Deep Learning Applied to Attractor Images Derived from ECG Signals for Detection of Genetic Mutation

Aston, Philip J.; Lyle, Jane V.; Bonet-Luz, Esther; Huang, Christopher L.‐H.; Zhang, Yanmin; Jeevaratnam, Kamalan; Nandi, Manasi

doi:10.22489/cinc.2019.097

Cited by 12 publications

(14 citation statements)

References 8 publications

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“…Furthermore, we used only basic attractor metrics and elementary machine learning to achieve some very promising results. Extending this work to larger datasets may benefit from more complex techniques, and the use of deep learning on the attractor images directly [15]. We only give a simple example here of a correlation between the changes in an attractor metric and changes in the QTc interval.…”

Section: Discussionmentioning

confidence: 99%

Investigating the Response to Dofetilide with Symmetric Projection Attractor Reconstruction of the Electrocardiogram

Lyle¹,

Aston²,

Nandi³

2019

Computing in Cardiology Conference (CinC)

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The aim of this study is a preliminary investigation into the application of our novel Symmetric Projection Attractor Reconstruction (SPAR) method to the electrocardiogram (ECG) signals of individuals treated with the cardioactive drug dofetilide. We show that our SPAR technique correlates with standard assessment, and is also able to discriminate gender from the ECG response to dofetilide more accurately than the standard metrics.

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Section: Discussionmentioning

confidence: 99%

Investigating the Response to Dofetilide with Symmetric Projection Attractor Reconstruction of the Electrocardiogram

Lyle¹,

Aston²,

Nandi³

2019

Computing in Cardiology Conference (CinC)

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“…The high inter-individual variability of the normal ECG and the numerous factors that are known to impact its appearance ( 16 ) suggest that differences will be subtle and that we need to build up a model from relatively weak predictors. Using this and our previous experience in machine learning on the attractor ( 11 , 12 , 27 ), we started by applying a k -nearest neighbors ( k -NN) algorithm to provide a classification of sex for each measure set (r density, θ density, attractor outline r) for each attractor.…”

Section: Methodsmentioning

confidence: 99%

“…Symmetric Projection Attractor Reconstruction (SPAR) is a method for visualizing and quantifying the morphology and variability of any approximately periodic signal (8)(9)(10), effectively replotting all the underlying data into a simpler two-dimensional representation, which we call an 'attractor'. We have previously applied SPAR to various physiological signals, including the ECG (11,12), arterial blood pressure (8)(9)(10)13) and photoplethysmogram (PPG) (14), where it has been shown to supplement standard cardiovascular assessment.…”

Section: Introductionmentioning

confidence: 99%

Symmetric Projection Attractor Reconstruction: Sex Differences in the ECG

Lyle

Nandi

Aston

2021

Front. Cardiovasc. Med.

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Background: The electrocardiogram (ECG) is a key tool in patient management. Automated ECG analysis supports clinical decision-making, but traditional fiducial point identification discards much of the time-series data that captures the morphology of the whole waveform. Our Symmetric Projection Attractor Reconstruction (SPAR) method uses all the available data to provide a new visualization and quantification of the morphology and variability of any approximately periodic signal. We therefore applied SPAR to ECG signals to ascertain whether this more detailed investigation of ECG morphology adds clinical value.Methods: Our aim was to demonstrate the accuracy of the SPAR method in discriminating between two biologically distinct groups. As sex has been shown to influence the waveform appearance, we investigated sex differences in normal sinus rhythm ECGs. We applied the SPAR method to 9,007 10 second 12-lead ECG recordings from Physionet, which comprised; Dataset 1: 104 subjects (40% female), Dataset 2: 8,903 subjects (54% female).Results: SPAR showed clear visual differences between female and male ECGs (Dataset 1). A stacked machine learning model achieved a cross-validation sex classification accuracy of 86.3% (Dataset 2) and an unseen test accuracy of 91.3% (Dataset 1). The mid-precordial leads performed best in classification individually, but the highest overall accuracy was achieved with all 12 leads. Classification accuracy was highest for young adults and declined with older age.Conclusions: SPAR allows quantification of the morphology of the ECG without the need to identify conventional fiducial points, whilst utilizing of all the data reduces inadvertent bias. By intuitively re-visualizing signal morphology as two-dimensional images, SPAR accurately discriminated ECG sex differences in a small dataset. We extended the approach to a machine learning classification of sex for a larger dataset, and showed that the SPAR method provided a means of visualizing the similarities of subjects given the same classification. This proof-of-concept study therefore provided an implementation of SPAR using existing data and showed that subtle differences in the ECG can be amplified by the attractor. SPAR's supplementary analysis of ECG morphology may enhance conventional automated analysis in clinically important datasets, and improve patient stratification and risk management.

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“…Furthermore, one of the benefits of the attractor method is that it provides a visual representation of the waveform data. In turn, we have commenced deep learning approaches on the attractor images themselves (Aston et al, 2019). This would allow features that are currently missed by the human eye to be detected and could again be used to assist in classification of biologically distinct groups.…”

Section: Conditionsmentioning

confidence: 99%

Extracting new information from old waveforms: Symmetric projection attractor reconstruction: Where maths meets medicine

Nandi

Aston

2020

Experimental Physiology

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New Findings What is the topic of this review?Symmetric Projection Attractor Reconstruction (SPAR) is a relatively new mathematical method that can extract additional information pertaining to the morphology and variability of physiological waveforms, such as arterial pulse pressure. Herein, we describe the potential utility of the method for more sensitive quantification of cardiovascular changes. What advances does it highlight?We use a simple example of a human tilt table to illustrate these concepts. SPAR can be used on any approximately periodic waveform and may add value to experimental and clinical settings, where such signals are collected routinely. Abstract Periodic physiological waveform data, such as blood pressure, pulse oximetry and ECG, are routinely sampled between 100 and 1000 Hz in preclinical research and in the clinical setting from a wide variety of implantable, bedside and wearable monitoring devices. Despite the underlying numerical waveform data being captured at such high fidelity, conventional analysis tends to reside in reporting only averages of minimum, maximum, amplitude and rate, as single point averages. Although these averages are undoubtedly of value, simplification of the data in this way means that most of the available numerical data are discarded. In turn, this may lead to subtle physiological changes being missed when investigating the cardiovascular system over time. We have developed a mathematical method (symmetric projection attractor reconstruction) that uses all the numerical data, replotting and revisualizing them in a manner that allows unique quantification of multiple changes in waveform morphology and variability. We propose that the additional quantification of these features will allow the complex behaviour of the cardiovascular system to be mapped more sensitively in different physiological and pathophysiological settings.

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Deep Learning Applied to Attractor Images Derived from ECG Signals for Detection of Genetic Mutation

Cited by 12 publications

References 8 publications

Investigating the Response to Dofetilide with Symmetric Projection Attractor Reconstruction of the Electrocardiogram

Investigating the Response to Dofetilide with Symmetric Projection Attractor Reconstruction of the Electrocardiogram

Symmetric Projection Attractor Reconstruction: Sex Differences in the ECG

Extracting new information from old waveforms: Symmetric projection attractor reconstruction: Where maths meets medicine

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