Described are novel systems for the diagnosis of specific mental disorders using neurometrics. EEG parameters are compared to thresholds to determine if a person is suffering from autism spectrum disorder, Alzheimer's disease, anxiety, depression, or schizophrenia.

A dynamic neuropsychological assessment tool according to an embodiment utilizes speech recognition, speech synthesis and machine learning to assess whether a patient is at risk for a neurological disorder, such as Alzheimer's disease. The dynamic neuropsychological assessment tool enables self-administration by a patient. The tool performs pre-test validation operations on the test environment, test equipment, and the patient's capability for performing the test at that time. The tool also enables dynamic modification of a questionnaire presented to the patient while the patient completes the questionnaire. Also provides the dynamic modification of which tests to present the patient with. The modification can be rule based or modified by a provider. The dynamic neuropsychological assessment tool enables providers and administrators to modify and improve tests and validate them using machine learning based on previously completed assessments and results.

This disclosure relates to a head-mounted magnetic resonance imaging device. The head-mounted magnetic resonance imaging device includes a head-mounted imaging unit, a controlling computer, and a signal processing computer. The signal processing computer includes a controlling module, a data processing module, an image reconstructing module, an image storing module, and an image comparing module. The image reconstructing module forms cross-sectional scanned images of an user's brain memory showing microstructure. The image comparing module is configured to analyze and comparing the cross-sectional scanned images of the user's brain memory showing microstructure collected at different times so that the controlling computer provided user suggestions corresponding to different judgement results of the image comparing module. The system may comprise a dementia monitoring system that provides users with advisory dementia warnings so users may be advised to seek further medical advice.

A method of determining a cognitive assessment for a subject includes receiving input position data associated with input provided by the subject during a time that the subject is responding to a cognitive test, receiving gaze position data associated with a gaze of the subject during the time that the subject is responding to the cognitive test, and determining a cognitive assessment for the subject based at least in part on the input position data and the gaze position data.

Techniques are described for determining cognitive impairment, an example of which includes accessing a set of epochs of magnetoencephalography (MEG) data of responses of a brain of a test patient to a plurality of auditory stimulus events; processing the set of epochs to identify parameter values one or more of which is based on information from the individual epochs without averaging or otherwise collapsing the epoch data. The parameter values are input into a model that is trained based on the parameters to determine whether the test patient is cognitively impaired.

A functional network analysis system for complex network provided by the present application, includea multi-signal-source measurement unit, a signal decomposition unitand a cross-frequency coupling analysis unit, wherein the multi-signal-source measurement unit, the signal decomposition unitand the cross-frequency coupling analysis unit are connected successively. A method using the functional network analysis system is more suitable for the decomposition of non-linear and non-stationary data in complex networks, and can reflect the dynamic properties of functional network links between different frequency bands in a complex system.

A dementia determination system (100) includes: an acquisition unit (111) configured to acquire a long press ratio which is a ratio of a number of long presses in which a button of an operating device (140) is pressed for a time longer than a reference time, to a number of presses of the button of the operating device (140) used by a user to operate an electric device (130); a determination unit (112) configured to determine a dementia level of the user based on the long press ratio acquired by the acquisition unit (111); and an output unit (113) configured to output dementia information indicating the dementia level determined by the determination unit (112), wherein the determination unit (112) is configured to determine that the dementia level is more severe as the long press ratio is lower.

A computer-implemented method of assessing whether a patent has a condition is provided, including generating a facial landmark on a received input video to define points associated with a region of interest on a face of the patient, defining a period of talking based respective positions of the defined points, during the period of talking, measuring pause frequency, repetitive pattern, and vocabulary variety, without determining or applying semantic information associated with the talking, to generate an aggregate score, and based on the aggregate score, generating a prediction of the patient having the condition associated with the aggregate score.

A non-invasive ocular light-based detection device for detecting Alzheimer's Disease (AD)-associated pathologies in the retina of the eye. The device uses two imaging modalities where one imaging modality guides the particular regions to be interrogated by the second imaging modality. A hyperspectral reflectance imaging unit detects light reflected and/or backscattered off of the retina from a broadband light source, which is used to determine one or more regions of interest. A Raman spectroscopy unit detects light that is re-emitted by the retina by Raman scattering phenomenon from a laser that is targeted onto a region of interest that is determined from hyperspectral reflectance information. The detected information from the hyperspectral reflectance imaging unit and the Raman spectroscopy unit are used to determine the presence of the one or more AD-associated pathologies. The detection device allows for the identification of at-risk populations, diagnosis, and tracking of patient response to treatments.

A method of analyzing an iris image with artificial intelligence to diagnose dementia in real time with a smart phone according to an embodiment of the present invention includes receiving an input image of a user's eye from user equipment; extracting a region of interest (RoI) from the input image to extract an iris; resizing the extracted RoI to a square shape and scaling the RoI; applying a deep neural network to the resized and scaled RoI; detecting a lesional area by applying detection and segmentation to an image acquired by applying the deep neural network; and diagnosing dementia by determining a position of the lesional area through the detection and by determining a shape of the lesional area through the segmentation.