Abstract: A wearable physiological monitoring device is configured to determine a wearer's sleep intention. In particular, the device evaluates activity that might be objectively associated with awaking from sleep in order to distinguish between a wearer's intention to end sleep and transitory stirring or other intermittent activity occurring in the context of a longer sleep interval. By evaluating sleep intention more accurately in this manner, the device can advantageously request sleep analysis from a remote server in those instances where a user intends to end a period of sleep (so that this data can be available to the user more quickly), while avoiding unnecessary or redundant server-side processing of sleep data in those instances where a user intends to continue sleeping.

Abstract: Physiological parameters such as respiratory rate and/or heart rate variability can be measured over time for a user and correlated to physiological and/or hormonal cycles such as the menstrual cycle. By determining the phase of such a cycle in this manner, an automatic coach for the user can recommend phase-specific adjustments to activities such as sleep and exercise.

Abstract: Disclosed herein is a device for continuous physiological monitoring as well as systems and methods for interpreting data from such a device. The systems and methods may include automatically detecting, assessing, and analyzing exercise activity, physical recovery states, sleep states, and the like. The acquisition of continuous physiological data may facilitate automated recommendations concerning changes to sleep, recovery time, exercise routines, and the like.

Abstract: Embodiments provide physiological measurement systems, devices and methods for continuous health and fitness monitoring. A wearable strap may detect reflected light from a user's skin, where data corresponding to the reflected light is used to automatically and continually determine a heart rate of the user. The wearable strap may monitor heart rate data including heart rate variability, resting heart rate, and sleep quality. The systems may include a processing module that generates an indicator of physical recovery based on the heart rate data. The recovery indicator may be used to determine strain related to an exercise routine, qualitative information on the user's health, whether to alter a user's exercise plan, and so forth.

Abstract: A wearable device supports continuous wearability and operation with a supplemental set of removable and replaceable batteries that recharge a first set of batteries powering the device. In an aspect, the wearable system includes a head portion coupled to an appendage of a user, where the head portion includes an electronic system powered by a first set of batteries, and a modular housing releasably engageable to the head portion that includes a second set of batteries. In this manner, the modular housing can be removed and recharged independent from the head portion, and then recoupled to the head portion to recharge the first set of batteries. Thus, in an aspect, the first set of batteries can continuously power the electronic system without a need for removal of the head portion. Such a system can be particularly advantageous for continuous, uninterrupted health and fitness monitoring.

Abstract: Disclosed herein is a device for continuous physiological monitoring as well as systems and methods for interpreting data from such a device. The device may support intelligent selection from among two or more different modes for heart rate detection. In addition, the acquisition of continuous physiological data facilitates automated recommendations concerning changes to sleep, recovery time, exercise routines and the like.

Abstract: A model of data quality is derived for physiological monitoring with a wearable device by comparing data from the wearable device to concurrent data acquisition from a ground truth device such as a chest strap or electrocardiography (EKG) heart rate monitor. With this comparative data, a machine learning model or the like may be derived to prospectively evaluate data quality based on the data acquisition context, as determined, for example, by other sensor data and signals from the wearable device.

Abstract: A wearable optical device embedded in a garment is described. The optical device is, in some embodiments, an optical sensor for optically detecting parameters of interest within muscle, such as during physical activity or when at rest. The parameters of interest include oxygenation level and/or hemoglobin concentrations in some situations. The detected parameters, such as oxygenation level, may be used to assess physical performance, such as the extent to which the muscle is utilizing aerobic or anaerobic processes. The garment is a compression garment in some embodiments to couple the optical device to a subject.

Abstract: A wearable optical device is described for optically detecting parameters of interest within muscle, such as during physical activity or when at rest. The parameters of interest include oxygenation level and/or hemoglobin concentrations in some situations. The detected parameters, such as oxygenation level, may be used to assess physical performance, such as the extent to which the muscle is utilizing aerobic or anaerobic processes. Methods for determining the parameters of interest, such as oxygenation level, from the detected optical signals are also described, and feedback may be provided to a user.

Abstract: A wearable optical device is described for optically detecting parameters of interest within muscle, including oxygenation level and/or hemoglobin concentrations. Detected parameters may be used to assess physical performance, such as the extent to which muscle is utilizing aerobic or anaerobic processes. The wearable optical device may include a pressure sensitive strap. Pressure provided by the strap may affect properties of tissue or sensor measurement, for example, by occluding blood flow or mechanically distorting measured tissue. Pressure sensors may be included in the strap, and may be used, for example, to: examine the heterogeneity of a pressure distribution of the strap, allowing a user to manage pressure consistency throughout measurements using the optical device; determine if pressure affects measurements taken by the optical device; and/or manage levels of blood flow restriction, allowing a user to perform exercises with lower levels of oxygen delivery, such as hypoxic training.

Abstract: A variety of techniques are used automate the collection and classification of workout data gathered by a wearable physiological monitor. The classification process is staged in order to correctly and efficiently characterize a workout type. Initially, a generalized workout event is detected using motion and heart rate data. Then a location of the monitor on a user is determined. An artificial intelligence engine can then be conditionally applied (if a workout is occurring and a suitable device location is detected) to identify the type of workout. In addition to improved speed and accuracy, a workout detection process implemented in this manner can be realized with a sufficiently small computational footprint for deployment on a wearable physiological monitor.

Abstract: A wearable optical device is described for optically detecting parameters of interest within muscle, such as during physical activity or when at rest. The parameters of interest include oxygenation level and/or hemoglobin concentrations in some situations. The detected parameters, such as oxygenation level, may be used to assess physical performance, such as the extent to which the muscle is utilizing aerobic or anaerobic processes. Methods for determining the parameters of interest, such as oxygenation level, from the detected optical signals are also described, and feedback may be provided to a user.

Abstract: A physiological monitoring device controls an optical signal acquisition system within a number of discrete operating states, each providing values for controllable parameters such as illumination intensity for a light source and the gain for an optical detector. Using this technique, a small number of operating states may be defined, such as operating states that are known to work well within expected use scenarios. This approach advantageously facilitates optimal or near optimal operation across a range of most likely use cases while avoiding complex or continuous optimization problems. The list of operating states may further be prioritized so that a best operating state can be selected based on, e.g., signal quality or environmental conditions.

Abstract: A variety of techniques are used automate the collection and classification of workout data gathered by a wearable physiological monitor. The classification process is staged in order to correctly and efficiently characterize a workout type. Initially, a generalized workout event is detected using motion and heart rate data. Then a location of the monitor on a user is determined. An artificial intelligence engine can then be conditionally applied (if a workout is occurring and a suitable device location is detected) to identify the type of workout. In addition to improved speed and accuracy, a workout detection process implemented in this manner can be realized with a sufficiently small computational footprint for deployment on a wearable physiological monitor.

Abstract: Embodiments provide physiological measurement systems, devices and methods for continuous health and fitness monitoring. A wearable strap may detect reflected light from a user's skin, where data corresponding to the reflected light is used to automatically and continually determine a heart rate of the user. The wearable strap may include a motion sensor that is used to determine a motion status of the user. Based upon the motion status of the user, the system may activate light emitters on the wearable strap to determine the heart rate of the user.

Abstract: Continuous monitoring of a plurality of physiological data may be used for health and fitness improvements for a user. To this end, a physiological monitoring and measurement device may include a wearable strap that receives heart rate data for a user including a time series of heart rate data, a maximum heart rate, and a resting heart rate. A processor may transform the heart rate data into a time series of heart rate reserve data that is weighted, e.g., to account for cardiovascular efficiencies at different intensity levels, to provide a weighted time series of heart rate reserve values. An intensity score that provides an indicator of cardiovascular intensity for an exercise routine may be generated from the weighted time series of heart rate reserve values and displayed to the user on the wearable strap.