A system and method for scoring movement disorder symptoms comprises a movement measurement data acquisition system and processing comprising an algorithm trained on standardized scores. The movement measuring apparatus may comprise sensors such as accelerometers or gyroscopes or may utilize motion capture and/or machine vision technology or various other methods to measure tremor, bradykinesia, gait and balance disturbances, dyskinesia, or other movement disorders in a subject afflicted with Parkinson's disease, essential tremor or the like. The system outputs a score having an inclusive 0-4 scale that correlates to the UPDRS and MDS-UPDRS, or to a particular component of the movement disorder such as speed, amplitude or rhythm, but has greater resolution and lower variability. In some embodiments, the system is used to provide recommendations for treatment and/or to provide treatment in the form of pharmaceutical drugs and/or electric stimulus as part of a closed-loop system.

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 neuromelanin sensitive magnetic resonance imaging (MRI) technique, method and computer-accessible medium for measuring the extent of, providing a diagnosis of, monitoring the treatment of, assessing novel treatments for, or determining a prognosis related to Parkinson's disease.

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 method for generating an indication for Parkinson's Disease in a subject is disclosed. The method comprises measuring, whilst the subject is awake, air flow in the nose of the subject during a plurality of nasal respirations using a sensor; receiving, by a device, data associated with said air flow measurements received from said sensor; and evaluating at least one respiration parameter received from said data, generating an indication for Parkinson's Disease of the subject based on the at least one respiration parameter.

A method for adjustment of a cognitive testing routine in dependence upon detection of a motor impairment of the patient during performance of the cognitive testing routine. In particular, a workflow for administering a neuropsychological assessment which comprises one or more cognitive tests is adjusted in dependence upon detection of a motor impairment.

Devices, systems, and techniques for analyzing video information to objectively identify patient behavior are disclosed. A system may analyze obtained video information of patient motion during a period of time to track one or more anatomical regions through a plurality of frames of the video information and calculate one or more movement parameters of the one or more anatomical regions. The system may also compare the one or more movement parameters to respective criteria for each of a plurality of predetermined patient behaviors and identify the patient behaviors that occurred during the period of time. In some examples, a device may control therapy delivery according to the identified patient behaviors and/or sensed parameters previously calibrated based on the identified patient behaviors.

Provided herein are, inter alia, methods for identifying subjects suffering from depression that will respond to treatment with an antidepressant.

Provided herein are, inter alia, methods for identifying subjects suffering from depression that will respond to treatment with an antidepressant.

The present disclosure relates to a computer-implemented method for monitoring hand movements of a writing instrument's user, comprising: providing an electromyography sensor on the user's wrist or hand; monitoring hand movements of the user during a writing session with the writing instrument by reading sensors of the writing instrument; monitoring hand muscle activity of the user during the writing session by reading the electromyography sensor; correlating hand motion data and hand muscle data obtained from the monitoring; evaluating the correlated data and classifying the hand movements as normal or abnormal based on at least one of tremor parameters, hypokinetic parameters, and historical data of the user; and providing an indication in case of an abnormal evaluation.