Abstract: Methods, systems, and devices for menstrual cycle phase identifier are described. A system may be configured to receive physiological data collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values taken over the plurality of days where the time series includes a plurality of menstrual cycles for the user. The system may then identify morphological features in the time series and identify menstrual cycle phases in the time series based on the morphological features. The system may cause the graphical user interface to display the identified menstrual cycle phases.

Abstract: Methods, systems, and devices for utilizing a multi-output neural network are described. The system may receive physiological data and input the physiological data into the multi-output neural network. The physiological data may include a first input stream corresponding to the heartbeat data and a second input stream corresponding to the motion data. The multi-output neural network is trained to simultaneously compute one or more values of a first physiological metric and one or more values of a second physiological metric. In some cases, the first physiological metric and the second physiological metric each include an input stream from at least one of the first input stream, the second input stream, or both. The system may generate, via a single pass of the multi-output neural network, the one or more values of the first physiological metric and the one or more values of the second physiological metric.

Abstract: Methods, systems, and devices for illness detection are described. A method may include receiving heart rate variability (HRV) data associated with a user from a wearable device, the HRV data collected via the wearable device throughout a first time interval and a second time interval subsequent to the first time interval. The method may include inputting the HRV data into a classifier, and identifying a satisfaction of deviation criteria between a first subset of the HRV data collected throughout the first time interval and a second subset of the HRV data collected throughout the second time interval. The method may include causing a graphical user interface (GUI) of a user device to display an illness risk metric for the user based on the satisfaction of the deviation criteria, the illness risk metric associated with a relative probability that the user will transition from a healthy state to an unhealthy state.

Abstract: Methods, systems, and devices for detection of medical conditions using respiration rate data are described. A method may include receiving physiological data associated with a user, the physiological data being continuously collected via a wearable device associated with the user, determining a set of respiration rate values for the user over a time interval based on the physiological data, and determining one or more respiration rate parameters associated with a change of the set of respiration rate values over the time interval. The method may further include determining one or more condition risk metrics associated with one or more medical conditions based on the one or more respiration rate parameters, where the one or more condition risk metrics associated with a relative probability that the user is associated with a respective medical condition.

Abstract: Methods, systems, and devices for miscarriage identification are described. A system may be configured to receive physiological data associated with a user that is pregnant and collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values. The system may then identify that the temperature values are lower than a pregnancy baseline of temperature values for the user and detect an indication of an early pregnancy loss of the user. The system may generate a message for display on a graphical user interface on a user device that indicates the indication of the early pregnancy loss.

Abstract: Methods, systems, and devices for illness detection are described. A method may include receiving heart rate variability (HRV) data associated with a user from a wearable device, the HRV data collected via the wearable device throughout a first time interval and a second time interval subsequent to the first time interval. The method may include inputting the HRV data into a classifier, and identifying a satisfaction of deviation criteria between a first subset of the HRV data collected throughout the first time interval and a second subset of the HRV data collected throughout the second time interval. The method may include causing a graphical user interface (GUI) of a user device to display an illness risk metric for the user based on the satisfaction of the deviation criteria, the illness risk metric associated with a relative probability that the user will transition from a healthy state to an unhealthy state.

Abstract: Methods, systems, and devices for detection of medical conditions using respiration rate data are described. A method may include receiving physiological data associated with a user, the physiological data being continuously collected via a wearable device associated with the user, determining a set of respiration rate values for the user over a time interval based on the physiological data, and determining one or more respiration rate parameters associated with a change of the set of respiration rate values over the time interval. The method may further include determining one or more condition risk metrics associated with one or more medical conditions based on the one or more respiration rate parameters, where the one or more condition risk metrics associated with a relative probability that the user is associated with a respective medical condition.

Abstract: Methods, systems, and devices for miscarriage identification are described. A system may be configured to receive physiological data associated with a user that is pregnant and collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values. The system may then identify that the temperature values are lower than a pregnancy baseline of temperature values for the user and detect an indication of an early pregnancy loss of the user. The system may generate a message for display on a graphical user interface on a user device that indicates the indication of the early pregnancy loss.

Abstract: Methods, systems, and devices for wearing detection are described. A user device may determine a condition to trigger an oxygen saturation measurement, or a measure of blood oxygen saturation (SpO2), for a user of a wearable device. The condition may be based on a physical state of the wearable device, a physiological state of the user, or both. In some examples, the user device may determine the condition based on one or more relationships between sensor data from the wearable device, application data, physiological data from the wearable device, or any combination thereof. The user device may receive a measure of oxygen saturation of the user from the wearable device. The user device may cause a graphical user interface (GUI) of the user device to display an indication of the measure of the oxygen saturation for the user.

Abstract: Methods, systems, and devices for heart rate detection are described. A method for measuring heart rate for a user may include receiving physiological data associated with the user, wherein the physiological data may include photoplethysmogram (PPG) data and motion data collected throughout a first time interval via a wearable device associated with the user. The method may include determining a set of candidate heart rate measurements within the first time interval based at least in part on the PPG data, selecting a first heart rate measurement from the set of candidate heart rate measurements based on the received motion data, and determining a first heart rate for the user within the first time interval based on the selected first heart rate measurement.

Abstract: Methods, systems, and devices for menopause detection and treatment are described. A system may be configured to receive physiological data associated with a user from a wearable device, and identify one or more physiological indications of a hot flash experienced by the user based on the physiological data satisfying one or more thresholds. Additionally, the system may be configured to determine a metabolic efficiency metric associated with the user based on the received physiological data, and determine a menopause metric for the user based on the metabolic efficiency metric, where the menopause metric is associated with a relative probability that the user will experience menopausal symptoms. The system may then cause a graphical user interface (GUI) of a user device to display information associated with the identified hot flash and/or one or more messages associated with the menopause metric.

Abstract: Methods, systems, and devices for illness detection are described. A method may include identifying a menstrual cycle model associated with a menstrual cycle for a user, and receiving physiological data for the user collected throughout a first time interval and a second time interval by a wearable device. The method may include inputting the physiological data and the menstrual cycle model into a classifier, and identifying a satisfaction of deviation criteria between first and second subsets of the physiological data collected throughout the first and second time intervals, respectively, based on the menstrual cycle model. The method may include causing a graphical user interface (GUI) of a user device to display an illness risk metric associated with the user based on the satisfaction of the deviation criteria, the illness risk metric associated with a relative probability that the user will transition from a healthy state to an unhealthy state.

Abstract: Methods, systems, and devices for pregnancy complication identification and prediction are described. A system may be configured to receive physiological data associated with a user that is pregnant and collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values. The system may then identify that the temperature values deviate from a pregnancy baseline of temperature values for the user and detect an indication of one or more pregnancy complications of the user. The system may generate a message for display on a graphical user interface on a user device that indicates the indication of the one or more pregnancy complications.

Abstract: Methods, systems, and devices for anovulatory cycle detection are described. A system may be configured to receive physiological data collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values taken over the plurality of days where the time series includes a plurality of ovulatory cycles for the user. The system may then identify the plurality of ovulatory cycles based on positive slopes in the time series and identify an indication of an anovulatory cycle based on deviations in the time series. The system may generate a message for display on a graphical user interface on a user device that indicates the indication of the identified anovulatory cycle.

Abstract: Methods, systems, and devices for fertility prediction are described. A system may be configured to receive physiological data collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values taken over the plurality of days where the time series includes a plurality of menstrual cycles. The system may then determine a plurality of menstrual cycle length parameters associated with the menstrual cycles and determine a user fertility prediction based on the menstrual cycle length parameters. The system may generate a message for display on a graphical user interface that indicates the determined user fertility prediction.

Abstract: Methods, systems, and devices for miscarriage identification are described. A system may be configured to receive physiological data associated with a user that is pregnant and collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values. The system may then identify that the temperature values are lower than a pregnancy baseline of temperature values for the user and detect an indication of an early pregnancy loss of the user. The system may generate a message for display on a graphical user interface on a user device that indicates the indication of the early pregnancy loss.

Abstract: Methods, systems, and devices for pregnancy detection are described. A system may be configured to receive physiological data collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values taken over the plurality of days. The system may then identify temperature elevations in the time series of the temperature values relative to a temperature baseline for the user and detect an indication of a pregnancy of the user based on the identified temperature elevations. The indication of the pregnancy may be detectable from the identified temperature elevations prior to being detectable from a threshold increase in hormone elevations relative to a hormone baseline of the user. The system may cause the graphical user interface to display the detected indication of the pregnancy.

Abstract: Methods, systems, and devices for labor onset and birth identification and prediction are described. A system may be configured to receive physiological data associated with a user that is pregnant and collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values. The system may then calculate a pregnancy baseline temperature slope for the user and identify that the temperature slope deviates from the pregnancy baseline temperature slope for the user. The system may detect an indication of a labor onset of the user and generate a message for display on a graphical user interface on a user device that indicates the indication of the labor onset.

Abstract: Methods, systems, and devices for a pregnancy mode configuration are described. In some cases, the system may receive physiological data associated with a user from a wearable device and provide a first set of targets associated with one or more physiological metrics and a first set of messages associated with the one or more physiological metrics based on the received physiological data. The system may receive an indication of the user being pregnant. In some cases, the system may identify a trigger to transition from the first operational mode to a second operational mode of the application based on receiving the indication. The system may provide a second set of targets associated with the one or more physiological metrics and a second set of messages associated with the one or more physiological metrics that are adjusted for pregnancy based on the second operational mode.

Abstract: Methods, systems, and devices for menstrual cycle phase identifier are described. A system may be configured to receive physiological data collected over a plurality of days, where the physiological data includes at least temperature data. Additionally, the system may be configured to determine a time series of temperature values taken over the plurality of days where the time series includes a plurality of menstrual cycles for the user. The system may then identify morphological features in the time series and identify menstrual cycle phases in the time series based on the morphological features. The system may cause the graphical user interface to display the identified menstrual cycle phases.