ECG model parameters optimization and space state reconstruction

Lopes, Felipe Rebelo; Gois, Jorge Audrin Morgado de

doi:10.1007/s40430-018-1313-3

Cited by 5 publications

(2 citation statements)

References 36 publications

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“…Moreover, most of the parameters do not have a specific morphological meaning. Other examples of model-based proposals are those by 10 – 13 or 14 . These approaches may be suitable to study some specific questions, but, they are far from being multi-purpose methods.…”

Section: Introductionmentioning

confidence: 99%

The hidden waves in the ECG uncovered revealing a sound automated interpretation method

Rueda

Larriba

Lamela

2021

Sci Rep

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A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P, Q, R, S and T waves plus an error term to account for artifacts in the data which provides a meaningful, physical interpretation of the heart’s electric system. The morphology of each wave is concisely described using four parameters that allow all the different patterns in heartbeats to be characterized and thus differentiated This multi-purpose approach solves such questions as the extraction of interpretable features, the detection of the fiducial marks of the fundamental waves, or the generation of synthetic data and the denoising of signals. Yet the greatest benefit from this new discovery will be the automatic diagnosis of heart anomalies as well as other clinical uses with great advantages compared to the rigid, vulnerable and black box machine learning procedures, widely used in medical devices. The paper shows the enormous potential of the method in practice; specifically, the capability to discriminate subjects, characterize morphologies and detect the fiducial marks (reference points) are validated numerically using simulated and real data, thus proving that it outperforms its competitors.

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Section: Introductionmentioning

confidence: 99%

The hidden waves in the ECG uncovered revealing a sound automated interpretation method

Rueda

Larriba

Lamela

2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Moreover, most of the parameters do not have a specific morphological meaning. Other examples of model-based proposals are those by [10], [11], [12], [13] or [14]. These approaches may be suitable to study some specific questions, but, they are far from being multi-purpose methods.…”

Section: Introductionmentioning

confidence: 99%

The hidden waves in the ECG uncovered: a sound automated interpretation method

Rueda,

Larriba,

Lamela

2020

Preprint

View full text Add to dashboard Cite

A novel approach for analysing cardiac rhythm data is presented in this paper. Heartbeats are decomposed into the five fundamental P , Q, R, S and T waves plus an error term to account for artefacts in the data which provides a meaningful, physical interpretation of the heart's electric system. The morphology of each wave is concisely described using four parameters that allow to all the different patterns in heartbeats be characterized and thus differentiated This multi-purpose approach solves such questions as the extraction of interpretable features, the detection of the fiducial marks of the fundamental waves, or the generation of synthetic data and the denoising of signals. Yet, the greatest benefit from this new discovery will be the automatic diagnosis of heart anomalies as well as other clinical uses with great advantages compared to the rigid, vulnerable and black box machine learning procedures, widely used in medical devices.The paper shows the enormous potential of the method in practice; specifically, the capability to discriminate subjects, characterize morphologies and detect the fiducial marks (reference points) are validated numerically using simulated and real data, thus proving that it outperforms its competitors.

show abstract