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- W2968935211 abstract "The increasing need for comprehensive medical signal data has been scarcely tackled in the scope of non-classical modalities and multimodal signal. To overcome this, a data-driven, statistical approach to model cardiorespiratory signals combined with copulas to emulate inter and intramodality dependence is suggested. Gaussian Mixture Models, Fourier Series and Sum of Sines are fitted to different physiological portions of segmented heart cycles. Marginal distributions of the yielded parameters and their linear correlation are used to define a Gaussian Copula from which random sets of parameters are generated to simulate new beats. The model is applied to regular and capacitively coupled Electrocardiography (ECG-cECG) as well as a combination of ECG with blood pressure and ballistocardiography (ECG-BP-BCG) to demonstrate generation of multimodal recordings. Results show realistic wave morphologies and relevant inter and intramodality correlations with a wide range of potential applications such as testing, training and integrating signal processing algorithms.The increasing need for comprehensive medical signal data has been scarcely tackled in the scope of non-classical modalities and multimodal signal. To overcome this, a data-driven, statistical approach to model cardiorespiratory signals combined with copulas to emulate inter and intramodality dependence is suggested. Gaussian Mixture Models, Fourier Series and Sum of Sines are fitted to different physiological portions of segmented heart cycles. Marginal distributions of the yielded parameters and their linear correlation are used to define a Gaussian Copula from which random sets of parameters are generated to simulate new beats. The model is applied to regular and capacitively coupled Electrocardiography (ECG-cECG) as well as a combination of ECG with blood pressure and ballistocardiography (ECG-BP-BCG) to demonstrate generation of multimodal recordings. Results show realistic wave morphologies and relevant inter and intramodality correlations with a wide range of potential applications such as testing,..." @default.
- W2968935211 created "2019-08-22" @default.
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- W2968935211 date "2019-01-01" @default.
- W2968935211 modified "2023-09-26" @default.
- W2968935211 title "Synthesis of cardiac signals using a Copula-approach" @default.
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- W2968935211 doi "https://doi.org/10.1063/1.5121995" @default.
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