A new variant of deep belief network assisted with optimal feature selection for heart disease diagnosis using IoT wearable medical devices

Aliyar Vellameeran Fathima; Brindha Thomas

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A new variant of deep belief network assisted with optimal feature selection for heart disease diagnosis using IoT wearable medical devices

机译：A new variant of deep belief network assisted with optimal feature selection for heart disease diagnosis using IoT wearable medical devices

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In this paper, the information related to heart disease using IoT wearable devices is collected from any benchmark site, which is publicly available. With the collected data, feature extraction process is performed initially, in which heart rate, zero crossing rate, and higher order statistical features like standard deviation, median, skewness, kurtosis, variance, mean, peak amplitude, and entropy are extracted. For acquiring most significant features, the optimal feature selection process is implemented. As a novel contribution, the feature selection process is done by the hybrid optimization algorithm called PS-GWO by integrating GWO and PSO. Next, the extracted features are subjected to a famous deep learning algorithm named modified DBN, in which the activation function and number of hidden neurons is optimized using the same developed hybrid algorithm to improve the heart diagnosis accuracy. From the analysis, for the test case 1, the accuracy of the developed PS-GWO-DBN is 60, 52.5, 35 and 35 increased than NN, KNN, SVM, and DBN. For test case 2, the accuracy of the proposed PS-GWO-DBN is 26, 24, 21.6 and 17 increased than NN, KNN, SVM, and DBN, respectively. The accuracy of the designed PS-GWO-DBN is 26 advanced than NN, 24 advanced than KNN, 21.6 advanced than SVM and 17 advanced than DBN for test case 3. Thus, the proposed heart disease prediction model using PS-GWO-DBN performs better than other classifiers.

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《Computer methods in biomechanics and biomedical engineering》 |2022年第4期|387-411|共25页
作者
Aliyar Vellameeran Fathima; Brindha Thomas;
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作者单位

Coll Engn, Dept Comp Applicat, Vadakara, Kerala, India;

Noorul Islam Ctr Higher Educ, Dept Informat Technol, Kanyakumari, Tamil Nadu, India;

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正文语种英语
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关键词
Heart disease diagnosis; internet of things; optimal feature selection; particle swarm-based Grey Wolf optimization; deep belief network;

A new variant of deep belief network assisted with optimal feature selection for heart disease diagnosis using IoT wearable medical devices

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