A system, method, and computer platform product for an adaptive cognitive training platform. In accordance with various aspects of the present disclosure, an adaptive cognitive training platform is configured to process user activity data from one or more instances of a computerized cognitive training program to determine a baseline cognitive assessment for one or more cognitive abilities/skills of a user. The cognitive assessment model may be configured to further process the user activity data to predict a relative value or measure of efficacy for one or more computerized stimuli or interactions within the computerized cognitive training program. The adaptive cognitive training platform may be configured to configure, modify and/or present one or more graphical user interface elements for one or more subsequent instances of the computerized cognitive training program according to the predicted value or measure of efficacy of one or more cognitive training tasks.

A MRS (magnetic resonance spectroscopy or nuclear magnetic resonance NMR)-based PTSD (post-traumatic stress disorder) and mTBI (mild traumatic brain injury) diagnostic system and method uses MRS signals, already pre-processed by the MRS scanner software. The signals are collected in vivo from specific regions of the brain. A wavelet decomposition is applied to the MRS signals, and the amplitude of the wavelet coefficients and their location in the MRS signals are used as features for training diagnostic classifiers of disease states. These classifiers are identified through analysis of features of individuals whose health status is known. Once the classifiers are trained, patients can be diagnosed by using the same wavelet features extracted from in vivo MRS scans of their brain regions.

The present disclosure concerns methods and systems for improving cognitive performance. More specifically, the disclosure concerns methods and systems for cognitive training under hyperbaric conditions.

A cognitive assessment system includes a computing device, a server coupled to the computing device and an eye tracking device coupled to the computing device. The computing device includes a cognitive assessment program with at least one cognitive assessment task for assessing at least one cognitive function of a user. The server includes a database. The database stores a historical task performance data of the user, a historical task performance model of the user, task performance data of a healthy population, and task performance data of a patient population. The eye tracking device is for capturing the eye movement data of the user.

The present invention includes methods and kits for the diagnosing a neurological disease within primary care settings comprising: obtaining a blood test sample from a subject, measuring IL-7 and TNFα biomarkers in the blood sample, comparing the level of the one or a combination of biomarkers and neurocognitive screening tests with the level of a corresponding one or combination of biomarkers in a normal blood sample and neurocognitive screening tests, and predicting that an increase in the level of the blood test sample in relation to that of the normal blood sample indicates that the subject is likely to have a neurological disease.

The present disclosure provides methods for diagnosing and determining the disease progression of neurodegenerative disorders in patients using neurophysiological biomarkers.

This disclosure relates generally to assessment of cognitive workload using breathing pattern of a person, where cognitive workload is the amount of mental effort required while doing a task. The method and system provides assessment of cognitive workload based on breathing pattern extracted from photoplethysmograph (PPG) signal, which is collected from the person using a wearable device. The PPG signal collected using the wearable device are processed in multiple stages that include breathing signal extraction to extract breathing pattern. The extracted breathing pattern is used for assessment of cognitive workload using a generated personalized training model, wherein the personalized training model is generated and dynamically updated for each person based on selection of a sub-set of breathing pattern features using feature selection and classification techniques that include maximal information coefficient (MIC) techniques. Finally based on personalized training model, the extracted breathing pattern is classified as high cognitive workload or low cognitive workload.

A method of determining if a subject has a mild cognitive impairment (MCI) or Alzheimer's Disease, the method comprising measuring the concentration of one or more VOCs in an exhaled sample from a subject, and comparing the concentration with a reference concentration, I.

A training apparatus is capable of generating and presenting a suitable training menu for finger exercise to maintain or improve a cognitive function and/or an exercise function of a human and supporting training of the human. The training apparatus includes a measuring apparatus and a terminal device. Analysis evaluating data based on measurement of the finger exercise including finger tapping is obtained, and the analysis evaluating data contains an evaluation value of an index item related to an exercise function of a user. A training menu for the user is generated based on the analysis evaluating data and contains a training item for the finger exercise. The index item includes at least one of an amount of exercise, endurance, rhythmicity, cooperativeness of both sides, or marker trackability. The training item includes an exercise to carry out the finger tapping in accordance with teaching information, stimulation, or a marker.

Disclosed herein is a method for diagnosing a neurological disorder based on at least one magnetic resonance imaging (MRI) image. The method includes identifying brain image regions that contain a respective portion of diffusion index values of at least one diffusion index. For each of the brain image regions, a characteristic parameter based on the respective portion of the diffusion index values is calculated. a diagnoses is then made for the brain using one of predetermined categories of the neurological disorder by performing classification on a combination of the characteristic parameters via a classifier.