Meta-Heuristic Algorithm Enabled Artificial Neural Network for Heart Disease Diagnosis Using IoT Smart Sensors
Bharatwaja Namatherdhala, Jinal Mistry, Vinay Mallikarjunaradhya, J. Logeshwaran
Abstract
This research work presents a meta-heuristic algorithm enabled Artificial Neural Network (ANN) for heart disease diagnosis using Internet of Things (IoT) smart sensors. This proposed system provides real-time heart rate monitoring via tangible wearable's that help in measuring the vital heart parameters. Smartphone-connected sensors continuously measure vital parameters such as heart rate, blood pressure, body temperature and even respiratory rate. Moreover, these sensors are connected to the cloud that helps in providing the necessary computing platform. The collected real-time data at the cloud is fed to a neural network based on the meta-heuristic algorithm to diagnose the severity of the disease or detect any abnormalities. The trained neural network is able to identify patterns from the data and detect the onset of abnormal heart rates or blood pressure parameters leading to a potential heart disease. This proposed system can be useful in providing early detection and diagnosis of heart diseases, and even predict the potential risk factors associated with them helping health care professionals provide proper consultation and treatments. Additionally, the system can be further leveraged to provide better lifestyle practices and modifications to those suffering from heart related diseases.