Abstract: A computationally-efficient method for a smart assistant computer to track a human includes receiving data from one or more sensors configured to monitor a physical environment. The data is computer-analyzed to recognize presence of a human in the physical environment, and upon confirming an identity of the human, a first level of computational resources of the smart assistant computer is dedicated to track the human. Upon failing to confirm the identity of the human while a known user is present, a second level of computational resources of the smart assistant computer, greater than the first level, is dedicated to determine the identity of the human. Upon failing to confirm the identity of the human while the known user is absent, a third level of computational resources of the smart assistant computer, is dedicated to determine the identity of the human.

Abstract: An optical heart rate sensor stores data indicating the timing of heart beats in a first-in-first-out rolling buffer. During a first condition, new data is added to the rolling buffer and adjusted such that a duration preceding a newly detected heart beat is closer to an average duration between each pair of consecutive heart beats stored in the rolling buffer if the duration preceding the newly detected heart beat differs from the average duration by more than a duration threshold. The rolling buffer is cleared when a number of data adjustments over a predetermined time period exceeds a counting threshold. The rolling buffer is then repopulated such that the duration between each pair of consecutive heart beats is equal to a most recent duration between consecutive heart beats that did not differ from the average duration by more than the duration threshold.

Abstract: Methods and devices for heart rate monitoring may include determining whether an adjustment triggering condition has been met. Moreover, the methods and devices may include, in accordance with a determination that the adjustment triggering condition has been met, adjusting the second sensor indication to obtain an adjusted second sensor indication based at least on the difference between the first sensor indication and the second sensor indication. The methods and devices may further include, in accordance with a determination that the adjustment triggering condition has not been met, transmitting the second sensor indication to the signaling filter.

Abstract: Methods and devices for correcting electrocardiogram (EKG) indication saturation may include receiving an EKG indication from at least one sensor and determining that a saturation condition has been met in response to receiving the EKG indication. Additionally, the methods and devices may include incrementing an EKG saturation level based on a determination that the saturation condition has been met. Moreover, the methods and devices may include determining whether the EKG saturation level satisfies an EKG saturation threshold. The methods and device may include disregarding at least a second EKG indication in accordance with a determination that the saturation level satisfies the EKG saturation threshold. The methods and devices may further include transmitting the second EKG indication to an output device in accordance with a determination that the saturation level does not satisfy the EKG saturation threshold.

Abstract: Methods and devices for blood pressure monitoring may include receiving one or more sensor measurements from the at least one sensor. The methods and devices may further include determining at least one of a first blood pressure indication using a first regression representation based on the one or more sensor measurements, a second blood pressure indication using a second regression representation based on the one or more sensor measurements, or a third blood pressure indication using a third regression representation based on the one or more sensor measurements. The methods and devices may include performing a blood pressure selection procedure using the first blood pressure indication, the second blood pressure indication, and the third blood pressure indication to determine an estimated blood pressure indication based on one or more classification characteristics. The methods and devices may further include transmitting the estimated blood pressure indication to the output device.

Abstract: A wearable heart rate monitoring device includes an optical sensor configured to translate test light reflected from a wearer of the wearable heart rate monitoring device into a machine-readable heart rate signal. The wearable heart rate monitoring device also includes a motion sensor configured to translate motion of the wearable heart rate monitoring device into a machine-readable motion signal. The wearable heart rate monitoring device also includes a heart rate reporting machine, configured to determine a type of activity currently being performed by the wearer of the wearable heart rate monitoring device based at least in part on the machine-readable motion signal, and output an estimated heart rate based on at least the machine-readable heart rate signal and the type of activity.

Abstract: Determining time spent outdoors. A method includes, at a first time, using one or more primary criteria including one or more criteria related to information provided by a first hardware input sensor on a device, to determine that the device is outdoors. The method further includes at one or more other times, using one or more secondary criteria, different than the primary criteria, the secondary criteria related to information provided by one or more second hardware input sensors, to determine continuity of the device being outdoors from the first time to the one or more other times. The method further includes based on determining that the device is outdoors and determining continuity of the device being outdoors from the first time to the one or more other times, identifying a total amount of time that the device has been outdoors.

Abstract: Systems and methods for estimating lifestyle metrics with a wearable electronic device are disclosed herein. One disclosed system may include the wearable electronic device comprising a processor and a sensor system providing inputs to the processor. The sensor system may include a high power sensor and a low power sensor. The processor may operate in a high power mode in which both sensors are operational and a low power mode in which the high power sensor is not operational. In the high power mode, the processor may compute a lifestyle metric about a user for a first time period based on first data from the high power sensor. In the low power mode, the processor may compute the lifestyle metric for a second time period based on second data from the low power sensor and the first data and/or a derivative of the first data.

Abstract: A method of optical heart rate sensing includes receiving a motion frequency from a motion sensor and receiving an optical signal from an optical sensor. The motion frequency is then filtered from the optical signal, and an estimated heart rate frequency is determined based on the filtered optical signal. A heart rate is reported that is based on the motion frequency, but not based on the estimated heart rate frequency, when a local neighbor magnitude ratio of the estimated heart rate frequency is below a confidence threshold.

Abstract: Computing devices and methods for controlling light output of a display are disclosed. In one example, a default brightness setting is set to an indoor light output level. A UV light sensor is activated to detect UV radiation levels. Based on determining that one or more of the UV radiation levels exceed a UV threshold, the default brightness setting is updated to correspond to an outdoor light output level that is greater than the indoor light output level. Without using information from an ambient light sensor, the display is activated from a deactivated state to illuminate at the updated default brightness setting corresponding to the outdoor light output level.

Abstract: A wearable heart rate monitoring device includes an optical sensor configured to translate test light reflected from a wearer of the wearable heart rate monitoring device into a machine-readable heart rate signal. The wearable heart rate monitoring device also includes an elevation sensor configured to translate an elevation of the wearable heart rate monitoring device into a machine-readable elevation signal. The wearable heart rate monitoring device further includes a heart rate reporting machine configured to output an estimated heart rate based on at least the machine-readable heart rate signal and the machine-readable elevation signal.

Abstract: A wearable heart rate monitoring device includes an optical sensor configured to translate test light reflected from a wearer of the wearable heart rate monitoring device into a machine-readable heart rate signal. The wearable heart rate monitoring device also includes a motion sensor configured to translate motion of the wearable heart rate monitoring device into a machine-readable motion signal. The wearable heart rate monitoring device also includes a heart rate reporting machine, configured to determine a type of activity currently being performed by the wearer of the wearable heart rate monitoring device based at least in part on the machine-readable motion signal, and output an estimated heart rate based on at least the machine-readable heart rate signal and the type of activity.

Abstract: Determining time spent outdoors. A method includes, at a first time, using one or more primary criteria including one or more criteria related to information provided by a first hardware input sensor on a device, to determine that the device is outdoors. The method further includes at one or more other times, using one or more secondary criteria, different than the primary criteria, the secondary criteria related to information provided by one or more second hardware input sensors, to determine continuity of the device being outdoors from the first time to the one or more other times. The method further includes based on determining that the device is outdoors and determining continuity of the device being outdoors from the first time to the one or more other times, identifying a total amount of time that the device has been outdoors.

Abstract: A network-accessible computer includes a network-communications interface, configured to receive health metrics of a user over a computer network. The network-accessible computer also includes a logic machine, which is configured to localize the user in a virtual space based on the health metrics, identify k nearest neighbors in the virtual space having k shortest Euclidean distances to the user, and generate a health insight comparing the user to the k nearest neighbors. The network-communications interface is further configured to send the health insight to a computing device associated with the user via the computer network.

Abstract: Examples are disclosed herein that are related to monitoring body hydration levels based on galvanic skin response measurements acquired by a wearable electronic device. One example provides a wearable electronic device including a sensor configured to measure a galvanic skin response, a logic device, and a storage device including instructions executable by the logic device to operate a hydration monitoring mode, acquire a plurality of measures of galvanic skin response over time, present data regarding the plurality of measures of galvanic skin response.

Abstract: A computing device includes a time-dependent sensor configured to output a time-dependent datum at a time-dependent frequency, the time-dependent datum specifying a sensed parameter. A time-independent, sample-count-based calculation module is configured to output a new time-agnostic datum after receiving a specific number of the time-dependent data regardless of elapsed time taken to receive the specific number of the time-dependent data.

Abstract: A system is described for providing the value of a biological characteristic. The system includes a sensor. The sensor is configured to generate a time domain photoplethysmogram (PPG) input signal. The system further includes a first computation module coupled to the sensor. The first computation module is configured to evaluate portions of the generated time domain PPG signal against predetermined quality criteria. The system further includes a second computation module coupled to the first computation module. The second computation module is configured to use portions of the generated time domain PPG signal that meet the predetermined quality criteria to generate an output value. The output value characterizes a biological characteristic at a point in time.

Abstract: A wearable device is described. The wearable device comprises: a device body configured to be secured in contact with a subject; a first sensor borne by the device body that is activatable to measure a heart rate of the subject; and control logic configured to activate the first sensor during a monitoring period during which the subject is determined to be in a sleep period.

Abstract: Collection and analysis of physiological reading can predict when a person is likely to develop a fever before that person's body temperature increases. In an implementation a device such as a wearable band collects physiological information from its wearer. The physiological information may include heart rate or respiration rate. The person's physiological information classified by an algorithm derived through machine learning techniques. The algorithm may be trained by using data from other individuals who are both healthy and who are sick and/or trained from past reading of the person's own physiological readings. The algorithm may evaluate a value of the person's physiological information to generate probabilities that the person is healthy or that the person likely to become sick and/or develop a fever in the next few days.