Abstract: In one embodiment, a method includes receiving touch inputs from a user corresponding to an activation trigger for an assistant system executing on a head-mounted device at the head-mounted device, accessing signals from inertial measurement unit (IMU) sensors of the head-mounted device by the head-mounted device, determining that the user is either donning or doffing the head-mounted device by an on-device don/doff detection model and based only on the signals from the IMU sensors, and overriding the activation trigger to prevent an activation of the assistant system responsive to the received touch inputs.

Abstract: In one embodiment, a method includes accessing from a client system associated with a first user sensor signals captured by sensors of the client system, wherein the client system comprises a plurality of sensors, and wherein the sensors signals are accessed from the sensors based on cascading model policies, wherein each cascading model policy utilizes one or more of a respective cost or relevance associated with each sensor, detecting a change in a context of the first user associated with an activity of the first user based on machine-learning models and the sensor signals, wherein the change in the context of the first user satisfies a trigger condition associated with the activity, and responsive to the detected change in the context of the first user automatically capturing visual data by cameras of the client system.

Abstract: The subject matter described herein is directed to systems, detection devices and enzyme sensors for real-time determination of the concentration levels of nutrients in a crop cultivation substrate using thermal signals and change in enthalpy per unit of enzyme. Methods of using the systems, detection devices and enzyme sensors for agricultural applications are described.

Abstract: In one embodiment, a method includes accessing from a client system associated with a first user sensor signals captured by sensors of the client system, wherein the client system comprises a plurality of sensors, and wherein the sensors signals are accessed from the sensors based on cascading model policies, wherein each cascading model policy utilizes one or more of a respective cost or relevance associated with each sensor, detecting a change in a context of the first user associated with an activity of the first user based on machine-learning models and the sensor signals, wherein the change in the context of the first user satisfies a trigger condition associated with the activity, and responsive to the detected change in the context of the first user automatically capturing visual data by cameras of the client system.

Abstract: In one embodiment, a method includes receiving touch inputs from a user corresponding to an activation trigger for an assistant system executing on a head-mounted device at the head-mounted device, accessing signals from inertial measurement unit (IMU) sensors of the head-mounted device by the head-mounted device, determining that the user is either donning or doffing the head-mounted device by an on-device don/doff detection model and based only on the signals from the IMU sensors, and overriding the activation trigger to prevent an activation of the assistant system responsive to the received touch inputs.

Abstract: In one embodiment, a method includes receiving touch inputs from a user corresponding to an activation trigger for an assistant system executing on a head-mounted device at the head-mounted device, accessing signals from inertial measurement unit (IMU) sensors of the head-mounted device by the head-mounted device, determining that the user is either donning or doffing the head-mounted device by an on-device don/doff detection model and based only on the signals from the IMU sensors, and overriding the activation trigger to prevent an activation of the assistant system responsive to the received touch inputs.

Abstract: A wearable physiological monitor is configured through a calibration procedure to provide a calibrated blood pressure measurement based on signals from an optical sensing system. In one aspect, optical (PPG) signals and motion signals are acquired while applying a mechanical stimulus over a range of mechanical frequencies with a haptic actuator. Resulting data is used to create a dynamic model for calculating blood pressure based on motion of the monitor. This blood pressure measurement can also usefully be correlated to the PPG signal for continuous blood pressure estimation. In another aspect, a monitoring device is positioned over a radial artery, and then optical measurements are taken of the radial artery while varying (and measuring) an applied force. Using various techniques, a model can be derived from this data for continuous blood pressure estimation.

Abstract: In one embodiment, a method includes rendering a first output image comprising one or more augmented-reality (AR) objects for displays of an AR rendering device of an AR system associated with a first user. The method further includes accessing sensor signals associated with the first user. The one or more sensor signals may be captured by sensors of the AR system. The method further includes detecting a change in a context of the first user with respect to a real-world environment based on the sensor signals. The method further includes rendering a second output image comprising the AR objects for the displays of the AR rendering device. One or more of the AR objects may be adapted based on the detected change in the context of the first user.

Abstract: In one embodiment, a method includes rendering a first output image comprising one or more augmented-reality (AR) objects for displays of an AR rendering device of an AR system associated with a first user. The method further includes accessing sensor signals associated with the first user. The one or more sensor signals may be captured by sensors of the AR system. The method further includes detecting a change in a context of the first user with respect to a real-world environment based on the sensor signals. The method further includes rendering a second output image comprising the AR objects for the displays of the AR rendering device. One or more of the AR objects may be adapted based on the detected change in the context of the first user.

Abstract: In one embodiment, a method includes rendering a first output image comprising one or more augmented-reality (AR) objects for displays of an AR rendering device of an AR system associated with a first user. The method further includes accessing sensor signals associated with the first user. The one or more sensor signals may be captured by sensors of the AR system. The method further includes detecting a change in a context of the first user with respect to a real-world environment based on the sensor signals. The method further includes rendering a second output image comprising the AR objects for the displays of the AR rendering device. One or more of the AR objects may be adapted based on the detected change in the context of the first user.

Abstract: In one embodiment, a method includes accessing from a client system associated with a first user sensor signals captured by sensors of the client system, wherein the client system comprises a plurality of sensors, and wherein the sensors signals are accessed from the sensors based on cascading model policies, wherein each cascading model policy utilizes one or more of a respective cost or relevance associated with each sensor, detecting a change in a context of the first user associated with an activity of the first user based on machine-learning models and the sensor signals, wherein the change in the context of the first user satisfies a trigger condition associated with the activity, and responsive to the detected change in the context of the first user automatically capturing visual data by cameras of the client system.

Abstract: In one embodiment, a system includes an automatic speech recognition (ASR) module, a natural-language understanding (NLU) module, a dialog manager, one or more agents, an arbitrator, a delivery system, one or more processors, and a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to receive a user input, process the user input using the ASR module, the NLU module, the dialog manager, one or more of the agents, the arbitrator, and the delivery system, and provide a response to the user input.