There are several main problems that we need to solve in order to make this framework happen

a. Human brain signal receiver

This can be done using an upgrading version from current Lie Detector, to use an extra device to obtain all human thought signals.

b. Analogue/Digital Signal Converter and Dominant Signal Filters

These two stages can be done in different orders (convert first, then select or vice versa), the main difficulty lies in the Dominant Signal Filter where we have to select the significant portion of the human thoughts from the chaos of signal pool. This however, can be done using common techniques like Principle Component Analysis (PCA) in selecting the most representative features of the signal, and use Neuron Networks or Support Vector Machine to verify whether the selected features are feasible for a complete thought or sense of human brain.

c. Human thought Understanding and Visualization

This is probably the most difficult part in this framework, there are too many combinations and complication within human's thoughts. However, one of the solution that we can think of is making use of a large database of human thoughts (which is built upon the training process of human thought and obtained signals), the a pattern recognizer can be built upon these training sets, and finally used to recognize new obtained signals.