Method and system for mental performance computing using artificial intelligence and blockchain

Abstract

The present invention generally relates to mental performance monitoring of brain activity that implements computing using blockchain and artificial intelligence technologies. Specifically, this invention relates to creating a blockchain from data obtained from a mental performance monitoring device that measures in real-time the mental activity and applying artificial intelligence machine-learning for pattern recognition of 'best performance' envelope to raise work efficiency, certify cognitive biometric status, detect cerebral microemboli, perform motor, sensory, facial, object and color processing tasks. The invention generally provides a mental status categorization that is implemented using a computer method for accessing, developing and maintaining a decentralized database through a peer-to-peer review network, to preserve the original state of 'best mental performance' envelope data inputs while applying artificial intelligence in a neural network model for pattern recognition of the changing mental states for use in cognitive biometrics, memory assessment, facial recognition, object recognition, language processing, odor recognition, color processing, psychomotor function, cognitive user preferences, task-difficulty, autonomy decision-making levels, and prediction of future actions. The system matches peer-to-peer clusters in a neural network of humans and human-robotic assembly for optimization of efficiency in task performance. The present invention could be applied to assist medical diagnosis through machine-learned models.