Abstract: A system and a method for recommending a physical routine to a person. The system includes a physical sensor, a biochemical sensor and a processing arrangement. The processing arrangement is configured to measure, via the physical sensor, a first intensity and a corresponding first training impulse of a first physical routine, and a second intensity and a corresponding second training impulse of a second physical routine; determine, via the biochemical sensor, a first level of a biochemical marker associated with completion of the first physical routine and a second level of a biochemical marker associated with completion of the second physical routine; calculate a corresponding first response value and a second response value; compare the calculated first response value and the calculated second response value, and recommend one of the first physical routine and the second physical routine for the person based on the comparison.

Abstract: A method and a system for providing feedback to a user for adjusting sleep pattern of the user. The method includes collecting a set of information related to the user, receiving a set of measurement data related to the user from a wearable electronic device, defining circadian rhythm and duration of sleep of the user, determining sleep scores for a predefined number of days and associating each sleep score with a corresponding go-to-bed time or time of falling asleep of the user. A sleep score is determined for each of the predefined number of days from the collected set of information, the set of measurement data, the circadian rhythm and the duration of sleep of the user. The method further includes analysing the sleep scores and associated go-to-bed time or time of falling asleep of the user to determine an optimum bedtime window for the user and providing feedback to the user based on the analysed sleep scores and the optimum bedtime window.

Abstract: Methods, systems, and devices for restorative moment identification are described. A method may include receiving physiological data associated with a user from a wearable device, the physiological data including heart rate data and temperature data. The method may include identifying that the heart rate data is less than or equal to a heart rate threshold and identifying that the temperature data is within a temperature range of a baseline temperature associated with the user for at least a portion of a time interval. The method may include identifying a restorative moment for the time interval that the user is in a relaxed state based on the heart rate data being less than or equal to the heart rate threshold and the temperature data being within the temperature range of the baseline temperature, and causing a user device to display an indication of the restorative moment.

Abstract: Methods, systems, and devices for sleep staging algorithms are described. A system may receive physiological data associated with a user from a wearable ring device, where the physiological data is collected via the wearable ring device throughout a time interval. The system may input the physiological data into a machine learning classifier, and classify the physiological data, using the machine learning classifier, into at least one sleep stage of a set of sleep stages for at least a portion of the time interval. The system may subsequently cause a graphical user interface (GUI) of a user device to display an indication of the at least one sleep stage of the set of sleep stages based on classifying the physiological data.

Abstract: Methods, systems, and devices for sleep staging algorithms are described. A system may receive physiological data associated with a user from a wearable device, where the physiological data may be collected via the wearable device throughout a time interval. The system may identify a circadian rhythm adjustment model configured to weight the physiological data based on a circadian rhythm associated with the user. The system may input the physiological data and the circadian rhythm adjustment model into a machine learning classifier, and classify the physiological data, using the machine learning classifier, into at least one sleep stage of a set of sleep stages for at least a portion of the time interval, where the classifying is based on the circadian rhythm adjustment model. A graphical user interface (GUI) of a user device may display an indication of the at least one sleep stage based on classifying the physiological data.

Abstract: A method and system for supplemental sleep detection is described. A system may receive data associated with a user from a wearable device worn by the user, and may detect a primary sleep period for the user based on the received data. The system may additionally detect a supplemental sleep period including a duration that exceeds a threshold duration based on the received data. In some implementations, the system may cause a graphical user interface (GUI) of a user device to display an indication of the detected supplemental sleep period, and may receive a confirmation of the supplemental sleep period via the user device and in response to the indication of the detected supplemental sleep period. The system may subsequently generate one or more insights associated with the user based on the primary sleep period and the supplemental sleep period and, in some implementations, in response to the confirmation.

Abstract: A method and a system for providing feedback to a user for adjusting sleep pattern of the user. The method includes collecting a set of information related to the user, receiving a set of measurement data related to the user from a wearable electronic device, defining circadian rhythm and duration of sleep of the user, determining sleep scores for a predefined number of days and associating each sleep score with a corresponding go-to-bed time or time of falling asleep of the user. A sleep score is determined for each of the predefined number of days from the collected set of information, the set of measurement data, the circadian rhythm and the duration of sleep of the user. The method further includes analysing the sleep scores and associated go-to-bed time or time of falling asleep of the user to determine an optimum bedtime window for the user and providing feedback to the user based on the analysed sleep scores and the optimum bedtime window.

Abstract: The present disclosure introduces a method for providing substantially optimal training instructions to a user based on temperature measurements performed by a wearable device. The algorithm determines non-REM sleep phases of the user, measures the maximum temperature of the NREM sleep phase or an averaged value among the maximum values of several NREM sleep phases in a night, and it determines most appropriate training instructions for the user based on that temperature information. Gender and age may also have an effect in the training instruction determinations. Training information and alerts can be given via a smartphone application to the user.

Abstract: A method and system for guiding a user to improve general performance. The system includes a wearable device to measure at least two parameters associated with the user during an activity period, and a computing device operatively coupled to the wearable device, wherein the computing device is operable to: determine a circadian rhythm of the user based on the measured parameters, classify the user into a chronotype class based on the determined circadian rhythm, determine a typical activity schedule for the user based on the measured parameters, determine an optimal time period in a typical day of the user for sleep and at least one of physical action and cognitive action, receive information about an intended activity of the user, analyse whether the intended activity is within the optimal time period, and guide the user on carrying out the intended activity.

Abstract: The present invention introduces a method for guiding an optimal stretching time to a user who has a wearable electronic device and a mobile communication device for measuring a set of measurement data comprising activity data of the user. The determination logic, implemented e.g. in a form of a server, takes age and gender into account, and determines a stretching index based on the activity of the user. The optimal stretching time may be alerted, with stretching guidance, to the user. Sleep can be taken into account as well. The system measures whether the actual stretching is done. Sleep is further analyzed, so the effect of the stretching can be monitored and this information can be given back to the user via the mobile communication device. Stretching guides can be updated as well. The wearable electronic device can be a ring device.

Abstract: A method and a system for providing feedback to a user for adjusting sleep pattern of the user. The method includes collecting a set of information related to the user, receiving a set of measurement data related to the user from a wearable electronic device, defining circadian rhythm and duration of sleep of the user, determining sleep scores for a predefined number of days and associating each sleep score with a corresponding go-to-bed time or time of falling asleep of the user. A sleep score is determined for each of the predefined number of days from the collected set of information, the set of measurement data, the circadian rhythm and the duration of sleep of the user. The method further includes analysing the sleep scores and associated go-to-bed time or time of falling asleep of the user to determine an optimum bedtime window for the user and providing feedback to the user based on the analysed sleep scores and the optimum bedtime window.

Abstract: A method and a system for assessing readiness of a user, the method including obtaining the user's movements; using the obtained user's movements to determine a nature of the period, wherein the nature of the period is selected from an activity period and a rest period; measuring at least one biosignal of the user during the rest period; determining a rest summary for the rest period, based on the measured at least one biosignal and at least one biosignal of a previous rest period; determining an activity summary for the activity period, based on the obtained movements of an activity period and obtained movements of at least one previous activity period; determining a body response summary based on the rest summary and the activity summary; and calculating a readiness score based on the body response summary and a previous body response summary, whereby the readiness score indicates a level of readiness of the user.

Abstract: The present invention discusses a system and method for defining an optimal wakeup time with an alarm, which method takes into consideration at least two persons. Sleep monitoring devices, such as health rings or bed sensors, measure parameters of the sleepers, and a server determines sleeping phases from the measurement results. In that regard, skin temperature, heart rate and amount of motion can be tracked with the ring. The analysis combines at least two persons and sets rules so that no-one is preferably woken from a deep sleep phase. The determined alarm time is a given time period before the final alarm deadline. An optimal alarm time is calculated in the server, and the alarm is triggered in a mobile device, through the wearable ring, or by another alarming device or means.

Abstract: Disclosed is a method for monitoring activity of a subject and a monitoring device therefor. The method comprises, detecting the direction of the monitoring device with respect to a hand of a subject by measuring a signal of y-axis for a time ty and averaging the signal measured. The method further comprises, detecting the hand on which the subject carries the monitoring device by measuring a signal of the x-axis for a time tx and averaging the signal measured. The method also comprises, using the obtained information to optimise the activity monitoring, and further to determine a main axis of motion of the monitoring device and direction of the main axis of motion in order to improve recognition of the activity of the subject.

Abstract: The present invention discusses a system and method for defining an optimal wakeup time with an alarm, which method takes into consideration at least two persons. Sleep monitoring devices, such as health rings or bed sensors, measure parameters of the sleepers, and a server determines sleeping phases from the measurement results. In that regard, skin temperature, heart rate and amount of motion can be tracked with the ring. The analysis combines at least two persons and sets rules so that no-one is preferably woken from a deep sleep phase. The determined alarm time is a given time period before the final alarm deadline. An optimal alarm time is calculated in the server, and the alarm is triggered in a mobile device, through the wearable ring, or by another alarming device or means.

Abstract: A method, apparatus, and a computer program for monitoring a fitness exercise are described. A plurality of heart-rate variability values and a plurality of exertion parameter values are measured during an exercise measured. The heart rate variability values correlate with the exertion parameter values through a human physiological mechanism, and the exertion parameter values characterize the physical exertion of the exercise. A mathematical correspondence is then constructed from the plurality of measured heart rate variability values and associated exertion parameter values. The mathematical correspondence describes correlation between the heart rate variability values and the exertion parameter values and the user's physiological state during the exercise. Then, the physical exertion of the exercise is monitored by applying the mathematical correspondence.

Abstract: A system that monitors user activity includes a wrist device including a curved body and an electronic circuitry supported by the body. The electronic circuitry includes a first set of light emitting diodes arranged in a matrix form and forming a display unit, at least one motion sensor configured to measure physical motion caused by a user to the wrist device, and at least one processor configured to acquire motion measurement data from the at least one motion sensor, to process the motion measurement data into a motion activity metric, and to cause the display unit to display the motion activity metric. The at least one processor is further configured to acquire heart activity measurement data from a heart activity sensor, to process the heart activity measurement data into a heart activity metric, and to cause the display unit to display the heart activity metric.

Abstract: Disclosed is a method for defining a balance between physical activity and rest for a user. The method comprises collecting sensor data indicative of a measure of activity performed and rest taken by the user as a function of time; analyzing the sensor data to distinguish sedentary stages from stages of activity or rest; assigning a level to a given stage of activity or rest; evaluating a plurality of activity-rest parameters for the user; and calculating an activity-rest score from the plurality of activity-rest parameters, so as to provide a feedback indicating a status of the balance between the physical activity and the rest.

Abstract: A method provides a service in a Bluetooth device. The method includes initiating, in a first Bluetooth device connection establishment with a second Bluetooth device; carrying out a service discovery procedure with the second Bluetooth device, during which at least one unique service identifier associated with a personal training data service is exchanged between the first Bluetooth device and the second Bluetooth device, wherein the personal training data service comprises at least one personal training data item processed by the first Bluetooth device and/or the second Bluetooth device during a physical exercise; and after the service discovery procedure, transferring at least one frame with the second Bluetooth device, wherein the frame comprises an information element specifying personal training data and a command information element specifying how to process the personal training data.

Abstract: A method and a system for assessing readiness of a user, the method including obtaining the user's movements; using the obtained user's movements to determine a nature of the period, wherein the nature of the period is selected from an activity period and a rest period; measuring at least one biosignal of the user during the rest period; determining a rest summary for the rest period, based on the measured at least one biosignal and at least one biosignal of a previous rest period; determining an activity summary for the activity period, based on the obtained movements of an activity period and obtained movements of at least one previous activity period; determining a body response summary based on the rest summary and the activity summary; and calculating a readiness score based on the body response summary and a previous body response summary, whereby the readiness score indicates a level of readiness of the user.