A method and device for predicting Alzheimer's disease based on voice characteristics are provided. The device for predicting Alzheimer's disease according to an embodiment includes: a voice input unit configured to generate a voice sample by recording a voice of a subject; a data input unit configured to receive demographic information of the subject; a voice characteristic extraction unit configured to extract voice characteristics from the generated voice sample; and a prediction model that is pre-trained to predict presence or absence of Alzheimer's disease in the subject, based on the voice characteristics and the demographic information.

An apparatus for providing information about a user's brain resources is provided. The apparatus includes at least sensor interface circuitry and processing circuitry coupled to the sensor interface circuitry. In a calibration mode, the sensor interface circuitry is configured to receive first sensor data from an electroencephalography sensor. The first sensor data are indicative of an electroencephalogram of the user. Further, the sensor interface circuitry is configured to receive second sensor data from a physiological sensor in the calibration mode. The second sensor data are indicative of a physiological property of the user. In the calibration mode, the processing circuitry is configured to train a brain-physiological model for the user based on the first sensor data and the second sensor data.

A device includes: a wireless power receiver configured to receive wireless power from an external device external to a body; a capacitor configured to store therein the wireless power received by the wireless power receiver; a wireless transceiver configured to transmit, to the external device, information associated with stored energy of the capacitor and scheduled energy to be used; and a processor configured to operate with the stored energy of the capacitor and process a biosignal of the body, wherein an operation of the external device and an operation of the device are synchronized, and a wireless power quantity of the wireless power to be received by the wireless power receiver from the external device is determined based on the information transmitted from the wireless transceiver to the external device.

The present invention relates to a digital content-based method for providing therapeutics information, the method comprising: a first step of performing stimulation on a brain of a user to obtain fNIRS (functional near-infrared spectroscopy) data of the user; a second step of extracting a first brain activation area from a plurality of brain areas of the user using the obtained fNIRS data; a third step of determining a first brain state of the user, based on the first brain activation area; a fourth step of providing the user with a content determined corresponding to the first brain state determined in the third step under an XR (Extended Reality) environment; a fifth step in which the user performs a mission corresponding to the content; a sixth step of extracting a second brain activation area from the plurality of brain areas with reference to the fNIRS data of the user following performing the mission; and a seventh step of determining a second brain state of the user, based on the second brain activation area; an eighth step of determining information related to amelioration of the brain state of the user.

Methods and systems for analyzing brain functional activity data are provided. Also provided are systems that find use in performing the present methods.

A processing device receives signals associated with nerve impulses that are transmitted to the visual cortex of a subject in response to one or more visual stimuli provided to at least one eye of the subject. The processing device processes the received signals and generates digital image data from the processed received signals that is representative of the visual perception, by the subject, of the one or more visual stimuli. In certain embodiments, the processing device processes digital image data that is representative of a scene to convert the digital image data to a sequence of nerve impulses, and provides the sequence of nerve impulses to the visual cortex of a subject such that the subject visually perceives the scene.

Brain computer interface BCI comprising an input adapted to be connected to at least one electroencephalography EEG sensor to receive EEG signals, the BCI further comprising a processor running an associative model trained to simulate electrocorticography ECoG signal features from EEG signals received via the input, the BCI comprising an output to transmit the simulated ECoG signal features.

Dysglycemia as a risk factor for neurodevelopmental disorder or developmental diabetes. The risk is assessed based on measurement of a glucose control indicator in a blood sample. One particular example of a neurodevelopmental disorder is retinopathy of prematurity in an infant. One particular example of a glucose control indicator is ‘comprehensive glycated hemoglobin fraction’ or ‘comprehensive glycated albumin fraction.’ This is calculated using ‘total whole blood protein’ in the denominator. In the case of chronic hyperglycemia, there is an increased risk of proliferative retinopathy of prematurity. In the case of chronic hypoglycemia, there is an increased risk of non-proliferative retinopathy of prematurity. This ‘total whole blood protein’ technique could also be used to determine the glucose control status in other types of patients.

A computer-implemented method for voxelizing a 3D structural medical image of a human's brain. The method including obtaining a 3D structural medical image of the human's brain, including a reference frame, generating a voxelized 3D structural medical image, obtaining parameters of at least one EEG electrode sensor and, for each EEG electrode sensor: a localization in the voxelized 3D structural medical image's reference frame, and a sensor detection distance, obtaining a regular 3D grid of voxels, and for each voxel of the 3D grid, iteratively subdividing the voxel while the distance between the voxel and the localization of any electrode sensor is smaller than or equal to the sensor detection distance and while a size of the voxel is greater than a predetermined length, each subdivided voxel joining a finite number of voxels of the voxelized 3D structural medical image.

Systems and methods of the present disclosure are directed to neural stimulation via non-invasive sensory stimuli. The non-invasive sensory stimuli can reduce neuroinflammation, improving synaptic plasticity and stimulating neural networking, and improving microglial-mediated clearance of cerebral insults, which would otherwise contribute to the progression of brain atrophy, by inducing synchronized gamma oscillations in at least one region of a brain in a subject. Stimulations can adjust, control or otherwise manage the frequency of the neural oscillations to provide beneficial effects to one or more cognitive states or cognitive functions of the brain, while mitigating or preventing adverse consequences on a cognitive state or cognitive function that stem from progression of brain atrophy.