..., and calculates the apnea-hypopnea index (AHI). By analyzing the snoring signal in frequency domain, spectral entropy and other frequency-domain features are selected. Finally, the neural network classifier model is established. In the model, the input variables are eight frequency-domain features, and the output...

... features from plantar pressure sensors. The maximum, minimum, and standard deviation of acceleration data were also selected as neural network inputs. To improve the generalization ability of the neural network, Bayesian regularization method was adopted. Experiments were conducted under seven different...

... classifications and neural network algorithms specific to patient clinical case data. The Lyapunov stability implemented with Levenberg–Marquardt model was used to advance DSS learning functional paradigms and algorithms in disease diagnosis to mimic specific patient disease conditions and symptoms. Thus...