دورية أكاديمية

Blood Pressure Estimation Using Emotion-Based Optimization Clustering Model

التفاصيل البيبلوغرافية
العنوان: Blood Pressure Estimation Using Emotion-Based Optimization Clustering Model
المؤلفون: Vaishali Rajput, Preeti Mulay, Sharnil Pandya, Chandrashekhar Mahajan, Rupali Deshpande
المصدر: Acta Informatica Pragensia, Vol 12, Iss 1, Pp 123-140 (2023)
بيانات النشر: Prague University of Economics and Business, 2023.
سنة النشر: 2023
المجموعة: LCC:Electronic computers. Computer science
مصطلحات موضوعية: audio signals, emotion recognition, enhanced grey wolf spotted hyena optimization, clustering, svm, optimization algorithm, Electronic computers. Computer science, QA75.5-76.95
الوصف: The features of human speech signals and emotional states are used to estimate the blood pressure (BP) using a clustering-based model. The audio-emotion-dependent discriminative features are identified to distinguish individuals based on their speech to form emotional groups. We propose a bio-inspired Enhanced grey wolf spotted hyena optimization (EWHO) technique for emotion clustering, which adds significance to this research. The model derives the most informative and judicial features from the audio signal, along with the person's emotional states to estimate the BP using the multi-class support vector machine (SVM) classifier. The EWHO-based clustering method gives better accuracy (95.59%), precision (97.08%), recall (95.16%) and F1 measure (96.20%), as compared to other methods used for BP estimation. Additionally, the proposed EWHO algorithm gives superior results in terms of parameters such as the silhouette score, Davies-Bouldin score, homogeneity score, completeness score, Dunn index, and Jaccard similarity score.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: Czech
English
Slovak
تدمد: 1805-4951
العلاقة: https://aip.vse.cz/artkey/aip-202301-0009_blood-pressure-estimation-using-emotion-based-optimization-clustering-model.phpTest; https://doaj.org/toc/1805-4951Test
DOI: 10.18267/j.aip.209
الوصول الحر: https://doaj.org/article/a5622b83494f4549a9e8a53ed2d4e883Test
رقم الانضمام: edsdoj.5622b83494f4549a9e8a53ed2d4e883
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:18054951
DOI:10.18267/j.aip.209