A method for calibrating and executing a rehabilitation exercise for a stroke-affected limb of a stroke patient is disclosed, the method comprising the steps of providing a haptic device for an able limb of the stroke patient to manipulate to perform a calibration action to result in a first position of the haptic device, and providing the haptic device for the stroke-affected limb to manipulate to perform the calibration action to result in a second position of the haptic device. The method further comprises the steps of moving the haptic device coupled with the stroke-affected limb from the second position towards the first position until a predetermined counterforce is detected, indicating an extreme position for the stroke-affected limb using the haptic device, and calibrating the haptic device with the extreme position such that during the rehabilitation exercise, the haptic device is prevented from moving beyond the extreme position.

A non-invasive system and method are provided. Brain activity of a user is detected using a non-invasive brain interface when the user is exposed to an external stimulus. The user is determined to be negatively primed by the external stimulus based on the detected brain activity. An alert that the user is being negatively primed by the external stimulus is automatically provided. A tagged training session may be automatically provided to the user in response determining that the user has a negative mental state, thereby promoting a positive mental state of the user. A training session list containing the tagged training session may be automatically modified based on the determined mental state of the user.

A system and method for communicating biofeedback to a user through a wearable device that includes collecting physiological data of at least one physiological property of a user; processing the physiological data into at least one biosignal; monitoring the at least one biosignal for a feedback activation condition; and upon satisfying a feedback activation condition, delivering haptic feedback.

The present disclosure relates generally to systems, methods, and devices for interpreting neural signals to determine a desired movement of a target, transmitting electrical signals to the target, and dynamically monitoring subsequent neural signals or movement of the target to change the signal being delivered if necessary, so that the desired movement is achieved. In particular, the neural signals are decoded using a feature extractor, decoder(s) and a body state observer to determine the electrical signals that should be sent.

A system in which a head-mountable wearable device detects a real-time electroencephalographic (EEG) response from a user while the user is performing an activity or exposed to an external stimulus in a real-world (non-clinical) setting. The wearable device performs on-board processing of a detected EEG signal to enable efficient data wireless transfer to a processing unit (e.g. on a smartphone or the like). The processing unit transforms the EEG signal in real time into a meaningful indicator of current mental state, and presents indicator to the user, e.g. in a form able to improve their performance of the activity, promote complementary activities or to enhance or alter their mental state.

An information processing device includes a receiver that receives a specification of a desired brain wave state of a user, and a controller that controls playback of music causing a brain wave state of the user to transition to or maintain the desired brain wave state.

Techniques that facilitate monitoring learning performance using neurofeedback are described. In one embodiment, a system is provided that comprises a memory that stores computer-executable components and a processor that executes computer-executable components stored in the memory. In one implementation, the computer-executable components comprise a feedback component that receives first feedback information regarding mental function of a user in association with participation in a learning experience, wherein the first feedback information is captured via a NIRS spectroscopy sensor worn by the user. The computer-executable components further comprise an assessment component that determines learning performance information for the user based on the first feedback information, wherein the learning performance information reflects the user's learning of content presented to the user in the learning experience, and a notification component that generates a notification based on the learning performance information indicating the user's learning of the content is below a defined learning performance level.

An ear tip for an earpiece including a body having first and second ends, an inner wall extending between the first and second ends to define a hollow passage to conduct sound waves, and an outer wall connected to the inner wall of the body at the first end and tapering away from the inner wall toward the second end. The ear tip further includes first and second electrically conductive elements arranged on an outer surface of the deformable outer wall.

Methods for mental treatments, such as treatments for mental disorders, are described. Such methods can include measuring user brainwaves while the user plays a video game, such as a video game where the user is exposed to a competitive environment. The user can be rewarded within the video game based upon brainwave measurements.

A method and system for assessing a mental fitness state of a person using objective physiologic signals from the person includes arranging one or more sensors in proximity to the person's head to measure at least one electroencephalogram (EEG) signal of the person, and analyzing the at least one EEG signal by computing a power in the EEG signal in an EEG signal band; determining a characteristic of the computed power that, for the EEG signal band, is indicative of an emotional or cognitive state of the person; and assessing a mental fitness state of the person based on the determined characteristic. An assessment output is generated which reports the assessed mental fitness state of the person. In at least one implementation, the EEG signal contains oscillating theta waves, and a variance in timing of maximum power occurring in the theta waves around a determined average latency is calculated.