Methods, systems, and devices for temperature analysis are described. The method may include receiving physiological data associated with a user collected via a first set of sensors of a wearable device. The physiological data may include skin temperature data. The method may include receiving surrounding temperature data associated with an environment surrounding the user. The surrounding temperature data may be collected via the first set of sensors, a second set of sensors, or both. The method may additionally include identifying one or more physiological characteristics associated with the user based at least in part on a comparison of the skin temperature data and the surrounding temperature data, and causing a graphical user interface (GUI) of a user device to display an indication of the one or more physiological characteristics, a message or alert associated with the one or more physiological characteristics, or both.

Aspects relate to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

Aspects relate to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

Techniques are provided for tracking heartrate metrics using different operating modes associated with different contexts of a wearable device. For example, a heartrate sensor of the wearable device may be operated in a first operating mode when an activity is being tracked within an application session of a particular application. The heartrate sensor may be operated in a second operating mode after detecting conclusion of the activity within the activity session (e.g., during sedentary time).

An estimation system includes: a first sensor that detects a first amount of activity that is an amount of activity of a subject in a room; a second sensor that detects a second amount of activity that is an amount of activity of the subject on a bed in the room; and an estimation device that estimates at least one of a position and an action of the subject in association with a position in the room based on the first amount of activity detected by the first sensor and the second amount of activity detected by the second sensor, and outputs an estimation result obtained from the estimation. The first sensor and the second sensor are sensors other than two-dimensional image sensors.

A method of providing workout training for a user of an activity tracking system includes displaying a plurality of training plan options to the user on a screen of a personal electronic device, and then receiving a selected training plan option from the user. Selected workout day options are received from the user and the system generates a training schedule for the user based on the selected training plan and the selected workout day options. One or more reminders identify the type of workout for the scheduled day and an option to accept or reject the workout. When the user selects the option to accept the workout, the workout goal associated with the scheduled workout is displayed. The method further includes determining progress toward the workout goal based on the received workout data, and displaying an indicator of progress toward the workout goal on the screen during the workout.

A driving assistance system and a driving assistance method are provided. The driving assistance system includes a physiological information sensing system, an external physical symptom detection system, and a processing device. The physiological information sensing system is configured to sense physiological information of a driver. The external physical symptom detection system is configured to detect an external physical symptom of the driver. The processing device is coupled to the physiological information sensing system and the external physical symptom detection system. When the physiological information of the driver and the external physical symptom of the driver are abnormal, the processing device initiates an emergency procedure.

A method for monitoring health of a subject based on a physiological response to physical exertion, by processing circuitry of a medical device system, is described that includes detecting a plurality of exertion events of the subject based on a first sensed signal that varies as a function of movement of the subject. The method further includes determining a response of a physiological parameter of the subject to the exertion event for each of the detected exertion events based on second sensed signal that varies as a function of the physiological parameter. The method further includes determining that a change in the responses over time crosses threshold and generating an alert to a user based on the determination that the change crosses the threshold.

The invention relates to a system (4) for estimating a fertility status of a woman, particularly for determining a conception probability of a woman, the system (4) comprising:—A wearable device (2A, 2B), comprising at least one sensor (201, 203, 204) configured to record at least one physiological signal from a woman wearing the wearable device (2A, 2B) and to generate sensor data from the at least one physiological signal, wherein the wearable device (2A, 2B) is configured and arranged to provide the sensor data to—An evaluation system (1) configured and arranged to receive and process the sensor data from the wearable device (2A, 2B), wherein the evaluation system (1) is further configured and arranged to classify the sensor data into at least a first group and a second group, wherein the first group is associated to sensor data indicative of a woman having a high fertility status and wherein the second group is associated to sensor data indicative of a woman having a low fertility status.

The invention generally relates to clinical monitoring of patient data. Embodiments provide a system comprising a processor for performing a method and/or computer-implemented method. In certain embodiments the method determines an intervention recommendation for a patient and may comprise analysing patient need data and intervention data to determine the intervention recommendation. In other embodiments, the method monitors, and/or facilitates monitoring of, the monitoring of a patient. The method may comprise receiving providing patient data to a monitor via a user interface on a computing device, monitoring activity and/or one or more actions of the monitor on the user interface, analysing monitoring data, and effecting an action based on the analysis of the monitoring data and/or generating a notification suggesting an action and sending the notification to the monitor based on the analysis of the monitoring data.