Today, Electro-Cardiogram (ECG) is considered the most important diagnostic tool in cardiology, because its extremely accuracy to reveal potential pathologic heart activities. In the context of a multi-agent system, where agents provide to monitor the health of patients in a personalized manner on the bases of different embedded modules, we propose a module developed with the aim to prevent possible hearth diseases. It is based on a Radial Basis Neural Network (RBNN) able to analyze the ECG signals and to evaluate the impact of some specific parameters for preventing heart diseases. Index Terms—ECG, Soft Computing, Multi-agent System, Radial Basis Neural Network, Cardiac Diseases.
A Radial Basis Neural Network based agent module exploiting ECG signals to prevent heart diseases / Calcagno, S; LA FORESTA, F.. - 1867:(2017), pp. 78-83. (Intervento presentato al convegno Workshop "From Objects to Agents", WOA 2017 tenutosi a Scilla, Italy nel June 15-15, 2017).
A Radial Basis Neural Network based agent module exploiting ECG signals to prevent heart diseases
CALCAGNO S;LA FORESTA F.
2017-01-01
Abstract
Today, Electro-Cardiogram (ECG) is considered the most important diagnostic tool in cardiology, because its extremely accuracy to reveal potential pathologic heart activities. In the context of a multi-agent system, where agents provide to monitor the health of patients in a personalized manner on the bases of different embedded modules, we propose a module developed with the aim to prevent possible hearth diseases. It is based on a Radial Basis Neural Network (RBNN) able to analyze the ECG signals and to evaluate the impact of some specific parameters for preventing heart diseases. Index Terms—ECG, Soft Computing, Multi-agent System, Radial Basis Neural Network, Cardiac Diseases.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
