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Algorithm for the classification of multi-modulating signals on the electrocardiogram

This article discusses the algorithm to measure electrocardiogram (ECG) and respiration simultaneously and to have the diagnostic potentiality for sleep apnoea from ECG recordings. The algorithm is composed by the combination with the three particular scale transform of a(j)(t), u(j)(t), o(j)(a(j))...

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Detalles Bibliográficos
Autor principal: Mita, Mitsuo
Formato: Texto
Lenguaje:English
Publicado: Springer-Verlag 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1820753/
https://www.ncbi.nlm.nih.gov/pubmed/17146692
http://dx.doi.org/10.1007/s11517-006-0130-5
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author Mita, Mitsuo
author_facet Mita, Mitsuo
author_sort Mita, Mitsuo
collection PubMed
description This article discusses the algorithm to measure electrocardiogram (ECG) and respiration simultaneously and to have the diagnostic potentiality for sleep apnoea from ECG recordings. The algorithm is composed by the combination with the three particular scale transform of a(j)(t), u(j)(t), o(j)(a(j)) and the statistical Fourier transform (SFT). Time and magnitude scale transforms of a(j)(t), u(j)(t) change the source into the periodic signal and τ(j) = o(j)(a(j)) confines its harmonics into a few instantaneous components at τ(j) being a common instant on two scales between t and τ(j). As a result, the multi-modulating source is decomposed by the SFT and is reconstructed into ECG, respiration and the other signals by inverse transform. The algorithm is expected to get the partial ventilation and the heart rate variability from scale transforms among a(j)(t), a(j+1)(t) and u(j+1)(t) joining with each modulation. The algorithm has a high potentiality of the clinical checkup for the diagnosis of sleep apnoea from ECG recordings.
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spelling pubmed-18207532007-03-12 Algorithm for the classification of multi-modulating signals on the electrocardiogram Mita, Mitsuo Med Biol Eng Comput Original Article This article discusses the algorithm to measure electrocardiogram (ECG) and respiration simultaneously and to have the diagnostic potentiality for sleep apnoea from ECG recordings. The algorithm is composed by the combination with the three particular scale transform of a(j)(t), u(j)(t), o(j)(a(j)) and the statistical Fourier transform (SFT). Time and magnitude scale transforms of a(j)(t), u(j)(t) change the source into the periodic signal and τ(j) = o(j)(a(j)) confines its harmonics into a few instantaneous components at τ(j) being a common instant on two scales between t and τ(j). As a result, the multi-modulating source is decomposed by the SFT and is reconstructed into ECG, respiration and the other signals by inverse transform. The algorithm is expected to get the partial ventilation and the heart rate variability from scale transforms among a(j)(t), a(j+1)(t) and u(j+1)(t) joining with each modulation. The algorithm has a high potentiality of the clinical checkup for the diagnosis of sleep apnoea from ECG recordings. Springer-Verlag 2006-12-05 2007-03 /pmc/articles/PMC1820753/ /pubmed/17146692 http://dx.doi.org/10.1007/s11517-006-0130-5 Text en © International Federation for Medical and Biological Engineering 2006
spellingShingle Original Article
Mita, Mitsuo
Algorithm for the classification of multi-modulating signals on the electrocardiogram
title Algorithm for the classification of multi-modulating signals on the electrocardiogram
title_full Algorithm for the classification of multi-modulating signals on the electrocardiogram
title_fullStr Algorithm for the classification of multi-modulating signals on the electrocardiogram
title_full_unstemmed Algorithm for the classification of multi-modulating signals on the electrocardiogram
title_short Algorithm for the classification of multi-modulating signals on the electrocardiogram
title_sort algorithm for the classification of multi-modulating signals on the electrocardiogram
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1820753/
https://www.ncbi.nlm.nih.gov/pubmed/17146692
http://dx.doi.org/10.1007/s11517-006-0130-5
work_keys_str_mv AT mitamitsuo algorithmfortheclassificationofmultimodulatingsignalsontheelectrocardiogram