The present disclosure relates to a method and a system for detecting a neurological disease and an eye gaze-pattern abnormality related to the neurological disease of a user. The method comprises displaying stimulus videos on a screen of an electronic device and simultaneously filming with a camera of the electronic device to generate a video of the user's face for each one of the stimulus videos, each one of the stimulus videos corresponding to a task. The method further comprises providing a machine learning model for gaze predictions, generating the gaze predictions for each video frame of the recorded video, and determining features for each task to detect the neurological disease using a pre-trained machine learning model.

The present invention relates to a method for predicting neurodegenerative decline and/or its severity for a patient, especially of cognitive impairment (CI). Strokes and Parkinson's disease are frequently associated with occurrence of long-term cognitive impairment or dementia with still incompletely resolved mechanisms. The discovery of diagnostic and predictive biomarkers thus remains a major challenge. The method of the invention uses radiomics corresponding to texture features extracted from a plurality of previously-acquired medical brain images and correlated with previously-acquired clinical and/or biological data. A classifier is trained beforehand for learning these radiomics, and then operated on radiomics computed from at least one brain image of a patient to generate a score representative of its risks of neurodegenerative decline. By applying this method on a cohort of 160 MCI and non-MCI patients, the inventors show that MCI patients could be early predicted with a mean accuracy of 88%. In the same way, the method was able to discriminate very early stages of cognitive decline in a Parkinson's disease population of 100 patients.

A signal processing apparatus and a signal processing method are provided. The signal processing apparatus includes a memristor array, an input circuit, a first switching circuit, a second switching circuit, an output circuit, and a control circuit. The memristor array includes memristor units and is connected to source lines, word lines and bit lines. The control circuit is configured to control the first switching circuit to select at least one source line to apply at least one first signal to the at least one source line respectively, control the second switching circuit to select and activate at least one word line to apply the at least one first signal to a memristor unit corresponding to the at least one word line, and control the output circuit to output a plurality of second signals based on conductivity values of memristors of the memristor array.

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

Methods and systems useful for detecting neurological disorders and for measuring general cognitive performance, in particular by measuring eye movements and/or pupil diameter during eye-movement tasks.

The invention generally relates to motion analysis systems and methods of use thereof. In certain aspects, the system includes an image capture device, at least one accelerometer, and a central processing unit (CPU) with storage coupled thereto for storing instructions that when executed by the CPU cause the CPU to receive a first set of motion data from the image capture device related to at least one joint of a subject while the subject is performing a task and receive a second set of motion data from the accelerometer related to the at least one joint of the subject while the subject is performing the task. The CPU also calculates kinematic and/or kinetic information about the at least one joint of a subject from a combination of the first and second sets of motion data, and outputs the kinematic and/or kinetic information for purposes of assessing a movement disorder.

Cognitive function evaluation system (100) includes motion detector (20), answer detector (30), and evaluator (40). Motion detector (20) generates frames representing three-dimensional coordinates of joints of subject (SJ) who is performing a predetermined task. The predetermined task includes a physical task and a cognitive task that requires subject (SJ) to answer questions on a cognitive examination. Motion detector (20) capture images of subject (SJ) to generate the frames. The frames are a series of frames generated in time order. Answer detector (30) detects answers to questions on the cognitive examination by subject (SJ). Evaluator (40) outputs motion features based on the frames and evaluates a cognitive function of subject (SJ) based on the motion features and the answers by subject (SJ). The motion features represent a feature of a spatial positional relationship and a feature of temporal variations, of the joints of subject (SJ) in the captured images.

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 system and method for tuning the parameters of a therapeutic medical device comprises a movement measurement data acquisition system capable of wireless transmission; processing comprising kinematic feature extraction, a scoring algorithm trained using scores from expert clinicians, a therapeutic device parameter setting adjustment suggestion algorithm preferably trained using the parameter setting adjustment judgments of expert clinicians; and a display and/or means of updating the parameter settings of the treatment device. The invention facilitates the treatment of movement disorders including Parkinson's disease, essential tremor and the like by optimizing deep brain stimulation (DBS) parameter settings, eliminating as much as possible motor symptoms and reducing time and costs of surgical and outpatient procedures and improving patient outcomes. In preferred embodiments, the system provides recommendations for treatment which may be semi-automatically or automatically applied to update the parameter settings of a treatment device such as a DBS implant.

This invention provides a method for treating or for reducing ambulatory deterioration in a human patient diagnosed to be afflicted with relapsing-remitting multiple sclerosis (RRMS) and having a high baseline disability score according to the Kurtzke Expanded Disability Status Scale (EDSS), comprising periodically administering to only the patient diagnosed with RRMS and having a high baseline disability score an amount of laquinimod effective to treat the patient or to reduce ambulatory deterioration. This invention further provides pharmaceutical compositions and packages comprising an effective amount of laquinimod for treating a human patient diagnosed to be afflicted with RRMS and having a high baseline disability score according to the EDSS.