Most particularly, the present invention relates to a customized and adaptive movement recovery system and a method of improving the functional motor recovery of a subject with a movement disorder. The present invention provides for a system and method, which in some embodiments can accurately quantify treatment device parameters and protocols including electrical stimulation amplitude (volts/amps), frequency (Hz), and pulse width (microseconds), and medication titrations, doses, and times by utilizing accelerometric, gyroscopic or other movement related information, such as electromyography (EMG) data, or the like, and a central database, or system of databases, of patient and treatment histories. In other embodiments, the system and method provide for an adaptive central database system and automated control of movement disorder treatment devices.

A system for overcoming fog (freezing of gait) episodes, comprising an acquisition device/component/or the like of at least one FOG-related motor datum of a subject affected by FOG episodes, said acquisition device/component being mounted on at least one piece of footwear worn by said subject; a detection device/component/or the like, separate from said acquisition device/component, operationally connected to the latter and configured to detect at least one FOG episode depending on at least the detected motor datum; an emission device/component/or the like for emitting at least one sensory stimulus perceivable by said subject as a result of the detection of the FOG episode and which allows the subject to overcome such FOG episode, worn by said subject, and operationally connected to said detection device/component, the latter being configured to signal to said emission device/component the detection of the FOG episode.

Systems and methods for detecting anatomical structures include, for each training subject of a plurality of training subjects, a corresponding MR image, and generating an initial anatomical template based on a first training subject of the plurality of training subjects. A computing device can map MR images of the other training subjects onto a template space by applying a global transformation followed by a local transformation. The computing device can average the mapped MR images with the initial anatomical template to generate a final anatomical template and boundaries of an anatomical structure of interest can be drawn in the final anatomical template. The computing device can fine tune the boundaries using an edge detection algorithm. The final anatomical template can be used to identify boundaries of the anatomical structure(s) of interest automatically (e.g., without human intervention) in non-training subjects.

A method and system for generating a classifier to classify facial images for cognitive disorder in humans. The system comprises receiving a labeled dataset including set of facial images, wherein each of the facial image is labeled depending on whether it represents a cognitive disorder condition; extracting, from each facial image in the set of facial images, at least one learning facial feature indicative of a cognitive disorder; and feeding the extracted facial features into a to produce a machine learning trained model to generate a classifier, wherein the classifier is generated and ready when the trained model includes enough facial features processed by a machine learning model.

A system and method for evaluation, detection, conditioning, and treatment of neurological functioning and conditions which uses data obtained while a person is engaged in simultaneously in a range of primary physical tasks combined with defined types of secondary activity, such as listening, reading, speaking, mathematics, logic puzzles, navigation of a virtual environment, recall of past stimuli, etc. The data from the physical and secondary activities are combined to generate a composite functioning score visualization indicating the relative functioning of areas aspects of neurological functioning; including those in which deficiencies may be present, which are early indicators of possible neurological conditions. Through algorithmic recommendations combined with expert and user input, a conditioning regimen targeting neurological aspects of interest paired with periodic testing allows the user to track their progress in these areas over time.

This disclosure provides methods for diagnosing a cognitive disorder including performing a tactile perception test on a subject, measuring the subject's tactile perception test performance with a microelectromechanical sensor, and performing a cognitive disorder diagnosis on the subject. The tactile perception test may include distinguishing between various shaped and sized objects and selecting a predetermined one. The tactile perception test may include a two-point discrimination test. The tactile perception test may include testing lower extremity coordination. The tactile perception test may include testing upper extremity coordination. The cognitive disorder may include dementia, Alzheimer's, brain trauma, or concussion. The microelectromechanical sensor may include an accelerometer or gyroscope.

A brain stimulation method and system are provided, wherein neuronal signals of a patient are continuously sensed by at least one sensor device and based on the sensed signals, stimulation signals are applied to the patient by at least one stimulation device, wherein the sensed signals are transmitted to a body-external, portable processing device wherein the sensed signals are evaluated, and based on the evaluated signals stimulation control signals are generated and transmitted to the stimulation device where based on the stimulation control signals the stimulation signals are generated.

A method for detecting and alleviating symptoms of a deviating gait disorder in a human patient, includes the steps of: a) continuous registering a person's gait using a sole embedded in the shoes of the patient, the sole comprises at least two pressure sensors in or on the surface of the sole, b) sending information based on a person's gait from the sole to a receiver device, c) analyzing and interpreting the information received by the receiver device in order to detect whether the gait is deviating or not, d) upon detecting a deviating gait, sending single or multiple cues to the patient in order to overcome the deviating gait.

Systems and methods for detecting anatomical structures include, for each training subject of a plurality of training subjects, a corresponding MR image, and generating an initial anatomical template based on a first training subject of the plurality of training subjects. A computing device can map MR images of the other training subjects onto a template space by applying a global transformation followed by a local transformation. The computing device can average the mapped MR images with the initial anatomical template to generate a final anatomical template and boundaries of an anatomical structure of interest can be drawn in the final anatomical template. The computing device can fine tune the boundaries using an edge detection algorithm. The final anatomical template can be used to identify boundaries of the anatomical structure(s) of interest automatically (e g., without human intervention) in non-training subjects.

A system and method for remote monitoring of patient motor functions includes a computing device that uses captured image data depicting a patient's body part and, based on movement information, detects whether a condition may exist that is affecting motor functions. The body part can be a hand that is tracked as the user performs a tapping exercise. The body part can also include the patient's face during speech and also without speech.