Abstract: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.

Abstract: A relationship relating a load of exercise and a user's aerobic capacity may be determined as follows. A processor circuit of a device may retrieve, from a memory, a prior probability distribution of the load of exercise and a prior probability distribution of the user's aerobic capacity. The processor circuit may compute a joint prior probability of the load of exercise and the user's aerobic capacity. The processor circuit may compute a joint likelihood of the load of exercise and the user's aerobic capacity based on data indicative of a measured time-stamped work rate and a measured time-stamped heart rate. The processor circuit may combine the joint prior probability and the joint likelihood to produce a joint posterior probability. The processor circuit may use the joint posterior probability to determine a relationship relating the load of exercise and the user's aerobic capacity and output a calorie calculation.

Abstract: The present disclosure relates to a system and method of detecting activity by a wheelchair user. In one aspect, a method comprises collecting motion data of a user device located on an appendage of the user; detecting, by a processor circuit, that one or more activities by the wheelchair user occurred based on the motion data; calculating, by a processor circuit, an energy expenditure by the user based the one or more activities by the wheelchair user occurred; and outputting, by a processor circuit, the energy expenditure estimation.

Abstract: A system and method for improving the accuracy of a user device when generating map/navigation information for display to a user, comprising: obtaining compass heading from a magnetometer of the user device located within a vehicle; adjusting the compass heading based on a mount angle of the user device within the vehicle; obtaining location data from a location sensor of the user device; determining if a course of the vehicle can be reliably determined from the location data; if the course of the vehicle cannot be reliably determined from the location data, determining the orientation of the vehicle using the compass heading but not the course; if the course of the vehicle can be reliably determined from the location data, calculating a course of the vehicle based on the location data and determining the orientation of the vehicle using the course; generating, by a processor, first map/navigation information using the orientation of the vehicle; and displaying, by a processor, the first map/navigation inform

Abstract: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.

Abstract: The present disclosure relates to a system and method of detecting activity by a wheelchair user. In one aspect, a method comprises collecting motion data of a user device located on an appendage of the user; detecting, by a processor circuit, that one or more activities by the wheelchair user occurred based on the motion data; calculating, by a processor circuit, an energy expenditure by the user based the one or more activities by the wheelchair user occurred; and outputting, by a processor circuit, the energy expenditure estimation.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: The present disclosure relates to systems and methods of estimating energy expenditure of a user while swimming. A processor circuit of a user device can estimate a speed of the user based on a stroke rate and a stroke length. The processor circuit can estimate an efficiency of the user. The processor circuit can classify a swimming style of the user. The processor circuit can determine energy expenditure of the user based on the speed, the efficiency, and the style. The processor circuit can also detect glides of the user and adjust the energy expenditure.

Abstract: Devices and related methods for the dynamic correction of spinal deformities are disclosed. The devices and methods are particularly useful for correcting an abnormal curvature of the spine. In one exemplary embodiment, a method for correcting deformity via a spinal implant that can include a polymer between or attached to a top and bottom plate, which can exist in a wedge-shaped configuration in order to apply asymmetric forces to the spinal column, is provided. The implant may be inserted between adjacent vertebrae comprising part of the abnormal curvature, thereby restoring the normal curvature of a spine.

Abstract: In one aspect, the present disclosure relates to a method including obtaining, by a fitness tracking device, a plurality of heart rate measurements of the user over a period of time, wherein the plurality of heart rate measurements can include heart rate data from a heart rate sensor of the fitness tracking device; analyzing, by the fitness tracking device, the plurality of heart rate measurements to determine a rate of change of a heart rate of the user during the period of time; determining, by the fitness tracking device, that the user is experiencing an onset phase if the rate of change of the heart rate during the period of time is greater than zero; determining, by the fitness tracking device, that the user is experiencing a cool-down phase if the rate of change of the heart rate during the period of time is less than zero; estimating, by the fitness tracking device, a first rate of energy expenditure of the user if the user is experiencing an onset phase using an onset calorimetry model; and estimating

Abstract: Aspects of the subject technology relate to electronic devices with pressure sensors. Pressure sensor occlusion may be detected based on a comparison of a variance of pressure data from the pressure sensor with a variance of acceleration data from an accelerometer of the device. If a ratio of the pressure data variance to the acceleration data variance is above a threshold, occlusion may be identified. Data from other sensors in the device or in an external device, or other features of the pressure data, may be used to identify a type of occlusion.

Abstract: Ear buds may have optical proximity sensors and accelerometers. Control circuitry may analyze output from the optical proximity sensors and the accelerometers to identify a current operational state for the ear buds. The control circuitry may also analyze the accelerometer output to identify tap input such as double taps made by a user on ear bud housings. Samples in the accelerometer output may be analyzed to determine whether the samples associated with a tap have been clipped. If the samples have been clipped, a curve may be fit to the samples. Optical sensor data may be analyzed in conjunction with potential tap input data from the accelerometer. If the optical sensor data is ordered, a tap input may be confirmed. If the optical sensor data is disordered, the control circuitry can conclude that accelerometer data corresponds to false tap input associated with unintentional contact with the housing.

Abstract: Ear buds may have optical proximity sensors and accelerometers. Control circuitry may analyze output from the optical proximity sensors and the accelerometers to identify a current operational state for the ear buds. The control circuitry may also analyze the accelerometer output to identify tap input such as double taps made by a user on ear bud housings. Samples in the accelerometer output may be analyzed to determine whether the samples associated with a tap have been clipped. If the samples have been clipped, a curve may be fit to the samples. Optical sensor data may be analyzed in conjunction with potential tap input data from the accelerometer. If the optical sensor data is ordered, a tap input may be confirmed. If the optical sensor data is disordered, the control circuitry can conclude that accelerometer data corresponds to false tap input associated with unintentional contact with the housing.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: Systems and methods are disclosed for tracking physiological states and parameters for calorie estimation. A start of an exercise session associated with a user of a wearable computing device is determined. Heart rate data is measured for a first period of time. An onset heart rate value of the user is determined based on the measured heart rate data, the onset heart rate value associated with a lowest valid heart rate measured during the first period of time. A resting heart rate parameter (RHR) of a calorimetry model is associated with at least one of the onset heart rate value, a preset RHR, and an RHR based on user biometric data. Energy expenditure of the user during a second period of time is estimated based on the calorimetry model and a plurality of heart rate measurements obtained by the wearable computing device during the second period of time.

Abstract: A system and method for improving the accuracy of a user device when generating map/navigation information for display to a user, comprising: obtaining compass heading from a magnetometer of the user device located within a vehicle; adjusting the compass heading based on a mount angle of the user device within the vehicle; obtaining location data from a location sensor of the user device; determining if a course of the vehicle can be reliably determined from the location data; if the course of the vehicle cannot be reliably determined from the location data, determining the orientation of the vehicle using the compass heading but not the course; if the course of the vehicle can be reliably determined from the location data, calculating a course of the vehicle based on the location data and determining the orientation of the vehicle using the course; generating, by a processor, first map/navigation information using the orientation of the vehicle; and displaying, by a processor, the first map/navigation inform

Abstract: Aspects of the subject technology relate to electronic devices with pressure sensors. Pressure sensor occlusion may be detected based on a comparison of a variance of pressure data from the pressure sensor with a variance of acceleration data from an accelerometer of the device. If a ratio of the pressure data variance to the acceleration data variance is above a threshold, occlusion may be identified. Data from other sensors in the device or in an external device, or other features of the pressure data, may be used to identify a type of occlusion.

Abstract: In one aspect, the present disclosure relates to a method including obtaining, by a heart rate sensor of a fitness tracking device, a heart rate measurement of a user of the fitness tracking device; obtaining, by at least one motion sensor, motion data of the user; analyzing, by the fitness tracking device, the motion data of the user to estimate a step rate of the user; estimating, by the fitness tracking device, a load associated with a physical activity of the user by comparing the heart rate measurement with the step rate of the user; and estimating, by the fitness tracking device, an energy expenditure rate of the user using the load and at least one of the heart rate measurement and the step rate.

Abstract: A fitness tracking device configured to be worn by a user obtains a plurality of physical characteristics of the user including a first age and a sex of the user. The fitness tracking device maps each physical characteristic of the user to a corresponding index, wherein the first age of the user is mapped to a first age index of a first age range of a plurality of age ranges, and wherein the sex of the user is mapped to a first sex index. The fitness tracking device selects, from a memory of the fitness tracking device, a first calorimetry model of a plurality of calorimetry models, wherein the first calorimetry model is associated with each corresponding index, including the first age index and the first sex index of the user. The fitness tracking device estimates an energy expenditure rate using the first calorimetry model.

Abstract: In one aspect, the present disclosure relates to a method including obtaining a plurality of heart rate measurements of the user over a period of time; obtaining motion data of the user over the period of time; analyzing the motion data of the user to determine for each of the plurality of heart rate measurements, a corresponding work rate measurement; determining, for each of the plurality of heart rate measurements, a first confidence level; determining, for each corresponding work rate measurement, a second confidence level; and estimating a first energy expenditure rate using the plurality of heart rate measurements; estimating a second energy expenditure rate using the plurality of work rate measurements; and estimating a weighted energy expenditure rate of the user by combining the first energy expenditure rate weighted by the first confidence level and the second energy expenditure rate weighted by the second confidence level.