Abstract: A system, computer-readable storage medium, and a method capable of, directly or indirectly, estimating sleep states of a user based on sensor data from movement sensors and/or optical sensors.

Abstract: Disclosed are devices and methods for estimating blood pressure, which implement a pulse-transit-time-based blood pressure model that can be calibrated. Some implementations provide reliable and user friendly means for calibrating the blood pressure model using blood pressure perturbation methods and multiple sensors.

Abstract: Disclosed are devices and methods for non-invasively measuring arterial stiffness using pulse wave analysis of photoplethysmogram data. In some implementations, wearable biometric monitoring devices provided herein for measuring arterial stiffness have the ability to automatically and intelligently obtain PPG data under suitable conditions while the user is engaged in activities or exercises. In some implementations, wearable biometric monitoring devices are provided herein with the ability to remove PPG data variance caused by factors unrelated to arterial stiffness. In some implementations, wearable biometric monitoring devices have the ability to perform PWA while accounting for the user’s activities, conditions, or status.

Abstract: Disclosed are devices and methods for non-invasively measuring arterial stiffness using pulse wave analysis of photoplethysmogram data. In some implementations, wearable biometric monitoring devices provided herein for measuring arterial stiffness have the ability to automatically and intelligently obtain PPG data under suitable conditions while the user is engaged in activities or exercises. In some implementations, wearable biometric monitoring devices are provided herein with the ability to remove PPG data variance caused by factors unrelated to arterial stiffness. In some implementations, wearable biometric monitoring devices have the ability to perform PWA while accounting for the user's activities, conditions, or status.

Abstract: Disclosed are devices and methods for estimating blood pressure, which implement a pulse-transit-time-based blood pressure model that can be calibrated. Some implementations provide reliable and user friendly means for calibrating the blood pressure model using blood pressure perturbation methods and multiple sensors.

Abstract: A system, computer-readable storage medium, and a method capable of, directly or indirectly, estimating sleep states of a user based on sensor data from movement sensors and/or optical sensors.

Abstract: In an embodiment, a data processing method comprises obtaining one or more photoplethysmography (PPG) signals from one or more PPG sensors of a monitoring apparatus, the PPG signals being generated based upon optically detecting pulsed variations in blood flow; obtaining a motion sensor signal from a motion sensor in the monitoring apparatus; identifying, based upon the motion sensor signal, one or more periods of motion (e.g., low motion) of the monitoring apparatus; and selectively obtaining and storing segments of the PPG signals based on a temporal relationship between the segments of the PPG signals and the identified periods of motion.

Abstract: In an embodiment, a data processing method comprises obtaining one or more photoplethysmography (PPG) signals from one or more PPG sensors of a monitoring apparatus, the PPG signals being generated based upon optically detecting pulsed variations in blood flow; obtaining a motion sensor signal from a motion sensor in the monitoring apparatus; identifying, based upon the motion sensor signal, one or more periods of motion (e.g., low motion) of the monitoring apparatus; and selectively obtaining and storing segments of the PPG signals based on a temporal relationship between the segments of the PPG signals and the identified periods of motion.

Abstract: A system, computer-readable storage medium, and a method capable of, directly or indirectly, estimating sleep states of a user based on sensor data from movement sensors and/or optical sensors.

Abstract: Disclosed are devices and methods for non-invasively measuring arterial stiffness using pulse wave analysis of photoplethysmogram data. In some implementations, wearable biometric monitoring devices provided herein for measuring arterial stiffness have the ability to automatically and intelligently obtain PPG data under suitable conditions while the user is engaged in activities or exercises. In some implementations, wearable biometric monitoring devices are provided herein with the ability to remove PPG data variance caused by factors unrelated to arterial stiffness. In some implementations, wearable biometric monitoring devices have the ability to perform PWA while accounting for the user's activities, conditions, or status.

Abstract: In one embodiment, an electronic device to be worn on a user's forearm includes a display and a set of one or more sensors that provide sensor data. In one aspect, a device may detect, using sensor data obtained from a set of sensors, that a first activity state of a user is active. The device may determine, while the first activity state is active, that the sensor data matches a watch check rule associated with the first activity state. Responsive to the detected match, the device may cause a change in visibility of the display.

Abstract: Disclosed are devices and methods for non-invasively measuring arterial stiffness using pulse wave analysis of photoplethysmogram data. In some implementations, wearable biometric monitoring devices provided herein for measuring arterial stiffness have the ability to automatically and intelligently obtain PPG data under suitable conditions while the user is engaged in activities or exercises. In some implementations, wearable biometric monitoring devices are provided herein with the ability to remove PPG data variance caused by factors unrelated to arterial stiffness. In some implementations, wearable biometric monitoring devices have the ability to perform PWA while accounting for the user's activities, conditions, or status.

Abstract: In one embodiment, an electronic device to be worn on a user's forearm includes a display and a set of one or more sensors that provide sensor data. In one aspect, a device may detect, using sensor data obtained from a set of sensors, that a first activity state of a user is active. The device may determine, while the first activity state is active, that the sensor data matches a watch check rule associated with the first activity state. Responsive to the detected match, the device may cause a change in visibility of the display.

Abstract: In one embodiment, an electronic device to be worn on a user's forearm includes a display and a set of one or more sensors that provide sensor data. In one aspect, a device may detect, using sensor data obtained from a set of sensors, that a first activity state of a user is active. The device may determine, while the first activity state is active, that the sensor data matches a watch check rule associated with the first activity state. Responsive to the detected match, the device may cause a change in visibility of the display.

Abstract: In an embodiment, a data processing method comprises obtaining one or more photoplethysmography (PPG) signals from one or more PPG sensors of a monitoring apparatus, the PPG signals being generated based upon optically detecting pulsed variations in blood flow; obtaining a motion sensor signal from a motion sensor in the monitoring apparatus; identifying, based upon the motion sensor signal, one or more periods of motion (e.g., low motion) of the monitoring apparatus; and selectively obtaining and storing segments of the PPG signals based on a temporal relationship between the segments of the PPG signals and the identified periods of motion.

Abstract: A method and apparatus for providing biofeedback during a meditation exercise are disclosed. In one aspect, the wearable device includes one or more biometric sensors and a user interface. The method may involve prompting the user, via the user interface, to perform a meditation exercise, the meditation exercise being associated with a target physiological metric related to the physiology of the user. The method may involve measuring, based on output of at least one of the one or more biometric sensors, a physiological metric of the user during the meditation exercise. The method may involve determining a performance score indicating the user's performance during the meditation exercise based on comparing the measured physiological metric with the target physiological metric. The method may involve providing, via the user interface, based on the performance score, feedback information indicative of the user's performance during the meditation exercise.

Abstract: A method and apparatus for providing biofeedback during a meditation exercise are disclosed. In one aspect, the wearable device includes one or more biometric sensors and a user interface. The method may involve prompting the user, via the user interface, to perform a meditation exercise, the meditation exercise being associated with a target physiological metric related to the physiology of the user. The method may involve measuring, based on output of at least one of the one or more biometric sensors, a physiological metric of the user during the meditation exercise. The method may involve determining a performance score indicating the user's performance during the meditation exercise based on comparing the measured physiological metric with the target physiological metric. The method may involve providing, via the user interface, based on the performance score, feedback information indicative of the user's performance during the meditation exercise.

Abstract: In one embodiment, an electronic device to be worn on a user's forearm includes a display and a set of one or more sensors that provide sensor data. In one aspect, a device may detect, using sensor data obtained from a set of sensors, that a first activity state of a user is active. The device may determine, while the first activity state is active, that the sensor data matches a watch check rule associated with the first activity state. Responsive to the detected match, the device may cause a change in visibility of the display.

Abstract: In one embodiment, an electronic device to be worn on a user's forearm includes a display and a set of one or more sensors that provide sensor data. In one aspect, a device may detect, using sensor data obtained from a set of sensors, that a first activity state of a user is active. The device may determine, while the first activity state is active, that the sensor data matches a watch check rule associated with the first activity state. Responsive to the detected match, the device may cause a change in visibility of the display.

Abstract: In one embodiment, an electronic device to be worn on a user's forearm includes a display and a set of one or more sensors that provide sensor data. In one aspect, a device may detect, using sensor data obtained from a set of sensors, that a first activity state of a user is active. The device may determine, while the first activity state is active, that the sensor data matches a watch check rule associated with the first activity state. Responsive to the detected match, the device may cause a change in visibility of the display.