Abstract: A system can include a location data module configured to receive location data, the location data including patient location information associated with a plurality patients and care team member location information associated with one or more care team members, and a route module operatively connected to the location data module and configured to determine a visitation route for each of the one or more care team members to visit the plurality of patients based on the location data.

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 physiological attributes of the user. In particular, the wearable strap may be used to monitor heart rate data including a resting heart rate, a heart rate variability, and sleep quality—e.g., to generate a recovery indicator that provides a quantitative assessment of a physical recovery state of the user indicating whether the user is recovered and ready for exercise.

Abstract: A wearable physiological measurement system may include, inter alia, sensors and circuitry for automatically and continually determining a heart rate of a wearer. The system can be charged while worn by the wearer via coupling with a removable modular housing, which may itself provide additional functionality such as a multi-function watch.

Abstract: A physiological monitor switches between a time domain analysis and a frequency domain analysis for determining a heart rate based on objective indicia of signal quality in an acquired heart rate signal.

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: Embodiments provide physiological measurement systems, devices and methods for continuous health and fitness monitoring. A lightweight wearable system is provided to collect various physiological data continuously from a wearer without the need for a chest strap. The system also enables monitoring of one or more physiological parameters in addition to heart rate including, but not limited to, body temperature, heart rate variability, motion, sleep, stress, fitness level, recovery level, effect of a workout routine on health, caloric expenditure. Embodiments also include computer-executable instructions that, when executed, enable automatic interpretation of one or more physiological parameters to assess the cardiovascular intensity experienced by a user (embodied in an intensity score or indicator) and the user's recovery after physical exertion (embodied in a recovery score). These indicators or scores may be displayed to assist a user in managing the user's health and exercise regimen.

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: Embodiments provide physiological measurement systems, devices and methods for cardiovascular intensity measurement. In an aspect, a wearable device receives a time series of heart rate data for a user. The time series of heart rate data can be weighted and summed according to a weighting scheme. The weighted and summed time series of heart rate data can be used to generate an intensity score indicating the cardiovascular intensities experienced by the user during a desired period of time.

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 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: 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 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 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.

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 system uses continuous tracking of sleep activity and heart rate activity to evaluate heart rate variability immediately before transitioning to an awake state, e.g., at the end of the last phase of deep sleep. In particular, a wearable, continuous physiological monitoring system as described herein includes one or more sensors to detect sleep states, the transitions between sleep states, and the transitions from a sleep state to an awake state for a user. This information can be used in conjunction with continuously monitored heart rate data to calculate heart rate variability of the user at the end of the last phase of sleep preceding the user waking up. By using the history of heart rate data in conjunction with sleep activity in this manner, an accurate and consistent recovery score can be calculated based on heart rate variability.