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.

Methods, devices, and systems are described for closed-loop neuromodulation for control of a physiological state. The system includes an energy application system, a user device, a sensor, and a controller. The controller may be configured to select a state phase based on an engagement component. The controller may be configured to prompt at least one of the user device to present a cue to the subject or the energy application system to apply the electrical stimulation to the subject based on the selected state phase. The controller may be configured to measure the set of physiological reactions induced by the selected state phase. The controller may determine a subject bio-psychiatric therapeutic trajectory based on the measured set of physiological reactions from the subject, the subject bio-psychiatric therapeutic trajectory generated by mapping the set of physiological reactions from the subject to the state phase.

Disclosed is a learning model employed to treat patients with functional impairments due to psychological, mental cognitive or physical disorders or disabilities. The treatment includes accessing at which transition stage of the learning model that a subject has movement transition deficits based on the subject's bio-signals, such as brain state and muscle state signals. The movement transition deficits are addressed so that the subject can attain an upward spiral, accelerating functional recovery or development and avoid a downward spiral towards compensation and slowing down of recovery.

A fitness device gaming controller to be used to control an application running on a host device. The fitness device operates as a normal piece of exercise equipment, with the capability of turning a user's monitored exercise activity and manual controls into standard gaming inputs for use by a gaming device such as a console or computer. Additional devices may be connected to the fitness device, such as additional sensors or smart devices that can provide additional sensors and controls for incorporation into the gaming inputs.

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.

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.

A method for selecting data derived from an electroencephalogram, in the form of a set of starting scalograms, each scalogram being calculated from a portion of an electroencephalographic signal. The method includes: extracting, via an artificial neural network, a set of candidate scalograms; and for some candidate scalograms of the set of candidate scalograms: calculating characteristics of the electroencephalographic signal portion corresponding to the candidate scalogram; and when the plurality of characteristics are within prerequisite value ranges, selecting the electroencephalographic signal portion of the candidate scalogram within an electroencephalographic signal selection data structure.

Disclosed is a method for assessing a cognition and movement disease or disorder in a subject. In the method, a qualimetric activity parameter for cognition and/or fine motoric activity measurements is determined from a dataset of measurements obtained from the subject using a mobile device. The qualimetric activity parameter is compared to a reference and the disease or disorder is thereby assessed. A method identifying whether a subject will benefit from a therapy for a cognition and movement disease or disorder is also disclosed. The method can be carried out with a mobile device having a processor, a sensor and a database as well as software that carries out the method. Also disclosed is a system having a mobile device with a sensor and a remote device having a processor and a database and software that carries out the method for assessing a cognition and movement disease or disorder.

A system for analyzing a neurological and/or neurodegenerative disorder (ND) is disclosed. The system include an electrocardiogram (ECG) sensor and an inertial measurement unit (IMU) sensor to a subject; a processor; a memory that stores instructions. When executed by the processor, the instructions cause the processor to: gather ECG and IMU data for the subject; input the integrated ECG and IMU data to a first computational model and a second computational model; and infer a presence of the ND based on the first computational model, or a change in the ND based on the second computational model. A method for analyzing and ND is also disclosed.

A sensor may be configured to detect periodic limb movement in a sleeping person. The sensor may be a non-contact sensor, such as a radar motion sensor. The sensor may include a radio frequency transmitter for emitting radio frequency signals toward the person. The sensor may include a receiver for receiving reflected ones of the emitted radio frequency signals and processing the reflected ones of the emitted radio frequency signals to produce motion signal(s). A processor, such as one integrated with or coupled to the sensor, may evaluate the motion signals, such as in-phase and quadrature motion signals, and generate an indicator to identify occurrence of periodic limb movement in the motion signals based on the evaluation of the motion signals.