Nov 19, 2012 · The proposed BBNN model offers advantages over conventional neural networks by performing the simultaneous optimization of both structure and ...
To implement neural network based monitoring systems, the physiological param- eters of ECG signal, heart rate (HR), corrected QT interval. (QTc) and skin ...
Monitoring systems for diabetes [5] and hypoglycemia [6] have benefitted from IEs and improved the quality of life for people around the world. IEs have ...
This paper represents a review of the researches that combined NN and EC. There are 3 main research focuses as follows. In the first research focus, EC ...
Hypoglycaemia is serious and causes unconsciousness, seizures or even death. The proposed system uses ECG signal for the detection of hypoglycemia. To find the ...
The proposed algorithm, evolvable block based neural network with HPSOWM can successfully detect the hypoglycemia episodes in T1DM in terms of testing ...
The performance of the proposed R-BBNN algorithm was evaluated by an application to the field of medical diagnosis using real hypoglycemia episodes in patients ...
To provide early detection of hypoglycemia episodes, the physiological parameters such as heart rate and corrected QT interval of electrocardiogram (ECG) signal ...
The performance of the proposed R-BBNN algorithm was evaluated by an application to the field of medical diagnosis using real hypoglycemia episodes in patients ...
Missing: Industrial Monitoring
Application study on the detection of hypoglycemic episodes is employed to demonstrate the better performance, which is achieved by proposed R-BBNN. The most ...