Embodiments may provide multimodal diagnostic systems and methods for detecting neurological disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), depression, PTSD, schizophrenia, dementia and many others. For example, a system for monitoring brain activity may comprise a plurality of sensors, each adapted to monitor a physical or physiological parameter and output a signal representing the monitored physical or physiological parameter, wherein the plurality of sensors includes at least one sensor configured to monitor a brain activity parameter, a data collection device adapted to receive the plurality of signals from the plurality of sensors and to process the signals to form digital data representing the monitored physical or physiological parameters, and a data processing device adapted to process digital data representing the monitored physical or physiological parameters to determine presence of a neurological disorder or condition.

Technologies for providing a cognitive capacity test for autonomous driving include a compute device. The compute device includes circuitry that is configured to display content to a user, prompt a message to the user to turn user’s attention to another activity that needs situational awareness, receive a user response, and analyze the user response to determine an accuracy of the user response and a response time, wherein the accuracy and response time are indicative of a cognitive capacity of the user to assume control of an autonomous vehicle when the autonomous vehicle encounters a situation that the vehicle is unable to navigate.

A novel AI-driven drug-repurposing method, DeepDrug, is used to identify a lead combination of previously FDA-approved drugs to treat AD by targeting the upstream genetic markers along the AD pathology. A three-step methodology is used. First, a heterogeneous biomedical graph is constructed comprising complex and interconnected genes, proteins, and drug information to capture the network characteristics of the AD pathology, considering the expert known associations between different AD pathways and utilizing node weighting and edge weighting and direction. Second, the curated graph is taken as an input to an artificial intelligence (AI)-driven graphical neural network (GNN) framework, with embeddings of drug and gene nodes as the outputs. Third, a drug scoring and selection analysis is conduced to generate the drug-gene scores and identify a lead combination of repurposed AD drug candidates for clinical verification.

It is an object to provide a device for estimating a plurality of mental/nervous system diseases by the voice analysis, the device being capable of estimating either major depression or bipolar disorder. Furthermore, there are provided an estimation device including an extraction means for extracting an acoustic feature amount that is not affected by a location where voices are acquired, and a method for operating the estimation device.

The present invention relates to methods and devices to consolidate memory and/or cognitive functions by monitoring brain rhythms and delivering a stimulus at an appropriate stage of sleep cycle.

Disclosed is a device for providing visual perceptual training including an output module and a controller that controls the output module such that the output module outputs an instruction message informing a trainee of a rule related to visual perceptual training, provides a training session for the visual perceptual training, and stores a result in the training session for evaluating cognitive ability of the trainee, wherein the controller may, in the training session, control the output module such that the output module sequentially displays visual objects, check a type of a response of the trainee, determine whether the checked response is correct according to the rule including the first condition and the second condition based on the attribute of the visual object, the display order of the visual object, and the type of the checked response, and output a feedback indicating that the checked response is correct.

An automated system and method is provided for biotype extraction and biomarker discovery from task-based fMRI imaging data. The system and method may include automatically mapping a localizome, such as a task-condition/contrast/population-specific brain functional localizome, based on fMRI data and automatically selecting and sorting brain regions or brain nodes to produce a subset of functional brain regions or brain nodes. A report may then be generated indicating that the subject has a particular brain circuit pattern of activity and connectivity associated with one or more symptoms of the given mental disorder, treatments, or associated with normal brain functions, based upon the extracted biosignatures by searching for the optimal multivariate classifier with least dimensionality in the brain functional localizome. These biosignatures and biomarkers that reveal hidden, implicit, and latent brain circuit patterns provoked by fMRI tasks, can also provide for the development of non-invasive diagnostics and targeted therapeutics in neuropsychiatric diseases.

Wearable apparatus and method of using same for tracking a labeled probe in a subject are disclosed.

A device is provided for diagnostic measurement by simultaneous multimodal analysis of a subject's head wherein the cerebral blood flow variations as well as the concentration level of oxygenation in the subject's blood are used to determine the presence and the pathophysiology of neurocognitive disorders, including the neurodegenerative disease referred to as Alzheimer's disease.

Apparatus, systems, and methods are provided for generating a quantified indicator of cognitive skills in an individual. In certain configurations, the apparatus, systems, and methods can be implemented for enhancing cognitive skills in an individual.