The present invention is directed to a device and method for monitoring and assessment of movement disorder symptoms. The device and method disclosed herein are particularly amenable to remote monitoring of a subject's movement disorder symptoms. Briefly stated, in certain preferred embodiments of the present invention the movement disorder monitoring device accompanies a subject to a remote location where the device is used to record data relating to the severity of a subject's movement disorder symptoms over a period of time. This data is then subsequently used by physicians or other clinicians in optimizing and assessing treatment options directed at alleviating a subject's movement disorder symptoms. The method and device of the present invention can be used to monitor symptoms of a number of movement disorders including but not limited to dystonia, essential tremor, Huntington's disease, various ataxias, multiple sclerosis, psychogenic tremor, and Parkinson's disease.

The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

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 system for identifying abnormal eye movements includes a near-eye display (NED), an eye-tracking camera, a frame supporting the NED and the eye-tracking camera, and a processor in data communication with the NED, the eye-tracking camera, and a computer readable medium. The computer readable medium has instructions thereon. When executed by the processor, the instructions cause the processor to provide a target on the NED to a user's eye and change the target or move the target to a plurality of locations in three dimensions on the NED according to one or more tasks of a task module. The processor further records positional information and pupil information of the user's eye during the one or more tasks of the task module and compares the positional information to at least one threshold value of an abnormality identification algorithm.

Systems and methods rely on feedback from an active medical device or devices (e.g., neurostimulator coupled to sensing and stimulation elements such as electrodes) to assess the effectiveness of a patient's drug regimen. Such reliance may include analyzing characteristics in physiological data acquired by the medical device(s), for example, in the form of responses evoked from the patient by electrical stimulation waveforms. Systems and methods further involved adjusting one or more parameters according to which a combination therapy consisting of at least a drug regimen and an electrical stimulation therapy are delivered to a patient, in an effort to optimize the therapeutic effect of the combination. The adjustments may be automatically by one or more implanted or external hosts working together or alone, and/or with the input of a physician.

The present invention relates to methods and devices for measuring and/or analysing the movement of a user to analyse the pronation and supination movements periods of a user. In particular, a medical biomarker indicative of a neurodegenerative disease or other disease impacting musculature control is determined. The method begins by receiving motion data from a sensor held or mounted for rotation with a body part of the user during a repeated rotational motion of the body part. The received data are processed to identify the orientation in a frame of reference associated with the sensor of mutually perpendicular primary, secondary, and tertiary axes of rotation for the motion of the body part of the user. The medical biomarker is then extracted by analysing the rotational motion of the body part of the user about at least one of the primary, secondary, and tertiary axes.

In one aspect, the invention comprises an implantable living electrode comprising a substantially cylindrical extracellular matrix core; one or more neurons implanted along or within the substantially cylindrical extracellular matrix core, the one or more neurons including one or more optogenetic or magnetogenetic neurons proximal to a first end of the implantable living electrode.

A computer-implemented method for quantitatively determining a clinical parameter which is indicative of the status or progression of a disease, comprises: providing a distal motor test to a user of a mobile device, the mobile device having a touchscreen display, wherein providing the distal motor test to the user of the mobile device comprises: causing the touchscreen display of the mobile device to display a test image; receiving an input from the touchscreen display of the mobile device, the input indicative of an attempt by a user to place a first finger on a first point in the test image and a second finger on a second point in the test image, and to pinch the first finger and the second finger together, thereby bringing the first point and the second point together; and extracting digital biomarker feature data from the received input wherein, either: (i) the extracted digital biomarker feature data is the clinical parameter, or (ii) the method further comprises calculating the clinical parameter from the extracted digital biomarker feature data.

A system and method for generating a physiological assessment of a user from biomechanical data gathered from the user. The method comprises the steps of acquiring biomechanical data of the user. generating trajectory data of the user using the acquired biomechanical data. classifying the trajectory data into variables of interest data according to a set of key biomechanical features, rejecting variables of interest data that do not fit a pre-determined acceptance criteria. extracting key features of the non-rejected variables of interest data: calculating a current cumulative risk data based on 1) the extracted key features: 2) a user profile covariate data: and 3) the variables of interest data, and generating the physiological assessment of the user using the current cumulative risk data.

Systems and method may be used for interfacing with a patient. Systems may include a plurality of electrodes in electrical communication with a processor. The processor may be configured to receive sense signals from electrodes and to determine the reliability of the received signal. A test tone signal comprising a test tone frequency may be applied, and the magnitude of the test tone frequency may be analyzed in the received signal. If it is determined that the magnitude of the test tone frequency is below a threshold, the system may take action, such as lowering the gain on an amplifier. Stimulation signals may be applied to the patient at a stimulation frequency simultaneously with one or both of receiving sense signals and providing the test tone signal.