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Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals
Manual analysis of human high-resolution colonic manometry data is time consuming, non-standardized and subject to laboratory bias. In this article we present a technique for spectral analysis and statistical inference of quasiperiodic spatiotemporal signals recorded during colonic manometry procedu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905106/ https://www.ncbi.nlm.nih.gov/pubmed/33643057 http://dx.doi.org/10.3389/fphys.2020.605066 |
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author | Wiklendt, Lukasz Costa, Marcello Scott, Mark S. Brookes, Simon J. H. Dinning, Phil G. |
author_facet | Wiklendt, Lukasz Costa, Marcello Scott, Mark S. Brookes, Simon J. H. Dinning, Phil G. |
author_sort | Wiklendt, Lukasz |
collection | PubMed |
description | Manual analysis of human high-resolution colonic manometry data is time consuming, non-standardized and subject to laboratory bias. In this article we present a technique for spectral analysis and statistical inference of quasiperiodic spatiotemporal signals recorded during colonic manometry procedures. Spectral analysis is achieved by computing the continuous wavelet transform and cross-wavelet transform of these signals. Statistical inference is achieved by modeling the resulting time-averaged amplitudes in the frequency and frequency-phase domains as Gaussian processes over a regular grid, under the influence of categorical and numerical predictors specified by the experimental design as a functional mixed-effects model. Parameters of the model are inferred with Hamiltonian Monte Carlo. Using this method, we re-analyzed our previously published colonic manometry data, comparing healthy controls and patients with slow transit constipation. The output from our automated method, supports and adds to our previous manual analysis. To obtain these results took less than two days. In comparison the manual analysis took 5 weeks. The proposed mixed-effects model approach described here can also be used to gain an appreciation of cyclical activity in individual subjects during control periods and in response to any form of intervention. |
format | Online Article Text |
id | pubmed-7905106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79051062021-02-26 Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals Wiklendt, Lukasz Costa, Marcello Scott, Mark S. Brookes, Simon J. H. Dinning, Phil G. Front Physiol Physiology Manual analysis of human high-resolution colonic manometry data is time consuming, non-standardized and subject to laboratory bias. In this article we present a technique for spectral analysis and statistical inference of quasiperiodic spatiotemporal signals recorded during colonic manometry procedures. Spectral analysis is achieved by computing the continuous wavelet transform and cross-wavelet transform of these signals. Statistical inference is achieved by modeling the resulting time-averaged amplitudes in the frequency and frequency-phase domains as Gaussian processes over a regular grid, under the influence of categorical and numerical predictors specified by the experimental design as a functional mixed-effects model. Parameters of the model are inferred with Hamiltonian Monte Carlo. Using this method, we re-analyzed our previously published colonic manometry data, comparing healthy controls and patients with slow transit constipation. The output from our automated method, supports and adds to our previous manual analysis. To obtain these results took less than two days. In comparison the manual analysis took 5 weeks. The proposed mixed-effects model approach described here can also be used to gain an appreciation of cyclical activity in individual subjects during control periods and in response to any form of intervention. Frontiers Media S.A. 2021-02-11 /pmc/articles/PMC7905106/ /pubmed/33643057 http://dx.doi.org/10.3389/fphys.2020.605066 Text en Copyright © 2021 Wiklendt, Costa, Scott, Brookes and Dinning. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Wiklendt, Lukasz Costa, Marcello Scott, Mark S. Brookes, Simon J. H. Dinning, Phil G. Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals |
title | Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals |
title_full | Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals |
title_fullStr | Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals |
title_full_unstemmed | Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals |
title_short | Automated Analysis Using a Bayesian Functional Mixed-Effects Model With Gaussian Process Responses for Wavelet Spectra of Spatiotemporal Colonic Manometry Signals |
title_sort | automated analysis using a bayesian functional mixed-effects model with gaussian process responses for wavelet spectra of spatiotemporal colonic manometry signals |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7905106/ https://www.ncbi.nlm.nih.gov/pubmed/33643057 http://dx.doi.org/10.3389/fphys.2020.605066 |
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