Frank vectorcardiographic system from standard 12 lead ECG: An effort to enhance cardiovascular diagnosis

Maheshwari, Sidharth; Acharyya, Amit; Schiariti, Michele; Puddu, Paolo Emilio

doi:10.1016/j.jelectrocard.2015.12.008

Cited by 27 publications

(14 citation statements)

References 47 publications

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“…Apart from the presented solutions, a number of different VCG transformations were tested by other teams, with varying results. Other teams carried out experiments based on affine transform, PCA, or transformation methods based on artificial neural networks that offer even higher accuracy [25,26,27]. These transformations will be a basis for our future research.…”

Section: Discussionmentioning

confidence: 99%

“…They concluded that for subjects with myocardial infarction and healthy control subjects, affine transform provides better accuracy than Dower transform. Maheshwari et al, 2016 [26] showed that principal component analysis (PCA) could also be used for deriving the VCG from ECG. They compared PCA with the inverse Dower transform and the Kors regression transform.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Different Electrocardiography with Vectorcardiography Transformations

Jaroš

Martínek

Danys

2019

Sensors

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This paper deals with transformations from electrocardiographic (ECG) to vectorcardiographic (VCG) leads. VCG provides better sensitivity, for example for the detection of myocardial infarction, ischemia, and hypertrophy. However, in clinical practice, measurement of VCG is not usually used because it requires additional electrodes placed on the patient’s body. Instead, mathematical transformations are used for deriving VCG from 12-leads ECG. In this work, Kors quasi-orthogonal transformation, inverse Dower transformation, Kors regression transformation, and linear regression-based transformations for deriving P wave (PLSV) and QRS complex (QLSV) are implemented and compared. These transformation methods were not yet compared before, so we have selected them for this paper. Transformation methods were compared for the data from the Physikalisch-Technische Bundesanstalt (PTB) database and their accuracy was evaluated using a mean squared error (MSE) and a correlation coefficient (R) between the derived and directly measured Frank’s leads. Based on the statistical analysis, Kors regression transformation was significantly more accurate for the derivation of the X and Y leads than the others. For the Z lead, there were no statistically significant differences in the medians between Kors regression transformation and the PLSV and QLSV methods. This paper thoroughly compared multiple VCG transformation methods to conventional VCG Frank’s orthogonal lead system, used in clinical practice.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of Different Electrocardiography with Vectorcardiography Transformations

Jaroš

Martínek

Danys

2019

Sensors

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“…No entanto, esse método tornou-se inviável devidoà complexidade da configuração dos eletrodos pelo corpo do paciente, que oferece considerável desconforto e requer habilidade para o posicionamento preciso dos mesmos, bem como devido a limitações de hardware traduzidas no custo dos equipamentos [2]. Assim, métodos alternativos de obtenção do VCG…”

Section: Abstract-unclassified

“…A rede neural foi alimentada com as seis combinações possíveis de parâmetros (graus de complexidade das três derivações do VCG) e para cada combinação, um valor de Sensibilidade (Sb), Especificidade (Es) e Acurácia (Ac) foi retornado, caracterizando a classificação entre pacientes saudáveis e infartados. Foram determinados 2 3 dos sinais para a etapa de treino e 1 3 para a etapa de teste, conforme utilizado por Costa et al [4]. Esse processo foi repetido para cada tamanho de bloco definido.…”

Section: Abstract-unclassified

Validação do Vetorcardiograma de Kors pela Identificação de Infarto Agudo do Miocárdio

Silva¹,

Costa²,

Hortegal³

et al. 2018

Anais De XXXVI Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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“…However, prior attempts to synthesize 12-lead ECG or 3-lead VCG from a single lead have not been successful. Most existing lead transformation approaches require at least two synchronously acquired leads [28][29][30][31][32][33][34][35][36][37][38][39][40], hampering their applicability to the present context. This has motivated our investigation into trying to synthesize the 3-lead VCG from single-lead ECG signal.…”

Section: Introductionmentioning

confidence: 99%

Automatic Classification of Myocardial Infarction Using Spline Representation of Single-Lead Derived Vectorcardiography

Chuang

Huang

Chang

et al. 2020

Sensors

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Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases worldwide and most patients suffer from MI without awareness. Therefore, early diagnosis and timely treatment are crucial to guarantee the life safety of MI patients. Most wearable monitoring devices only provide single-lead electrocardiography (ECG), which represents a major limitation for their applicability in diagnosis of MI. Incorporating the derived vectorcardiography (VCG) techniques can help monitor the three-dimensional electrical activities of human hearts. This study presents a patient-specific reconstruction method based on long short-term memory (LSTM) network to exploit both intra- and inter-lead correlations of ECG signals. MI-induced changes in the morphological and temporal wave features are extracted from the derived VCG using spline approximation. After the feature extraction, a classifier based on multilayer perceptron network is used for MI classification. Experiments on PTB diagnostic database demonstrate that the proposed system achieved satisfactory performance to differentiating MI patients from healthy subjects and to localizing the infarcted area.

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Frank vectorcardiographic system from standard 12 lead ECG: An effort to enhance cardiovascular diagnosis

Cited by 27 publications

References 47 publications

Comparison of Different Electrocardiography with Vectorcardiography Transformations

Comparison of Different Electrocardiography with Vectorcardiography Transformations

Validação do Vetorcardiograma de Kors pela Identificação de Infarto Agudo do Miocárdio

Automatic Classification of Myocardial Infarction Using Spline Representation of Single-Lead Derived Vectorcardiography

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