An eye-movement data acquisition system includes an illumination source configured to produce infrared light and a camera assembly configured to receive a portion of the infrared light reflected from a user's face during activation of the infrared illumination source. The camera assembly includes a rolling shutter sensor configured to produce individual scan line images associated with the user's eyes at a line sampling rate. A processor is communicatively coupled to the camera assembly and the illumination sources and is configured to produce eye-movement data based on the individual scan line images.

A system and method for scoring movement disorder symptoms comprises a movement measurement data acquisition system and processing comprising kinematic feature extraction and an algorithm trained using Unified Parkinson's Disease Rating Scale (UPDRS) scores from skilled clinicians. The movement data acquisition system, or “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, dyskinesia, or other movement disorders in a subject afflicted with Parkinson's disease, essential tremor or the like. The method outputs, and system displays, a score that uses the same scale as the UPDRS but has greater resolution and lower variability. In some embodiments, the system is used to diagnose and/or treat the patient by providing recommendations for treatment and/or by supplying treatment in the form of pharmaceutical drugs and/or electric stimulus as part of a closed-loop system.

Restless Leg Syndrome (RLS) or Periodic Limb Movement Disorder (PLMD) can be treated using high frequency (HF) electrostimulation. This can include selecting or receiving a subject presenting with RLS or PLMD. At least one electrostimulation electrode can be located at a location associated with at least one of, or at least one branch of, a sural nerve, a peroneal nerve, or a femoral nerve. HF electrostimulation can be delivered to the subject, which can include delivering subsensory, subthreshold, AC electrostimulation at a frequency that exceeds 500 Hz and is less than 15,000 Hz to the location to help reduce or alleviate the one or more symptoms associated with RLS or PLMD. A charge-balanced controlled-current HF electrostimulation waveform can be used.

An exemplary hearing device configured to be worn by a user includes a microphone and a processor. The microphone detects an audio signal. The processor is configured to determine that the audio signal includes own voice content representative of a voice of the user and determine that an environmental noise level within the audio signal is below a threshold The processor is further configured to apply, based on the environmental noise level being below the threshold, a biomarker feature analysis heuristic to the own voice content.

A typing data analysis system may be used to accurately detect early onset of CNS diseases and psychiatric disorders based on typing data. The typing data analysis system may determine typing cadence data and typing error data from typing data captured during normal, everyday typing activities including typing an email, blog, or text message. The typing cadence data and typing error data may be analyzed to determine typing based measures of different CNS diseases and psychiatric disorders. Typing based measures may be continuously determined from a patient's typing activities on the patient's personal computer, smartphone, or other commonly used device to monitor the patient's brain function over time. The typing based measures for the patient may be compared to profiles of CNS diseases and/or psychiatric disorders to screen the patient for a particular disease/disorder.

A wearable gait detection device, a walking ability improvement system and a wearable gait detection system detect manifestation in a brain based on the wearer's gait and preventive measures. A load measurement part measures a load of a sole of the wearer's feet, a foot movement detection part at the shoes detects acceleration and/or angular velocity during feet movement, a centroid position calculation part calculates a centroid position of the feet based on changes in measured load, a movement locus calculation part calculates a movement locus of the feet based on acceleration and/or angular velocity detected by the foot movement detection part, a manifestation recognition part recognizes manifestation in the brain according to a specificity of centroid fluctuation of the feet based on the calculated centroid position and movement locus of the feet, and a sensory output part feeds back a sensation to the wearer based on a recognition result.

The present invention relates to a system for providing neuronal stimulation signals configured to elicit sensory percepts in the cortex of an individual, comprising means for obtaining spatial information relating to the actual or planned position of at least one neuronal stimulation means relative to at least one afferent axon targeting at least one sensory neuron in the cortex of the individual and means for determining at least one neuronal stimulation signal to be applied to at least one afferent axon via the at least one neuronal stimulation means based at least in part on the obtained spatial information. The present invention further relates to a system for communicating conceptual information to an individual, comprising means for selecting at least one neuronal stimulation signal to be applied to at least one afferent axon targeting at least one sensory neuron in the cortex of the individual, wherein the at least one neuronal stimulation signal corresponds to the conceptual information to be communicated and means for transmitting the at least one neuronal stimulation signa to at least one neuronal stimulation means of the individual.

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.

In some embodiments, apparatuses and methods are provided herein useful to digitally measuring, or generating biomarkers. In some embodiments, a system for generating a movement-based biomarker comprises an imaging device configured to generate image data associated with a user, a control system communicatively coupled to the imaging device, the control system configured to identify, in the first image, a feature of the user, determine, in the first image, a first location parameter associated with the feature of the user, identify, in the second image, the feature of the user, determine, in the second image, a second location parameter associated with the feature of the user, calculate, based on the first location parameter associated with the feature of the user and the second location parameter associated with the feature of the user, movement of the feature of the user, and generate, using the movement of the feature of the user, the movement-based biomarker.

Systems and methods for physical therapy and training delivery are presented herein. These technologies may comprise notifying a patient of a scheduled prescribed activity via an on-location at least one client device or console; identifying the patient with one or more sensors connected to or part of the at least one client device or console; confirming, via the at least one client device or console, the patient's acknowledgment of the notification; demonstrating, via a graphical interactive avatar displayed on the at least one client device or console, the prescribed activity to be carried out by the patient; confirming, via the at least one client device or console, that the patient is undertaking or will be undertaking the prescribed activity; capturing, via the one or more sensors, frames of the patient undertaking the prescribed activity; and processing frames of the patient undertaking the prescribed activity.