ABSTRACT
The demand for global healthcare systems for human health improvement is ever-growing. The Internet of Things (IoT) has a great impact on all industries in the global market. The Internet of Health Things (IoHT)-based healthcare system makes use of intelligent gateways among sensor networks and the Internet. Effective prediction of heart disease (HD) can be achieved by early diagnosis and treatment. This chapter presents a new IoT wearable–based heart disease diagnosis model. The proposed model gathers the patient details and transmits the data to the health care center. Then, the feature process takes place followed by a deep neural network (DNN)–based classification. The proposed model will effectively predict the presence of HD from the data gathered by the IoT wearable. The effectiveness of the proposed model has been tested using a benchmark data set. The results indicated that the proposed model outperforms the existing models in a significant way. The experimental outcome pointed out that the proposed model reaches a maximum sensitivity, specificity, and F-score.
