A mathematical model may be trained to diagnose a medical condition of a person by processing acoustic features and language features of speech of the person. The performance of the mathematical model may be improved by appropriately selecting the features to be used with the mathematical model. Features may be selected by computing a feature selection score for each acoustic feature and each language feature, and then selecting features using the scores, such as by selecting features with the highest scores. In some implementations, stability determinations may be computed for each feature and features may be selected using both the feature selection scores and the stability determinations. A mathematical model may then be trained using the selected features and deployed. In some implementations, prompts may be selected using computed prompt selection scores, and the deployed mathematical model may be used with the selected prompts.

The present disclosure relates to systems and methods for characterizing a behavior change of a process. A behavior model that can include a set of behavior parameters can be generated based on behavior data characterizing a prior behavior change of a process. A stimulus parameter for a performance test can be determined based on the set of behavior parameters. An application of the performance test to the process can be controlled based on the stimulus parameter to provide a measure of behavior change of the process. Response data characterizing one or more responses associated with the process during the performance test can be received. The set of behavior parameters can be updated based on the response data to update the behavior model characterizing the behavior change of the process. In some examples, the behavior model can be evaluated to improve or affect a future behavior performance of the process.

The purpose of the present invention is to provide a technique whereby multiple projection targets are efficiently identified from multiple neurons in multiple brain areas with the use of multis-point light stimulation. An acquisition unit 52 acquires spike signals generated from multiple neurons existing in the vicinity of two or more recording sites. A stimulation control unit 51 selects one projection target candidate from two or more candidates in accordance with a definite system on the basis of the spike signals and then determines irradiation timing of light stimulation. Upon the light stimulation, a management unit 53 acquires the spike signals in all of the recording sites within a definite period of time before or after the light stimulation, while dividing the spike signals into anti responses and collision responses. An anti response management unit 81 acquires and manages information relating to the anti responses. A collision response management unit 82 acquires and manages information relating to the collision responses. A priority control section 54 corrects and determines priority depending on the anti response information and the collision response information.

An evaluation apparatus includes: a display screen; a gaze point detecting unit that detects a position of a gaze point of a subject observing the display screen; a display control unit that causes the display screen to display an image including a specific object and a comparison object different from the specific object; an area setting unit that sets a specific area corresponding to the specific object and a comparison area corresponding to the comparison object; a determining unit that, based on the position of the gaze point, determines whether the gaze point is present in the specific area and the comparison area during a period in which the image is displayed; a calculating unit that calculates gaze point data based on the determination result of the determining unit; and an evaluating unit that obtains evaluation data of the subject based on the gaze point data.

Systems and methods for use in identifying a brain condition of a subject are provided. In some aspects, a provided method includes constructing a classifier to identify a brain condition of a subject comprising steps of receiving image data obtained from a plurality of subjects, wherein the image data is acquired during an acquisition period following administration of at least one radioactive tracer. The method also includes defining a plurality of brain condition classes using the image data associated with one or more time frames during the acquisition period, and processing the image data to generate signatures corresponding to each of the plurality brain condition classes. The method further includes constructing the classifier using the signatures. The classifier can then be applied to determine a degree to which the subject expresses one or more disease states in order to determine a brain condition of the subject.

A method for non-invasive video oculographic measurement of eye movements as diagnostic support for (early) detection of neuropsychiatric diseases, using an indicator for a visual stimulus and a camera for video recording. A position of the camera is kept constant in relation to the display and a face of a test person is continuously recorded, at least in parts. A recognition algorithm is started which creates an eye template in which an absolute position of the eye and a pupil of the eye are continuously recorded in the image. Furthermore, a reference range, especially around the eye, is defined and, after selecting a predefined measurement paradigm of the pupil are continuously recorded and analyzed at the end of the stimulus.

A home automation (HA) system may include a cloud server, HA operation devices within a senior living facility, and HA user interface devices for respective users within the senior living facility. Each HA user interface device may include a user input device, a display defining a user interface (UI), and a controller. The HA system may include HA hub devices within the senior living facility to provide communications for the cloud server, the HA user interface devices, and the HA operation devices. The controller may send user interaction data to the cloud server and operate the UI according to a user cognitive level. The cloud server may be configured to determine the user cognitive level based upon the user interaction data received from a given HA user interface device, and send the user cognitive level to the given HA user interface device.

Example systems, methods, and apparatus are provided for using data collected from the responses of an individual with the computerized tasks of a cognitive platform to derive performance metrics as an indicator of cognitive abilities, and applying predictive models to generate an indication of a neurodegenerative condition. The example systems, methods, and apparatus also can be configured to adapt the computerized tasks to enhance the individual's cognitive abilities, and for using data collected from the responses of an individual with the adapted computerized tasks to derive performance metrics and applying predictive models to generate the indication of neurodegenerative condition.

A disease, by definition, is an undesired or abnormal state. Diseases are characterized by symptoms that may change during disease progression. But each symptom is underpinned by at least one factor that alters metabolism within cells of the body. Without at least one change in cell activity (metabolism) there would be no symptoms. These metabolic alterations involve modified rates or occurrence of alternate biochemical reactions. Disease-associated patterns of reactions (metabolisms) produce a characterizing or signature pattern of reaction products and byproducts. These metabolites, especially volatile organic metabolites (VOCs), may be assayed using a device of this invention to produce results that indicate a subject's disease or class of diseases and to differentiate between diseases.

Disclosed are a method and an apparatus for rehabilitation training of a cognitive function. A method for rehabilitation training of a cognitive function may comprise the steps of: performing a cognitive function test by a cognitive rehabilitation service server; receiving a cognitive function test result of the cognitive function test by the cognitive rehabilitation service server; determining a rehabilitation method matching the cognitive function test result, by the cognitive rehabilitation service server; and providing a user device with a rehabilitation content according to the rehabilitation method so as to perform rehabilitation training, by the cognitive rehabilitation service server.