4th Order Shannon Energy Envelope Approach for Localization of S1 and S2 for Early-Stage Detection of Heart Valve Dysfunction
Notice bibliographique
Résumé
The recent reports of the World Health Organization showed that a huge extent of the population below 55 years has become much prone to cardiac disease, and the death percentage has increased caused by various cardio vascular diseases (CVD).Moreover, in the Covid-19 pandemic situation, the people suffering from heart disease were found severely vulnerable to viral infections, which proved to be a major cause of increased death percentage.The CVD could be caused by dysfunction of heart valves which could end up with cardiac arrest.The prime method for early-stage detection of the heart valve dysfunction is analysis of major heart sounds occurring in a cardiac cycle.The proposed work dealt with exploration of S1 and S2, which are supposed to be prime sounds of Phonocardiogram (PCG) signal.Here, the proposed analysis has six steps.First, signalacquisition set-up which was assembled for acquiring PCG and ECG signals from the people having age between 15 to 40 years.Second step, pre-processing: in which the samples of PCG and ECG signals were prepared and the signal was denoised using modified Butterworth worth filter.The third step was the incorporation of Empirical Mode Decomposition to get Intrinsic Mode Functions i.e., frequency components of the PCG.Further, only two appropriate IMFs were selected and recombined to generate a combined component signal (CChs).In the fourth step; a Modified Shannon Energy Envelope algorithm (MSEE) i.e., 4th order Shannon energy Envelope was implemented to frame energy envelopes.In the fifth step; an adaptive-thresholding was used for the time-lobes formation followed by peak correction algorithm i.e., correction of time-lobe peaks.In the sixth and final step; time-lobes of the PCG signal were computed and were correlated with R-peaks of ECG signal, through which localization of S1 and S2 was done.A total of 40 samples of the PCG signal consisting of 195 cardiac cycles were taken for the analysis.It came out from the analysis of the self-acquired PCG signal that the best result of localization of S1 and S2 is obtained for the PCG signal acquired from the Pulmonic position.After analyzing the confusion matrix for the findings of the proposed method; accuracy & precision were 90.20%, sensitivity 100%, and an error rate of 9.8% was obtained.The accuracy of the method was found lesser if the PCG was acquired from the remaining three auscultation areas of the human chest.The proposed method was compared with three other earlier algorithms, out of which the proposed method showed a greater improvement.Moreover, the implementation of EMD followed by choosing a few specific IMFs for the formation energy envelope reduced the computation cost and enhanced the accuracy of the method, too.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».