Abstract: A method and a system for determining the maximum heart rate, called HRmax of a user of in a freely performed physical exercise and using an apparatus with software and memory. An intensity model takes account of, in addition to heart rate, respiration rate and/or kinetics information.

Abstract: The invention relates to a method and a system for determining body's readiness to respond to physical exercise and for providing feedback to a user. In the method the user starts to perform an exercise, an earlier performance level is determined before starting a performance check having steps of: an instant performance level of the user is determined, the earlier performance level is compared to the instant performance level, a readiness index is determined according to the said comparison and optionally with background and/or training history of the user, a feedback is given according to the determined readiness index.

Abstract: A method and system for determining training status of a user from exercises using a device with a heart rate sensor, a processor, memory, an output device and software. The training status is selected from a fixed group of alternatives. Each exercise is monitored using the heart rate sensor. Chosen exercise characteristics of each executed exercise are determined using obtained heart rate data and the determined characteristics of each executed exercise are stored in a memory. The chosen exercise characteristics include values of at least following variables: a date of the exercise, a value depicting physical readiness level for exercise during the exercise, a value depicting a training load of the exercise. When the exercises have been executed, values of selection variables are calculated using the stored exercise characteristics in the memory.

Abstract: The application presents providing next workout recommendation(s) for a user. The current training load for the next workout recommendation is determined based on a present activity class, a phase of the micro-cycle of successive training days and the sum of the training load values for a number of past trainings. The present activity class of the user corresponds to a present fitness level of the user. A total target training load is determined based on the present activity class and the training goal, which relates to maintaining, increasing or increasing fast the fitness level of the user. The phase of the micro-cycle of successive training days for the next workout recommendation is determined by the realized training load value(s) for daily training session(s) of at least one previous day from training history data, as a percentage of the sum of the training load values for a number of past trainings.

Abstract: A method and a system for determining the maximum heart rate, called HRmax of a user of in a freely performed physical exercise and using an apparatus with software and memory. An intensity model takes account of, in addition to heart rate, respiration rate and/or kinetics information.

Abstract: A method and a system for determining the maximum heart rate of a user in a freely performed physical exercise and using an apparatus with software and memory. An intensity model takes account of, in addition to heart rate, respiration rate and/or kinetics-information. The kinetics information depicts change in excess post-exercise oxygen consumption (EPOC), more generally the direction of cumulative physiological disturbance in homeostasis, whether it is at steady state, on-response (rising) or off-response (descending) to decrease the value of the determined maximal heart rate to obtain a result.

Abstract: A method and system for determining anaerobic threshold intensity (AnT) of a user in a freely performed physical exercise. A physiological response of a user is measured by heart rate and measured heart rate values are recorded as heart rate data. An external workload values are recorded and are each associated with one measured heart rate values to form a plurality of data points. The data points are filtered to form accepted data points, which are classified within a plurality of heart rate segments representing a heart rate within an anaerobic threshold (AnT) of the user. A data point with highest probability is stored for each segment. A first probability factor for each accepted data point is calculated. The calculated first probability factor is compared to a stored probability factor in each segment, and the higher probability factor is retained. AnT is calculated using the stored probabilities in each segment.

Abstract: A system of estimating acclimatization to environmental conditions, and providing a corrected fitness level estimates based on said acclimatization level. The environmental conditions are particularly related to heat and altitude. At first previous training history is provided including a plurality of day records, where each day record includes a date stamp and information regarding altitude and optionally temperature and humidity and training history including timestamp and training load data from executed exercises in stored records.

Abstract: A method and system for determining training status of a user from exercises using a device with a heart rate sensor, a processor, memory, an output device and software. The training status is selected from a fixed group of alternatives. Each exercise is monitored using the heart rate sensor. Chosen exercise characteristics of each executed exercise are determined using obtained heart rate data and the determined characteristics of each executed exercise are stored in a memory. The chosen exercise characteristics include values of at least following variables: a date of the exercise, a value depicting physical readiness level for exercise during the exercise, a value depicting a training load of the exercise. When the exercises have been executed, values of selection variables are calculated using the stored exercise characteristics in the memory.

Abstract: The application presents providing next workout recommendation(s) for a user. The current training load for the next workout recommendation is determined based on a present activity class, a phase of the micro-cycle of successive training days and the sum of the training load values for a number of past trainings. The present activity class of the user corresponds to a present fitness level of the user. A total target training load is determined based on the present activity class and the training goal, which relates to maintaining, increasing or increasing fast the fitness level of the user. The phase of the micro-cycle of successive training days for the next workout recommendation is determined by the realized training load value(s) for daily training session(s) of at least one previous day from training history data, as a percentage of the sum of the training load values for a number of past trainings.

Abstract: A method and system for determining training status of a user from exercises using a device with a heart rate sensor, a processor, memory, an output device and software. The training status is selected from a fixed group of alternatives. Each exercise is monitored using the heart rate sensor. Chosen exercise characteristics of each executed exercise are determined using obtained heart rate data and the determined characteristics of each executed exercise are stored in a memory. The chosen exercise characteristics include values of at least following variables: a date of the exercise, a value depicting physical readiness level for exercise during the exercise, a value depicting a training load of the exercise. When the exercises have been executed, values of selection variables are calculated using the stored exercise characteristics in the memory.

Abstract: A method and a system for determining the maximum heart rate, called HRmax of a user of in a freely performed physical exercise and using an apparatus with software and memory means.

Abstract: The invention relates to a method for providing an approximation of a minimum heart rate, (minHR) from collected heart rate data of a user. The method comprises calculating, from heartbeat signal collected from a user, a heart rate (HR) value and an artefact percentage for one or more time periods of the collected heartbeat signal and qualifying data of the time period(s) for which, the user is verified to be awake and immobile, and for which the artefact percentage is under a predetermined value. Data of the other time periods is disqualified. The method further comprises calculating heart rate parameters from the qualified data and applying a function to the heart rate parameters in order to obtain the approximation of minHR.

Abstract: A method and apparatus for determining training status from a group of alternatives from a plurality of exercises, where a user has frequently monitored exercises with at least heart rate being measured by a host process, which outputs selected variables for calculating the training status by a child process.

Abstract: The invention relates to a method and a system for determining body's readiness to respond to physical exercise and for providing feedback to a user. In the method the user starts to perform an exercise, an earlier performance level is determined before starting a performance check having steps of: an instant performance level of the user is determined, the earlier performance level is compared to the instant performance level, a readiness index is determined according to the said comparison and optionally with background and/or training history of the user, a feedback is given according to the determined readiness index.

Abstract: The invention relates to a method and a system for determining body's readiness to respond to physical exercise and for providing feedback to a user. In the method the user starts to perform an exercise, an earlier performance level is determined before starting a performance check having steps of: an instant performance level of the user is determined, the earlier performance level is compared to the instant performance level, a readiness index is determined according to the said comparison and optionally with background and/or training history of the user, a feedback is given according to the determined readiness index.

Abstract: A method and system for determining training status of a user from exercises using a device with a heart rate sensor, a processor, memory, an output device and software. The training status is selected from a fixed group of alternatives. Each exercise is monitored using the heart rate sensor. Chosen exercise characteristics of each executed exercise are determined using obtained heart rate data and the determined characteristics of each executed exercise are stored in a memory. The chosen exercise characteristics include values of at least following variables: a date of the exercise, a value depicting physical readiness level for exercise during the exercise, a value depicting a training load of the exercise. When the exercises have been executed, values of selection variables are calculated using the stored exercise characteristics in the memory.

Abstract: A method and apparatus for determining training status from a group of alternatives from a plurality of exercises, where a user has frequently monitored exercises with at least heart rate being measured by a host process, which outputs selected variables for calculating the training status by a child process.

Abstract: A method and system for determining anaerobic threshold intensity (AnT) of a user in a freely performed physical exercise. A physiological response of a user is measured by heart rate and measured heart rate values are recorded as heart rate data. An external workload values are recorded and are each associated with one measured heart rate values to form a plurality of data points. The data points are filtered to form accepted data points, which are classified within a plurality of heart rate segments representing a heart rate within an anaerobic threshold (AnT) of the user. A data point with highest probability is stored for each segment. A first probability factor for each accepted data point is calculated. The calculated first probability factor is compared to a stored probability factor in each segment, and the higher probability factor is retained. AnT is calculated using the stored probabilities in each segment.

Abstract: A method and system for determining anaerobic threshold intensity (AnT) of a user in a freely performed physical exercise. A physiological response of a user is measured by heart rate and measured heart rate values are recorded as heart rate data. An external workload values are recorded and are each associated with one measured heart rate values to form a plurality of data points. The data points are filtered to form accepted data points, which are classified within a plurality of heart rate segments representing a heart rate within an anaerobic threshold (AnT) of the user. A data point with highest probability is stored for each segment. A first probability factor for each accepted data point is calculated. The calculated first probability factor is compared to a stored probability factor in each segment, and the higher probability factor is retained. AnT is calculated using the stored probabilities in each segment.