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.

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: Wrist-worn devices and related methods measure a pulse transit time non-invasively and calculate a blood pressure value using the pulse transit time. A wrist-worn device include a wrist-worn elongate band, at least four EKG or ICG electrodes coupled to the wrist-worn device for detecting a ventricular ejection of a heart, a photo-plethysmogram (PPG) sensor coupled to the wrist-worn device for detecting arrival of a blood pressure pulse at the user's wrist, and a controller configured to calculate a pulse transit time (PTT) for the blood pressure pulse. The controller calculates one or more blood pressure values for the user based on the PTT.

Abstract: The present invention provides non-invasive devices, methods, and systems for determining a pressure of blood within a cardiovascular system of a user, the cardiovascular system including a heart and the user having a wrist covered by skin. More particularly, the present invention discloses a variety of wrist-worn devices having a variety of sensors configured to non-invasively engage the skin on the wrist of the user for sensing a variety of user signals from the cardiovascular system of the user. Generally, approaches disclosed herein may passively track blood pressure values without any interaction required on the part of the user or may allow for on demand or point measurements of blood pressure values by having a user actively interact with the sensors of the wrist-worn device.

Abstract: A breathing sequence may define a suggested breathing pattern. Based on signal data collected by a user device, an initial breathing pattern that includes a cyclic pattern may be estimated. A first period of the breathing sequence may be initiated by generating a breathing sequence element based on a synchronization of the cyclic pattern with the breathing sequence. The breathing sequence element may fluctuate during a second period of the breathing sequence in accordance with a breathing profile associated with the suggested breathing pattern.

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 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: An algorithm for determining heart rate by removing motion artifacts from a PPG signal in the frequency domain utilizes a principal component analysis. Some examples of the present disclosure process PPG signals in combination with accelerometer signals to remove unwanted artifacts in the frequency domain. For example, principal components of the accelerometer signal can be generated and combined with the PPG signal to filter out acceleration contributions represented in the PPG signal to reveal heart rate peaks. Additionally, in some examples, templates may be stored for correlation with candidate heart rate peaks to select those peaks with the highest correlations with the stored templates.

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: 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: Algorithms for detecting whether a device is properly secured to a user's skin are described. The operation of a device, such as a wearable device, can be adjusted based on whether the device is properly secured to a user's skin (e.g., on-wrist) or not properly secured to the user's skin (e.g., off-wrist). For example, certain functions can be disabled for power-saving, security or other purposes if the device is off-wrist. In order to avoid falsely identifying the device as off-wrist or on-wrist, algorithms for detecting whether the device is on-wrist or off-wrist can calculate one or more variances based on signals measured by a light sensor and compare the one or more variances with one or more thresholds. Comparing the one or more variances to the one or more threshold can improve the accuracy of wrist-detection algorithms.

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: Algorithms for detecting whether a device is properly secured to a user's skin are described. The operation of a device, such as a wearable device, can be adjusted based on whether the device is properly secured to a user's skin (e.g., on-wrist) or not properly secured to the user's skin (e.g., off-wrist). For example, certain functions can be disabled for power-saving, security or other purposes if the device is off-wrist. In order to avoid falsely identifying the device as off-wrist or on-wrist, algorithms for detecting whether the device is on-wrist or off-wrist can calculate one or more variances based on signals measured by a light sensor and compare the one or more variances with one or more thresholds. Comparing the one or more variances to the one or more threshold can improve the accuracy of wrist-detection algorithms.

Abstract: A breathing sequence may define a suggested breathing pattern. Based on signal data collected by a user device, an initial breathing pattern that includes a cyclic pattern may be estimated. A first period of the breathing sequence may be initiated by generating a breathing sequence element based on a synchronization of the cyclic pattern with the breathing sequence. The breathing sequence element may fluctuate during a second period of the breathing sequence in accordance with a breathing profile associated with the suggested breathing pattern.

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: The present invention provides non-invasive devices, methods, and systems for determining a pressure of blood within a cardiovascular system of a user, the cardiovascular system including a heart and the user having a wrist covered by skin. More particularly, the present invention discloses a variety of wrist-worn devices having a variety of sensors configured to non-invasively engage the skin on the wrist of the user for sensing a variety of user signals from the cardiovascular system of the user. Generally, approaches disclosed herein may passively track blood pressure values without any interaction required on the part of the user or may allow for on demand or point measurements of blood pressure values by having a user actively interact with the sensors of the wrist-worn device.

Abstract: Wrist-worn devices and related methods measure a pulse transit time non-invasively and calculate a blood pressure value using the pulse transit time. A wrist-worn device include a wrist-worn elongate band, at least four EKG or ICG electrodes coupled to the wrist-worn device for detecting a ventricular ejection of a heart, a photo-plethysmogram (PPG) sensor coupled to the wrist-worn device for detecting arrival of a blood pressure pulse at the user's wrist, and a controller configured to calculate a pulse transit time (PTT) for the blood pressure pulse. The controller calculates one or more blood pressure values for the user based on the PTT.

Abstract: Algorithms for detecting whether a device is properly secured to a user's skin are described. The operation of a device, such as a wearable device, can be adjusted based on whether the device is properly secured to a user's skin (e.g., on-wrist) or not properly secured to the user's skin (e.g., off-wrist). For example, certain functions can be disabled for power-saving, security or other purposes if the device is off-wrist. In order to avoid falsely identifying the device as off-wrist or on-wrist, algorithms for detecting whether the device is on-wrist or off-wrist can calculate one or more variances based on signals measured by a light sensor and compare the one or more variances with one or more thresholds. Comparing the one or more variances to the one or more threshold can improve the accuracy of wrist-detection algorithms.

Abstract: Algorithms for detecting whether a device is properly secured to a user's skin are described. The operation of a device, such as a wearable device, can be adjusted based on whether the device is properly secured to a user's skin (e.g., on-wrist) or not properly secured to the user's skin (e.g., off-wrist). For example, certain functions can be disabled for power-saving, security or other purposes if the device is off-wrist. In order to avoid falsely identifying the device as off-wrist or on-wrist, algorithms for detecting whether the device is on-wrist or off-wrist can calculate one or more variances based on signals measured by a light sensor and compare the one or more variances with one or more thresholds. Comparing the one or more variances to the one or more threshold can improve the accuracy of wrist-detection algorithms.