Abstract: This relates to methods for measuring irregularities in a signal and corresponding devices. The devices can include a PPG sensor unit configured to detect multiple occurrences of a given event in the measured signal(s) over a sampling interval. In some instances, the device can register the occurrences of the events. In some examples, the device can include one or more motion sensors configured to detect whether the device is in a low-motion state. The device may delay initiating measurements when the device is not in a low-motion state to enhance measurement accuracy. Examples of the disclosure further include resetting the sample procedure based on one or more factors such as the number of non-qualifying measurements. In some examples, the device can be configured to perform both primary and secondary measurements, where the primary measurements can include readings using a set of operating conditions different from the secondary measurements.

Abstract: A configuration for a breathing sequence may be defined using a user interface of a user device. The user interface may also be used to begin the breathing sequence. Prior to beginning the breathing sequence, the user device can determine a breath ratio for the breathing sequence based on a breathing profile. The breath ratio is based at least in part on inhale time and exhale time of a breath of the breathing sequence. During the breathing sequence, a fluctuating user interface element may fluctuate at a cyclic rate corresponding to the breath ratio. Such fluctuation may include repeated growing and repeated shrinking of the fluctuating user interface element.

Abstract: This relates to methods for measuring irregularities in a signal and corresponding devices. The devices can include a PPG sensor unit configured to detect multiple occurrences of a given event in the measured signal(s) over a sampling interval. In some instances, the device can register the occurrences of the events. In some examples, the device can include one or more motion sensors configured to detect whether the device is in a low-motion state. The device may delay initiating measurements when the device is not in a low-motion state to enhance measurement accuracy. Examples of the disclosure further include resetting the sample procedure based on one or more factors such as the number of non-qualifying measurements. In some examples, the device can be configured to perform both primary and secondary measurements, where the primary measurements can include readings using a set of operating conditions different from the secondary measurements.

Abstract: A configuration for a breathing sequence may be defined using a user interface of a user device. The user interface may also be used to begin the breathing sequence. During the breathing sequence, a fluctuating user interface element may fluctuate at a cyclic rate. Such fluctuation may include repeated growing and repeated shrinking of the fluctuating user interface element. During the breathing sequence, heart rate data may be collected and used to present heart rate information at a conclusion of the breathing sequence.

Abstract: A pulse transit time is measured non-invasively and used to calculate a blood pressure value. A method of determining one or more blood pressure values includes propagating an alternating drive current through a thorax of a subject via electrodes located on a wrist-worn device. Resulting voltage levels of the subject are sensed by the wrist-worn device. The voltage levels are processed to detect when a volume of blood is ejected from the left ventricle. Output from a pulse arrival sensor coupled to the wrist-worn device is processed to detect when a blood pressure pulse generated by ejection of the volume of blood from the left ventricle arrives at the wrist. A pulse transit time (PTT) for transit of the blood pressure pulse from the left ventricle to the wrist is calculated. One or more blood pressure values for the subject are determined based on the PTT.

Abstract: This disclosure relates to methods for measuring one or more physiological signals while the user is engaged in a predetermined activity. Exemplary predetermined activities can include activities such as walking, climbing stairs, biking, and the like. The physiological measurements can include, but are not limited to, heart rate signals. The physiological measurements may be affected by the predetermined activity, so the system may be configured to employ one or more criteria prior to measuring physiological information to minimize the effects. The one or more criteria can include, but are not limited to, an inter-sampling waiting time, continuous motion criteria, predetermined activity criteria, a post-physiological measurement amount of time, and a confidence value. The continuous motion criteria can be based on the type of predetermined activity. For example, walking may have walking state criteria and a step count criteria.

Abstract: Embodiments are directed to systems and methods for determining a cardiac burden of a user. Methods include collecting a series of cardiac measurements at a first set of time points using one or more sensors and determining a set of measured data points. Each measured data point can include a time value from the first set of time points and a classification comprising one of an occurrence of a qualified cardiac event or absence of the qualified cardiac event. Methods include generating a set of additional data points each including a time value from the second set of time points and a classification of one of the occurrence of the qualified cardiac event or the absence of the qualified cardiac event. Methods include determining a value of the cardiac burden for a predefined period of time using the set of measured data points and the set of additional data points.

Abstract: This relates to methods for measuring irregularities in a signal and corresponding devices. The devices can include a PPG sensor unit configured to detect multiple occurrences of a given event in the measured signal(s) over a sampling interval. In some instances, the device can register the occurrences of the events. In some examples, the device can include one or more motion sensors configured to detect whether the device is in a low-motion state. The device may delay initiating measurements when the device is not in a low-motion state to enhance measurement accuracy. Examples of the disclosure further include resetting the sample procedure based on one or more factors such as the number of non-qualifying measurements. In some examples, the device can be configured to perform both primary and secondary measurements, where the primary measurements can include readings using a set of operating conditions different from the secondary measurements.

Abstract: This disclosure relates to methods for measuring one or more physiological signals while the user is engaged in a predetermined activity. Exemplary predetermined activities can include activities such as walking, climbing stairs, biking, and the like. The physiological measurements can include, but are not limited to, heart rate signals. The physiological measurements may be affected by the predetermined activity, so the system may be configured to employ one or more criteria prior to measuring physiological information to minimize the effects. The one or more criteria can include, but are not limited to, an inter-sampling waiting time, continuous motion criteria, predetermined activity criteria, a post-physiological measurement amount of time, and a confidence value. The continuous motion criteria can be based on the type of predetermined activity. For example, walking may have walking state criteria and a step count criteria.

Abstract: An example technique may include tracking motion of a user wearing the wearable device using at least first sensors of one or more sensors of the wearable device. The technique may also include tracking a physical state of the user using at least second sensors of the one or more sensors of the wearable device. The technique may also include determining whether an application of the wearable device has been launched. The technique may also include determining an action category of the user based at least in part on at least one of the motion of the user, the physical state of the user, or whether the application has been launched. The technique may also include collecting heartrate data of the user. The technique may also include categorizing the heartrate data based at least in part on the determined action category.

Abstract: A configuration for a breathing sequence may be defined using a user interface of a user device. The user interface may also be used to begin the breathing sequence. During the breathing sequence, a fluctuating user interface element may fluctuate at a cyclic rate. Such fluctuation may include repeated growing and repeated shrinking of the fluctuating user interface element. During the breathing sequence, heart rate data may be collected and used to present heart rate information at a conclusion of the breathing sequence.

Abstract: Techniques are provided for tracking heartrate metrics using different operating modes associated with different contexts of a wearable device. For example, a heartrate sensor of the wearable device may be operated in a first operating mode when an activity is being tracked within an application session of a particular application. The heartrate sensor may be operated in a second operating mode after detecting conclusion of the activity within the activity session (e.g., during sedentary time).

Abstract: A configuration for a breathing sequence may be defined using a hardware element of a user device. A user interface of the user device may be used to begin the breathing sequence. During the breathing sequence, a fluctuating progress indicator user interface element may fluctuate at a cyclic rate. Such fluctuation may include repeated growing and repeated shrinking of the fluctuating progress indicator user interface element. During the breathing sequence, heart rate data may be collected and used to present heart rate information at a conclusion of the breathing sequence.

Abstract: This disclosure relates to methods for measuring one or more physiological signals while the user is engaged in a predetermined activity. Exemplary predetermined activities can include activities such as walking, climbing stairs, biking, and the like. The physiological measurements can include, but are not limited to, heart rate signals. The physiological measurements may be affected by the predetermined activity, so the system may be configured to employ one or more criteria prior to measuring physiological information to minimize the effects. The one or more criteria can include, but are not limited to, an inter-sampling waiting time, continuous motion criteria, predetermined activity criteria, a post-physiological measurement amount of time, and a confidence value. The continuous motion criteria can be based on the type of predetermined activity. For example, walking may have walking state criteria and a step count criteria.

Abstract: This disclosure relates to methods for measuring one or more physiological signals while the user is engaged in a predetermined activity. Exemplary predetermined activities can include activities such as walking, climbing stairs, biking, and the like. The physiological measurements can include, but are not limited to, heart rate signals. The physiological measurements may be affected by the predetermined activity, so the system may be configured to employ one or more criteria prior to measuring physiological information to minimize the effects. The one or more criteria can include, but are not limited to, an inter-sampling waiting time, continuous motion criteria, predetermined activity criteria, a post-physiological measurement amount of time, and a confidence value. The continuous motion criteria can be based on the type of predetermined activity. For example, walking may have walking state criteria and a step count criteria.

Abstract: A configuration for a breathing sequence may be defined using a hardware element of a user device. A user interface of the user device may be used to begin the breathing sequence. During the breathing sequence, a fluctuating progress indicator user interface element may fluctuate at a cyclic rate. Such fluctuation may include repeated growing and repeated shrinking of the fluctuating progress indicator user interface element. During the breathing sequence, heart rate data may be collected and used to present heart rate information at a conclusion of the breathing sequence.

Abstract: A breathing sequence may define a suggested breathing pattern. Input may be received at a user interface of a device to initiate the breathing sequence. The breathing sequence may include a configuration phase in which configuration information may be received. The configuration information may define a variable time period for the breathing sequence. The breathing sequence also may include a preliminary phase during which a first version of a fluctuating progress indicator may be presented on the user interface. The fluctuating progress indicator may include a plurality of variable visual characteristics and may fluctuate at a first cyclic rate. The breathing sequence may also include a breathing phase during which a second version of the fluctuating progress indicator may be presented. The second version of the fluctuating progress indicator may fluctuate at a second cyclic rate according to a breathing rate.

Abstract: Techniques are provided for tracking heartrate metrics using different operating modes associated with different contexts of a wearable device. For example, a heartrate sensor of the wearable device may be operated in a first operating mode when an activity is being tracked within an application session of a particular application. The heartrate sensor may be operated in a second operating mode after detecting conclusion of the activity within the activity session (e.g., during sedentary time).

Abstract: Embodiments of the present disclosure can provide systems, methods, and computer-readable medium for tracking the heartrate of a user using different techniques associated with different contexts. For example, motion of a user wearing a wearable device can be tracked using at least first sensors of the one or more sensors. The physical state of the user can also be tracked using at least second sensors of the one or more sensors. In some cases it can be determines whether an application of the wearable device has been launched. Additionally, an activity category of the user can be determined based at least in part on the motion of the user, the physical state of the user, and/or whether the application has been launched. Heartrate data of the user can be collected, and the heartrate data can be categorized based at least in part on the determined category.

Abstract: Methods and devices for obtaining a blood pressure measurement of a subject measure a transit time of a blood pulse of the subject. A method includes sensing, with a pulse ejection sensor of a wrist-worn device, ejection of blood from the left ventricle. Arrival of a resulting blood pressure pulse at the wrist is sensed via a pulse arrival sensor of the wrist-worn device. A transit time of the blood pressure pulse from the left ventricle to the wrist is determined. A relative blood pressure value of the subject is determined based on the transit time. A reference absolute blood pressure value associated with the relative blood pressure value is received. An absolute blood pressure value for the relative blood pressure value is determined based on the reference absolute blood pressure value and the relative blood pressure value.