Novel multiscale E-metric cross-sample entropy-based cardiac arrhythmia detection and its performance investigation in reference to multiscale cross-sample entropy-based analysis

Sharma, Kanchan; Sunkaria, Ramesh Kumar

doi:10.1007/s11760-023-02503-4

Cited by 7 publications

(2 citation statements)

References 42 publications

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“…In recent years, the proliferation of network distance computation with increased mathematical assumptions has laid a solid foundation for graph-based network analysis. Indeed, network distance calculations not only be applied directly to networks, but also be employed to measure the distinction between two data sets, similar to the role of KL divergence, Wasserztein distance or cross entropy (see Al-Jarrah et al [7] and Sharma and Sunkaria [8]). This is because a graph or network framework is instructive for irregular/structured data, and by merging the network with the metric space, network distance facilitates to characterize the gap between two data structures or data sets.…”

Section: Introductionmentioning

confidence: 99%

Ratio-based distortion and network distance

Gao,

Wang,

Zhang

2024

Preprint

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Due to the prevalent theoretical status and high-performance efficiency in computer networks, face recognition, and heterogeneous data analysis, network distance has received mass attention and become an emerging technology in recent years. It is noted that the original difference-based network distance is incompetent to describe the network discrepancy by proportionally expanding/contracting the weight function. To mitigate this shortcoming, this paper proposes ratio-based distortion and network distance, and defines a proportional strong/weak isomorphism which is compatible with the new setting. Several results with theoretical underpinning are deduced by means of mathematical analysis approaches. Additionally, this paper conducts a similarity analysis experiment on a randomly generated network structure dataset using the proposed network distance formula. The analysis of the experimental results, including the corresponding hierarchical clustering diagrams and heatmaps, indicates that the proposed network distance formula has practical application value. The code and data of this paper are completely public at https://github.com/AizhEngHN/Ratio-based-distortion-and-network-distance. 2010 Mathematics Subject Classification: 68T09, 54E35.

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Section: Introductionmentioning

confidence: 99%

Ratio-based distortion and network distance

Gao,

Wang,

Zhang

2024

Preprint

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“…A phenomenon of entropy measures is associated with its ability to characterize the rate of creation of valuable information in a dynamical system, identifying the level of uncertainty or the possibility of an indirect description of the number of available states, which can have a direct impact on many biological aspects [ 10 ]. The different kinds of entropy measures, in the forms of Shannon, Kolmogorov, approximate, or sample entropy, are involved in the analysis of electrophysiological signals, including cardiac rate variability [ 11 , 12 ], electromyography (EMG) [ 13 ], and electroencephalography (EEG) [ 14 ], to name but a few.…”

Section: Introductionmentioning

confidence: 99%

Non-Monotonic Complexity of Stochastic Model of the Channel Gating Dynamics

Machura

Wawrzkiewicz-Jałowiecka

Richter

et al. 2023

Entropy

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The simple model of an ionic current flowing through a single channel in a biological membrane is used to depict the complexity of the corresponding empirical data underlying different internal constraints and thermal fluctuations. The residence times of the channel in the open and closed states are drawn from the exponential distributions to mimic the characteristics of the real channel system. In the selected state, the dynamics are modeled by the overdamped Brownian particle moving in the quadratic potential. The simulated data allow us to directly track the effects of temperature (signal-to-noise ratio) and the channel’s energetic landscape for conformational changes on the ionic currents’ complexity, which are hardly controllable in the experimental case. To accurately describe the randomness, we employed four quantifiers, i.e., Shannon, spectral, sample, and slope entropies. We have found that the Shannon entropy predicts the anticipated reaction to the imposed modification of randomness by raising the temperature (an increase of entropy) or strengthening the localization (reduction of entropy). Other complexity quantifiers behave unpredictably, sometimes resulting in non-monotonic behaviour. Thus, their applicability in the analysis of the experimental time series of single-channel currents can be limited.

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A Fault Diagnosis Method for Rolling Bearing Combining Signal Difference and Coarse Graining

Yu,

Li,

et al. 2024

J Fail. Anal. and Preven.

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Novel multiscale E-metric cross-sample entropy-based cardiac arrhythmia detection and its performance investigation in reference to multiscale cross-sample entropy-based analysis

Cited by 7 publications

References 42 publications

Ratio-based distortion and network distance

Ratio-based distortion and network distance

Non-Monotonic Complexity of Stochastic Model of the Channel Gating Dynamics

A Fault Diagnosis Method for Rolling Bearing Combining Signal Difference and Coarse Graining

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