm is applied to subjects engaged in meditative practice, with distinctive dynamics in the respiration patterns elicited as a result. Experimental results confirm the ability of the algorithm to track important changes in cardiorespiratory interactions elicited during meditation, otherwise not evidenced in control resting states. |
| first_indexed | 2024-09-23T16:49:15Z |
| format | Article |
| id | mit-1721.1/69876 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T16:49:15Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | mit-1721.1/698762022-09-29T21:42:55Z Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics Kodituwakku, Sandun Lazar, Sara W. Indic, Premananda Brown, Emery N. Barbieri, Riccardo Harvard University--MIT Division of Health Sciences and Technology Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Brown, Emery N. Brown, Emery N. Lazar, Sara W. Barbieri, Riccardo Respiratory sinus arrhythmia (RSA) is largely mediated by the autonomic nervous system through its modulating influence on the heartbeat. We propose an algorithm for quantifying instantaneous RSA as applied to heart beat interval and respiratory recordings under dynamic respiration conditions. The blood volume pressure derived heart beat series (pulse intervals, PI) are modeled as an inverse gaussian point process, with the instantaneous mean PI modeled as a bivariate regression incorporating both past PI and respiration values observed at the beats. A point process maximum likelihood algorithm is used to estimate the model parameters, and instantaneous RSA is estimated by a frequency domain transfer function approach. The model is statistically validated using Kolmogorov-Smirnov (KS) goodness-of-fit analysis, as well as independence tests. The algorithm is applied to subjects engaged in meditative practice, with distinctive dynamics in the respiration patterns elicited as a result. Experimental results confirm the ability of the algorithm to track important changes in cardiorespiratory interactions elicited during meditation, otherwise not evidenced in control resting states. National Institutes of Health (U.S.) (Grant R01-HL084502) National Institutes of Health (U.S.) (Grant R01-DA015644) National Institutes of Health (U.S.) (Grant DP1-OD003646) 2012-03-28T15:35:14Z 2012-03-28T15:35:14Z 2010-11 2010-09 Article http://purl.org/eprint/type/JournalArticle 978-1-4244-4123-5 1557-170X INSPEC Accession Number: 11650368 http://hdl.handle.net/1721.1/69876 Kodituwakku, S et al. “Point Process Time-frequency Analysis of Respiratory Sinus Arrhythmia Under Altered Respiration Dynamics.” IEEE, 2010. 1622–1625. © Copyright 2010 IEEE. 21096135 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0002-6166-448X en_US http://dx.doi.org/10.1109/IEMBS.2010.5626648 Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009. EMBC 2009 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Institute of Electrical and Electronics Engineers IEEE |
| spellingShingle | Kodituwakku, Sandun Lazar, Sara W. Indic, Premananda Brown, Emery N. Barbieri, Riccardo Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics |
| title | Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics |
| title_full | Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics |
| title_fullStr | Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics |
| title_full_unstemmed | Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics |
| title_short | Point process time-frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics |
| title_sort | point process time frequency analysis of respiratory sinus arrhythmia under altered respiration dynamics |
| url | http://hdl.handle.net/1721.1/69876 https://orcid.org/0000-0003-2668-7819 https://orcid.org/0000-0002-6166-448X |
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