Systems and methods for prompting a user to perform an exercise and monitoring the exercise are provided. Multiple independent sensors or sensor systems may be used to calculate energy expenditure. Various criteria may be used to manually or automatically select the independent sensor or sensor system or combination that will be used with the energy expenditure calculations.

A method and apparatus for automated arm training includes at least one therapeutic device that includes a handle, a sensor assembly, and a display. The handle is configured to move along a path. The sensor assembly is configured to provide a measured time series made up of multiple handle location measurements at a corresponding multiple of measured time instances. The display is configured to present an image based on the measured time series. A robot motor can be configured to keep the handle moving near a tolerance of a target trajectory.

One or more custom actions are stored in memory. Each of the custom actions is associated with a pattern of physical movement and a threshold. Physical movement data captured by a user device of the user is received and mapped to an identified one of the custom actions. When the physical movement data matches the associated pattern of physical movement within the associated threshold, it is determined that the user is authorized to access the identified custom action.

Embodiments of the presently described device, system and method support upper extremity (UE) therapy through tracking the human hand. The system can include a hand-wearable sensor mounting system with hand-wearable components and a movement interpretation circuit. The device can include a hand-wearable component comprising a hook, and a sensing transducer comprising a clip, wherein the clip is detachably securable to the hook. In embodiments, one or more sensing transducers are translationally and rotationally restricted when secured to the hand-wearable components.

A system and method for rehabilitation and recovery using adaptive surface electromyographic sensing and visualization is disclosed. The system uses surface electromyography (sEMG) sensors to identify signals of intent from patients with physical disabilities and then uses these signals to interact with a computer system designed to create repetitive practice in a manner that promotes neurological recovery. A machine teaming module analyses body signals picked up during patient movement attempts and converts these body signals to a visual representation of the intended movement by way of a virtual body or virtual body part displayed on a computer display, display glasses, or the like. The system thus allows for very early patient therapy, providing early benefits to rehabilitation therapy not heretofore possible. The virtual reality or augmented reality environment provides a patient with very early visual reinforcement of beneficial muscle activation patterns.

A method and system are disclosed for outputting augmented reality information to a first user. In an embodiment, the method includes acquiring first information, including image information, depth information, coordinate information and combinations thereof, the first information relating to at least one of a medical device and a medical examination of a patient; creating the augmented reality information, relating to the medical device and/or the medical examination of the patient, based on the first information; and outputting the augmented reality information such that the augmented reality information is perceivable in a field of view of the first user.

A method of providing workout training for a user of an activity tracking system includes displaying a plurality of training plan options to the user on a screen of a personal electronic device, and then receiving a selected training plan option from the user. Selected workout day options are received from the user and the system generates a training schedule for the user based on the selected training plan and the selected workout day options. One or more reminders identify the type of workout for the scheduled day and an option to accept or reject the workout. When the user selects the option to accept the workout, the workout goal associated with the scheduled workout is displayed. The method further includes determining progress toward the workout goal based on the received workout data, and displaying an indicator of progress toward the workout goal on the screen during the workout.

The invention comprises a method for estimating state of a cardiovascular system, comprising the steps of: providing a cardiac analyzer, comprising: a blood pressure sensor, the blood pressure sensor generating a time-varying pressure state waveform output from a portion of a person; a system processor connected to the blood pressure sensor; and a dynamic state-space model of a cardiovascular system, the system processor receiving cardiovascular input data, from the blood pressure sensor, related to a transient pressure state of the cardiovascular system, where at least one probabilistic model, of the dynamic state-space model, operating on the time-varying pressure state waveform output generates a probability distribution function to a non-pressure state of the cardiovascular system. The probability distribution function is iteratively updated using synchronized updated time-varying pressure state waveform output from the blood pressure sensor and a non-pressure state output related to a cardiovascular system parameter is generated.

A force measurement system is disclosed herein. The force measurement system includes a force measurement assembly configured to receive a subject, and one or more data processing devices operatively coupled to the force measurement assembly. In one embodiment, the one or more data processing devices are configured to determine a difference between a center of pressure and a center of mass for the subject from output force and/or moment data, and to determine the fall risk of the subject based upon the difference between the center of pressure and the center of mass for the subject. In another embodiment, the one or more data processing devices are configured to determine one or more balance parameters of the subject from the output force and/or moment data while the subject is stepping onto the top surface of the force measurement assembly and/or stepping off the top surface of the force measurement assembly.

Embodiments of a system for controlling an object using brainwaves are disclosed. The system includes a set of EEG electrodes configured to be positioned on a head of a user and to collect EEG signals. The system further includes one or more computer readable storage mediums storing a framework configured to execute an extensible architecture through which EEG signals are interpreted for control of the object. The framework includes an EEG device plugin associated with the set of EEG electrodes and configured to extract the EEG signals from the set of EEG electrodes. The framework also includes an interpreter plugin configured to convert the EEG signals extracted by the EEG device plugin into a command. Further, the framework includes an object control plugin configured to access the command through an extension point of the interpreter plugin and to execute the command to control the object.