Abstract: A wearable device may be used to perform a health or medical assessment of a user. The wearable device may detect user movements of the user. The wearable device generates signal data representing the user movements. The signal data is input into a model to identify a feature set. The feature set is converted into a score that corresponds to a medical condition of the user.

Abstract: A method including determining historical user data associated with an event occurring on a wearable device, determining a probability of interacting with an object on a display of the wearable device based on the historical user data, scaling a hitbox associated with the object to form a scaled hitbox, detecting a user input based on an eye tracking being within the scaled hitbox, and in response to detecting the user input, initiating an action corresponding to the object.

Abstract: Physical gestures may be performed by a user to interact with a head-mounted device. These physical gestures can be detected by other devices worn by the user. For example, a fitness tracker worn on a wrist of a user may be used to detect the movement of the wrist as a gesture and then communicate this gesture to the head-mounted device. This accessory-mediated gesture interaction may be interrupted when the accessory device loses power or otherwise stops tracking. In this condition, the disclosed head-mounted device may take-over gesture detection by monitoring distortions to a magnetic field caused by movement of the device. This form of gesture detection can be used when an active device has exhausted its battery. Further, this form of gesture detection can be used for electrically inactive objects that can cause detectable changes to the magnetic field when moved in the magnetic field.

Abstract: Physical gestures may be performed by a user to interact with a head-mounted device. These physical gestures can be detected by other devices worn by the user. For example, a fitness tracker worn on a wrist of a user may be used to detect the movement of the wrist as a gesture and then communicate this gesture to the head-mounted device. This accessory-mediated gesture interaction may be interrupted when the accessory device loses power or otherwise stops tracking. In this condition, the disclosed head-mounted device may take-over gesture detection by monitoring distortions to a magnetic field caused by movement of the device. This form of gesture detection can be used when an active device has exhausted its battery. Further, this form of gesture detection can be used for electrically inactive objects that can cause detectable changes to the magnetic field when moved in the magnetic field.

Abstract: A method including determining historical user data associated with an event occurring on a wearable device, determining a probability of interacting with an object on a display of the wearable device based on the historical user data, scaling a hitbox associated with the object to form a scaled hitbox, detecting a user input based on an eye tracking being within the scaled hitbox, and in response to detecting the user input, initiating an action corresponding to the object.

Abstract: Techniques of controlling electronic devices using gestures use a wearable device on a user which translates, via a model, user movements into signals that both identify an electronic device to be controlled and a specific action to take with regard to that electronic device. The wearable device includes an inertial measurement unit (IMU) sensor and a photoplethysmography (PPG) sensor and measure six degrees of freedom (6DOF). The model is a convolutional neural network (CNN) that takes x, y, and z-acceleration signals generated by the IMU and PPG and places each acceleration component generated from each sensor in a separate channel. The CNN takes the input from each channel and generates a respective, separate model for each channel. The output at each of the stacked layers are combined in a fully connected layer to produce CNN output identifying an electronic device and a control for the electronic device.

Abstract: A method can include determining, by a head-mounted device, that a user is looking at a first electronic device; determining that the user made a predefined gesture; determining content that was presented by the first electronic device when the user made the predefined gesture; and instructing a second electronic to present the content that was presented by the first electronic device when the user made the predefined gesture.

Abstract: A method can include determining, by a head-mounted device, that a user is looking at a first electronic device; determining that the user made a predefined gesture; determining content that was presented by the first electronic device when the user made the predefined gesture; and instructing a second electronic to present the content that was presented by the first electronic device when the user made the predefined gesture.