A thermal control unit for controlling a patient's temperature includes a fluid outlet for delivering temperature-controlled fluid to a patient, a pump, a heat exchanger, and a controller that automatically pauses thermal treatment of the patient prior the patient reaching a target temperature. During the pause, the controller assesses a reaction of the patient and changes a temperature of the fluid only inside the thermal control unit if the patient is likely to reach the target temperature without further thermal treatment. However, if the patient is unlikely to reach the target temperature without further thermal treatment, the controller restarts the thermal treatment. The controller may pause thermal treatment again prior to reaching the target temperature and assess the patient's reaction. In some embodiments, the controller may selectively include and exclude a fluid reservoir in a circulation channel within the thermal control unit.

A flexible sheet for neurostimulation has a flexible non-conductive substrate matrix in which electrodes are embedded along a lower surface. Electrically conductive wires extend from the electrodes through the flexible substrate to another exterior surface of the substrate. Methods of making the flexible sheet and making a device using the flexible sheet are also disclosed.

Systems, methods and computer readable media comprising a virtual exercise board, which is represented by images on the screen of a pad device; wearable devices configured to attach to each shoe of a user and to collect and transmit touch data to the pad device; cameras for tracking movement and calibrating with the data collected by the wearable devices; and computer programs for collecting user data, processing user data, and generating outputs. In embodiments, features include augmented reality; ratings of performance; automated workouts/protocols; real-time progress bar; multi-location database capabilities; and reports.

An electronic device that includes an electronic calendar containing scheduled events, the device further including a) software that matches an event with an optimal brain state, and b) means for convening to the user of the device such optimal brain state when the calendar indicates that the event is imminent or has arrived.

A fabric-based item may be provided with a stretchable band. The stretchable band may be formed from a ring-shaped strip of stretchable fabric having an opening configured to fit around a body part of a user. Circuitry may be coupled to strands of material in the stretchable band. The circuitry may include sensor circuitry for making measurements on the body part such as electrocardiogram measurements, blood pressure measurements, and respiration rate measurements. Wireless communications circuitry in the fabric-based item may be used to communicate wirelessly with external electronic equipment. A wireless power transmitting device may transmit wireless power. A coil formed from conductive strands in the fabric-based item may be used by wireless power receiving circuitry in the fabric-based item to receive the wireless power. The coil may have one or more turns that run around the ring-shaped strip of stretchable fabric.

A quantitative gait training and/or analysis system includes one or more footwear modules that may include a piezoresistive sensor, an inertial sensor and an independent logic unit. The footwear module functions to permit the extraction of gait kinematics and evaluation thereof in real time, or data may be stored for later reduction and analysis. Embodiments relating to calibration-based estimation of kinematic gait parameters are described.

A method comprising: digitally processing orientation measurements provided by each of first and second inertial measurement units, the first and second units being arranged on first and second body members of a person, respectively, according to a predetermined unit arrangement, and the first and second body members being connected by a joint; the measurements are digitally processed such that the computing device at least: computes a length vector of a segment of the first body member based on a first orientation measurement of the first unit; defines a joint axis plane of the joint based on a second orientation measurement of the second unit; and computes a heading rotation value for making the first orientation measurement to be contained within the joint axis plane defined; and the method further comprising digitally modifying the first orientation measurement or the second orientation measurement by applying a rotation at least based on the heading rotation value computed. Also, a motion tracking system and a computer program product.

The present disclosure relates to sensing devices, systems, and their methods of use for aiding transcutaneous magnetic stimulation (tMS) therapy, such as for the treatment, alleviation, and the management of pain. The sensing device being configured for determining and measuring the efficacy thereof. Particularly, the present disclosure is directed to providing sensing devices, systems including the same, and their methods of use in identifying and targeting one or more sources of pain, such as chronic neuropathic pain, as well as for facilitating in the treatment thereof.

A motion monitoring method (500) is provided, which includes: obtaining a movement signal of a user during motion, wherein the movement signal includes at least an electromyographic signal or an attitude signal (510); and monitoring a movement of the user during motion based at least on feature information corresponding to the electromyographic signal or the feature information corresponding to the attitude signal (520).

A mixed reality (MR) training system includes an identification algorithm (ML1) that identifies incidents of concern (IOCs) based on an incident report data set and related contextual data. Each IOC occurs in the data set with a frequency at least equal to a pre-determined threshold or the resulting consequence is at least equal to a different pre-determined threshold. The system also includes a prediction algorithm (ML2) configured to identify predicted changes in the frequency or contextual data of incidents, an experience generation algorithm (ML3) configured to generate an MR training experience based on IOCs identified by ML1 and the predictions of ML2. A fourth algorithm (ML4) tailors and optimizes MR generated training experiences based, in part, on (i) changes in the incident report data or contextual data or (ii) performance data or biometric response data received during or after a user's interaction with the MR training experience.