Abstract
In aspects, the present approaches allow neural networks to be taught to understand patterns of human behavior without the need of expert data labeling or laboratory studies. First and second neural networks are trained to understand these patterns without labeling. Once trained, the neural networks can be deployed with a trained classifier to determine or classify human activity based upon received sensor inputs.
Full Text
What is claimed is:
In aspects, the present approaches allow neural networks to be taught to understand patterns of human behavior without the need of expert data labeling or laboratory studies. First and second neural networks are trained to understand these patterns without labeling. Once trained, the neural networks can be deployed with a trained classifier to determine or classify human activity based upon received sensor inputs.
Timeline
Filed
06/16/2026Published
10/01/2026Granted
Not AvailableIPC Codes(3)
G06N 3/084:Backpropagation, e.g. using gradient descent
G06N 3/045:Combinations of networks
G16H 10/20:for electronic clinical trials or questionnaires