Abstract: Implementations relate to automatic suggested responses based on message stickers provided in a messaging application. In some implementations, a computer-implemented method to provide message suggestions in a messaging application includes detecting a first message sent by a first user device to a second user device over a communication network, programmatically analyzing the first message to determine a semantic concept associated with the first message, identifying one or more message stickers based at least in part on the semantic concept, and transmitting instructions to cause the one or more message stickers to be displayed in a user interface displayed on the second user device.

Abstract: An indoor air quality (IAQ) system for a building includes an IAQ sensor that is located within the building and that is configured to measure an IAQ parameter. The IAQ parameter is one of: an amount of particulate of at least a predetermined size present in air; an amount of volatile organic compounds (VOCs) present in air; and an amount of carbon dioxide present in air. A mitigation module is configured to: selectively turn on a mitigation device based on a comparison of the IAQ parameter with a first ON threshold and a second ON threshold; and selectively turn off the mitigation device based on a comparison of the IAQ parameter with an OFF threshold. A clean module is configured to determine a clean value for the IAQ parameter. A thresholds module is configured to, based on the clean value, determine the first ON threshold and the OFF threshold.

Abstract: A system and method for collecting motion data using a fitness tracking device located on an arm of a user, detecting that the arm is constrained based on the motion data, estimating a stride length of the user based on the motion data and historical step cadence-to-stride length data, calculating fitness data using the estimated stride length, and outputting the fitness data to the user.

Abstract: Implementations relate to automatic suggested responses based on message stickers provided in a messaging application. In some implementations, a computer-implemented method to provide message suggestions in a messaging application includes detecting a first message sent by a first user device to a second user device over a communication network, programmatically analyzing the first message to determine a semantic concept associated with the first message, identifying one or more message stickers based at least in part on the semantic concept, and transmitting instructions to cause the one or more message stickers to be displayed in a user interface displayed on the second user device.

Abstract: Wearable electronic devices, such as watches, can be provided with an ability to detect whether a tactile input provided to an input component, such as a button, is intentional or unintentional. For example, a wearable device can analyze the context in which a tactile input is received, such as attributes of the tactile input and/or operational parameters of the wearable device at the time the tactile input is received. By further example, a wearable device can infer whether a tactile input is a result of an activity, such as exercising, random movement, or collision with an object. The wearable devices can accept or reject the tactile input and determine whether an action associated with the tactile input should be performed.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting the end of hiking activities. By accurately and promptly detecting the end of hiking activities automatically, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording a hiking activity.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting walking workouts. By accurately and promptly detecting the start of walking workouts activities and automatically distinguishing between walking workout and causal walking activities, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording walking workouts.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting cardio machine activities, estimating user direction of travel, and monitoring performance during cardio machine activities. By accurately and promptly detecting cardio machine activities and automatically distinguishing between activities performed on different types of cardio machines, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording activities on a wide variety of cardio machines. In various embodiments, cardio machine activity detection techniques may use magnetic field data from a magnetic field sensor to improve the accuracy of orientation data and device heading measurements used to detect the end of a cardio machine activity.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting cycling activities and monitoring performance during cycling. By accurately and promptly detecting the end of cycling workouts automatically, the disclosure enables wearable devices to accurately calculate user performance information when users forget to stop recording a cycling activity session. In various embodiments, cycling activity detection techniques involve a cycling speed measure that incorporates terrain gradient determined based on pressure data. In various embodiments, the cycling activity detection techniques may distinguish between a temporary stop and an intentional stop using an estimated energy expenditure.

Abstract: Disclosed embodiments include wearable devices and techniques for detecting swimming activities, classifying user motion, detecting water submersion, and monitoring performance during swimming activities. By accurately and promptly detecting swimming activities and automatically distinguishing between different swimming stroke type performed during a swimming activity, the disclosure enables wearable devices to accurately calculate user performance information when users forget to start and/or stop recording swimming activities. In various embodiments, swimming activity detection techniques may improve the selectivity of motion based methods of identifying swimming activities identification by confirming motion analysis with water immersion and pressure data analysis that detects when the wearable device is submerged in water.

Abstract: A method for calibrating a magnetometer of an electronic device can include detecting a change in a magnetism of the electronic device, collecting a first magnetic field data from the magnetometer at sampling frequency of at least 1 hertz, generating an elliptical calibration model based at least partially on the collected first magnetic field data, collecting a second magnetic field data from the magnetometer, and fitting the collected second magnetic field data to a sphere using the elliptical calibration model.

Abstract: An indoor air quality (IAQ) system for a building includes an IAQ sensor that is located within the building and that is configured to measure an IAQ parameter. The IAQ parameter is one of: an amount of particulate of at least a predetermined size present in air; an amount of volatile organic compounds (VOCs) present in air; and an amount of carbon dioxide present in air. A mitigation module is configured to: selectively turn on a mitigation device based on a comparison of the IAQ parameter with a first ON threshold and a second ON threshold; and selectively turn off the mitigation device based on a comparison of the IAQ parameter with an OFF threshold. A clean module is configured to determine a clean value for the IAQ parameter. A thresholds module is configured to, based on the clean value, determine the first ON threshold and the OFF threshold.

Abstract: In an example method, a mobile device receives motion data obtained by one or more sensors over a time period, where the one or more sensors are worn by a user, The mobile device determines, based on the motion data, an impact experienced by the user during the time of period, and determines one or more of characteristics of the user. The mobile device determines, based on the motion data and the one or more characteristics of the user, a likelihood that the user requires assistance subsequent to the impact, and generates one or more notifications based on likelihood.

Abstract: An electronic device may have components that experience performance variations as the device changes orientation relative to a user. Changes in the orientation of the device relative to the user can be monitored using a motion sensor. A camera may be used to periodically capture images of a user's eyes. By processing the images to produce accurate orientation information reflecting the position of the user's eyes relative to the device, the orientation of the device tracked by the motion sensor can be periodically updated. The components may include audio components such as microphones and speakers and may include a display with an array of pixels for displaying images. Control circuitry in the electronic device may modify pixel values for the pixels in the array to compensate for angle-of-view-dependent pixel appearance variations based on based on the orientation information from the motion sensor and the camera.

Abstract: The invention provides an injectable composition and method for the minimally invasive, in-situ repair and regeneration of an injured ligament or tendon in a mammalian subject. The composition is also useful for the delivery of growth factors, therapeutic agents and cells into the area of tendon or ligament injury.

Abstract: Embodiments are disclosed for indoor/outdoor detection using a mobile device, such as wearable computer (e.g., smartwatch). In an embodiment, a method comprises: receiving, by one or more processors of a wearable computer, wireless access point (AP) scan data, global navigation satellite system (GNSS) data and inertial sensor data; determining, by the one or more processors, a first state of the wearable computer based on the wireless AP scan data; determining, by the one or more processors, a second state of the wearable computer based on a comparison of the GNSS data and the inertial sensor data; and outputting, by the one or more processors, an indoor/outdoor signal indicating that the wearable computer is indoors or outdoors based on the first and second states.

Abstract: One example of determining an estimated time of arrival (ETA) based on calibrated distance includes a method implemented by a processor included in a mobile device to be carried by a user. An estimated distance between a starting location and an ending location is received. A calibration factor based on a location of the mobile device on the user's body and a movement pace of the user is determined. The estimated distance between the starting location and the ending location is modified based, in part, on the determined calibration factor resulting in a modified estimated distance. An estimated time to arrive (ETA) at the ending location is determined based, in part, on the modified estimated distance.

Abstract: In an example method, a mobile device receives motion data obtained by one or more sensors worn by a user. The mobile device determines, based on the motion data, that the user has fallen at a first time and whether the user has moved between a second time and a third time subsequent to the first time. Upon determining that the user has not moved between the second time and the third time, the mobile device initiates a communication to an emergency response service at a fourth time after the third time. The communication includes an indication that the user has fallen and a location of the user.

Abstract: In an example method, a mobile device obtains sample data generated by one or more sensors over a period of time, where the one or more sensors are worn by a user. The mobile device determines that the user has fallen based on the sample data, and determines, based on the sample data, a severity of an injury suffered by the user. The mobile device generates one or more notifications based on the determination that the user has fallen and the determined severity of the injury.

Abstract: In an example method, a mobile device obtains a database including a plurality of data records. Each data record includes an indication of a respective impact previously experienced by a user of the mobile device, and sensor data generated by one or more first sensors worn by the user during that impact. The mobile device obtains sensor data generated by one or more second sensors worn by the user over a period of time, and determines whether the user has fallen during the period of time based on the database and the additional sensor data. The mobile device generates one or more notifications based on the determination of whether the user has fallen during the period of time.