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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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Formato: | Texto |
Lenguaje: | English |
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Springer-Verlag
2006
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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. |
format | Text |
id | pubmed-1820753 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
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 |