An elbow joint rehabilitation system and an elbow joint rehabilitation method are provided. The elbow joint rehabilitation system includes a support member, a motor, a torque sensing unit, a first electromyography sensor, a second electromyography sensor and a motor control device. In the elbow joint rehabilitation method, the support member is configured to support an arm of a patient. Thereafter, the torque sensing unit is configured to sense the torque applied on the support member to obtain a sensed arm torque signal. Then, the first electromyography sensor and the second electromyography sensor are configured to sense the muscle activities of biceps and triceps of the patient to obtain electromyography signals. Thereafter, the motor is controlled to drive the support member to perform rehabilitation in accordance with the sensed arm torque signal, the electromyography signals and a current support member position provided by the motor.

An elbow joint rehabilitation system and an elbow joint rehabilitation method are provided. The elbow joint rehabilitation system includes a support member, a motor, a torque sensing unit, a first electromyography sensor, a second electromyography sensor and a motor control device. In the elbow joint rehabilitation method, the support member is configured to support an arm of a patient. Thereafter, the torque sensing unit is configured to sense the torque applied on the support member to obtain a sensed arm torque signal. Then, the first electromyography sensor and the second electromyography sensor are configured to sense the muscle activities of biceps and triceps of the patient to obtain electromyography signals. Thereafter, the motor is controlled to drive the support member to perform rehabilitation in accordance with the sensed arm torque signal, the electromyography signals and a current support member position provided by the motor.

A device, a process and a computer program influence the breathing of a person. The device (10) for influencing the inspiratory muscles of a person (20) includes a detection device (12) for detecting an electromyographic signal of the person; a breathing influencing device (14) and a control device (16) for controlling the detection device (12) and the breathing influencing device (14). The control device (16) is configured to determine information on a muscle state of an inspiratory muscle of the person (20) on the basis of the electromyographic signal. The control device (16) is further configured to operate the breathing influencing device (14) as a function of the information on the muscle state in a training mode, which is limited in time, with a training intensity.

A device, a process and a computer program influence the breathing of a person. The device (10) for influencing the inspiratory muscles of a person (20) includes a detection device (12) for detecting an electromyographic signal of the person; a breathing influencing device (14) and a control device (16) for controlling the detection device (12) and the breathing influencing device (14). The control device (16) is configured to determine information on a muscle state of an inspiratory muscle of the person (20) on the basis of the electromyographic signal. The control device (16) is further configured to operate the breathing influencing device (14) as a function of the information on the muscle state in a training mode, which is limited in time, with a training intensity.

Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Devices, systems, and methods herein relate to electromyography (EMG) that may be used in diagnostic and/or therapeutic applications, including but not limited to electrophysiological study of muscles in the body relating to neuromuscular function and/or disorders. Sensor assemblies and methods are described herein for non-invasively generating an EMG signal corresponding to muscle tissue where the sensor may be positioned directly on a surface of the muscle tissue including any associated membrane (e.g., mucosal, endothelial, synovial) overlying the muscle tissue. A sensor assembly may include one or more pairs of closely spaced, atraumatic electrodes in a bipolar or multipolar configuration. The first and second electrodes may be applied against a surface of muscle tissue (that may include a membrane overlying the muscle) and receive electrical activity signal data corresponding to an electrical potential difference of the portion of muscle between the electrodes.

An example system includes a plurality of biometric sensors to generate a plurality of signals. The system includes a feature engine to generate a plurality of feature vectors from the plurality of signals. The system includes a classifier engine to generate a plurality of decision vectors based on the plurality of feature vectors. The system includes an attention engine to weight the plurality of feature vectors and the plurality of decision vectors and determine a characteristic of a user based on the weighted feature and decision vectors.

An example system includes a plurality of biometric sensors. The system also includes a first classifier engine to produce a first latent space representation of a first signal from a first biometric sensor of the plurality of biometric sensors. The system includes a second classifier engine to produce a second latent space representation of a second signal from a second biometric sensor of the plurality of biometric sensors. The system includes an attention engine to weight the first latent space representation and the second latent space representation based on correlation among latent space representations. The system includes a final classifier engine to determine a characteristic of a user based on the weighted first and second latent space representations.

Apparatus and systems that improve or enhance a user's visual experience are provided. The apparatus or system includes an intraocular implant which incorporates a processor, a sensor, and an effector. The apparatus or system is responsive to commands provided by a user, for example spoken commands, gestures, and imagery. All or part of the apparatus or system can be located within the user's eye. Some embodiments include a display, which can provide an enhanced image and/or information related to the apparatus or system.

The present invention relates to a system and method for acquiring and analyzing physiological data from a user. The system includes a plurality of interconnected devices, which may communicate sensor data to a personal mobile electronic device. Each interconnected device includes at least one sensor to acquire physiological data. In addition, at least one sensor is operably connected to the body of the user. Further, the interconnected biometric devices may be implanted medical devices and/or wearable electronic devices. The personal mobile electronic device is wirelessly connected to each of the plurality of interconnected biometric devices. In addition, the personal mobile electronic device is configured to receive and analyze physiological data acquired by each of the plurality of interconnected devices and to compute the difference between the values of the same physiological parameter measured at a different location of the users body.