Abstract: Various embodiments provide a wellness tracking device with a base plate that may be utilized as a combination electrode by a variety of sensors. The base plate may be a multi-material electrode that includes a conductor and a transparent or semi-transparent material to enable optical sensing. In certain embodiments, the base plate supports a plurality of different sensors, which may selectively utilize the base plate as an electrode.

Abstract: Multiple circuits in a computing device can share one or more conductive elements. The use of the conductive element can vary by circuit, such as an antenna radiator for a radio frequency (RF) circuit or an electrode for an electrocardiography (ECG) circuit. The circuitry sharing a conductive element can utilize signals obtained over different frequency ranges. Those ranges can be used to select decoupling circuitry, or elements, that can enable the respective circuits to obtain signals over a respective frequency range, excluding signals over one or more other frequency ranges corresponding to other circuitry sharing the circuit. Such an approach allows for concurrent independent operation of the circuitry sharing a conductive element.

Abstract: Health information for a woman can be used to predict timing of events related to the woman's menstrual cycle. If available, historical cycle information for a woman can be used to predict upcoming cycle events, such as the start and stop of menstruation. To improve the accuracy of those predictions, one or more health metrics are monitored for the woman that can be correlated with the menstrual cycle. These can include, for example, the resting heart rate (RHR), blood oxygen concentration (SpO2) level, and hemoglobin concentration, among other such options. The metrics are monitored over time to determine patterns that can be correlated with menstrual cycle. This information can then be used to update the predictive model, as well as to update individual event predictions. Information about the predictions, and updates to the predictions, can be surfaced accordingly.

Abstract: The disclosure provides BMDs that have multiple device modes depending on operational conditions of the devices, e.g., motion intensity, device placement, and/or activity type. The device modes are associated with various data processing algorithms. In some embodiments, the BMD is implemented as a wrist-worn or arm-worn device. In some embodiments, methods for tracking physiological metrics using the BMDs are provided. In some embodiments, the process or the BMD applies a time domain analysis on data provided by a sensor of the BMD for a first activity, and applies a frequency domain analysis on the data for a second activity, which contributes to improved accuracy and speed of biometric data.

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: Physiological variables, metrics, biomarkers, and other data points can be used, in connection with a non-invasive wearable device, to screen for, and predict, mental health issues and cognitive states. In addition to metrics such as heart rate, sleep data, activity level, gamification data, and the like, information such as text message and email data, as well as vocal data obtained through a phone and/or a microphone, may be analyzed, provided user authorization. Applying predictive modeling, one or more of the monitored metrics can be correlated with mental states and disorders. Identified patterns can be used to update the predictive models, such as via machine learning-trained models, as well as to update individual event predictions. Information about the mental state predictions, and updates thereto, can be surfaced to the user accordingly.

Abstract: Assessing the sleep quality of a user in association with an electronic device with one or more physiological sensors includes detecting an attempt by the user to fall asleep, and collecting physiological information associated with the user. The disclosed method of assessing sleep quality may include determining respective values for one or more sleep quality metrics, including a first set of sleep quality metrics associated with sleep quality of a plurality of users, and a second set of sleep quality metrics associated with historical sleep quality of the user, based at least in part on the collected physiological information and at least one wakeful resting heart rate of the user, and determining a unified score for sleep quality of the user, based at least in part on the respective values of the one or more sleep quality metrics.

Abstract: This invention provides devices, systems, and methods for performing point-of-care, analysis, including multiplexed analysis, of a biological fluid analyte, such as blood. The invention includes a cartridge for collecting the biological fluid analyte. The cartridge is configured to be inserted into an assay reader, in which one or more assay reactions may be performed. The assay reader is designed to read and report the results of the one or more assay reactions.

Abstract: The accuracy of physiological data measured through contact with skin can be validated by characterizing the forces at the surfaces where data is measured. Conventional devices do not monitor the fit of skin-based sensors, making the accuracy and confidence in physiological data dependent on the user ensuring that the device is fitted properly. Over time, the seating of a device will vary due to changes in user activity and the need to periodically remove a device. Inevitably, instances will arise where the device is not fitted correctly, which may result in skewed physiological metrics. By monitoring the forces acting on the housing of a device, the interface of skin sensors can be characterized allowing for confidence metrics in the corresponding physiological data to be determined. In some cases, a user can be notified when a device is not seated properly, and in some cases, data may even be calibrated based on the fit of a device.

Abstract: Techniques are disclosed for using contextual information to determine an appropriate response in a system that includes a device paired with an accessory device. The contextual information can be sourced from local sensors, received communications, and information stored on a device within the system. Stored parameters in the system allow flexibility and configurability in evaluating the contextual information. Using feedback obtained after actions taken based on the contextual information allows the system to adapt to better meet the needs of the user.

Abstract: A method includes receiving location data of a monitoring device when carried by a user and receiving motion data of the monitoring device. The motion data is associated with a time of occurrence and the location data. The method includes processing the received motion data to identify a group of the motion data having a substantially common characteristic and processing the location data for the group of the motion data. The group of motion data by way of processing the location data provides an activity identifier. The motion data includes metric data that identifies characteristics of the motion data. The method includes transferring the activity identifier and the characteristics of the motion data to a screen of a device for display. The activity identifier being a graphical user interface that receives an input for rendering more or less of the characteristics of the motion data.

Abstract: Approaches described herein can capture an audio signal using at least one microphone while a user of an electronic device is determined to be asleep. At least one audio frame can be determined from the audio signal. The at least one audio frame represents a spectrum of frequencies detected by the at least one microphone over some period of time. One or more sounds associated with the at least one audio frame can be determined. Sleep-related information can be generated. The information identifies the one or more sounds as potential sources of sleep disruption.

Abstract: A wearable computing device includes an electronic display with a configurable brightness level setting, a physiological metric sensor system including a light source configured to direct light into tissue of a user wearing the wearable computing device and a light detector configured to detect light from the light source that reflects back from the user. The device may further include control circuitry configured to activate the light source during a first period, generate a first light detector signal indicating a first amount of light detected by the light detector during the first period, deactivate the light source during a second period, generate a second light detector signal indicating a second amount of light detected by the light detector during the second period, generate a physiological metric based at least in part on the first light detector signal and the second light detector signal, and modify the configurable brightness level setting based on the second light detector signal.

Abstract: Systems, devices, and methods for tracking one or more physiological metrics (e.g., heart rate, blood oxygen saturation, and the like) of a user are described. For example, one or more light sources and one or more light detectors may be positioned on a wearable device such that light can be emitted towards the user's skin and further such that light reflected back to the wearable device can be measured and used to generate values for the one or more physiological metrics.

Abstract: Aspects of automatically detecting periods of sleep of a user of a wearable electronic device are discussed herein. For example, in one aspect, an embodiment may obtain a set of features for periods of time from motion data obtained from a set of one or more motion sensors in the wearable electronic device or data derived therefrom. The wearable electronic device may then classify the periods of time into one of a plurality of statuses of the user based on the set of features determined for the periods of time, where the statuses are indicative of relative degree of movement of the user. The wearable electronic device may also derive blocks of time each covering one or more of the periods of time during which the user is in one of a plurality of states, wherein the states include an awake state and an asleep state.

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: Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Abstract: According to one embodiment, an apparatus comprising a portable monitoring device to be affixed to a user. The portable monitoring device including: 1) a set of one or more sensors to generate sensor data indicative of physical activity of a user when the portable monitoring device is affixed to the user; and 2) processing circuitry coupled with the set of sensors, to detect that the user has been sedentary for a period of time, and cause the portable monitoring device to alert the user responsive to the detection to encourage the user to move.