Abstract: A method, device and a computer program product for determining a training load distribution of a user is provided. Heart rate is continuously measured by a heart rate sensor. An aerobic training effect and load are calculated using intensity values and divided into categories of Aerobic Low and Aerobic High. An anaerobic training effect and load are calculated using determined characteristics related to high intensity periods of an exercise.

Abstract: An apparatus and method for determining injury risk from plurality of exercises using a device with a heart rate sensor, a processor, memory including a resident memory, an output device and software. For example the method may: determine and store values of Training load of each exercise in the resident memory obtaining a register, perform a HRV-based Recovery Test and storing Recovery values in the register, calculate indices depicting Short Term Training Load, ratio of Short Term Training Load to Long Term Training Load, and Recovery, calculate weighting factors for each said index, correct each index with corresponding weighting factor to obtain weighted indices, calculate a value of the Injury Risk using the weighted indices, and display the value of Injury Risk.

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 improving recognition of anaerobic sections of exercise and to providing feedback on training load or training effect reflecting energy systems used and trained during exercise. The method determines an ‘oxygen debt’ like cumulative physiological sum (usually training effect TE as EPOC value) brought on by a change in a body homeostasis and its aerobic and anaerobic values. Particularly anaerobic value may be determined by a procedure, where a total EPOC (or TRIMP) is determined as a total sum and an aerobic part calculated in a known manner, is deducted from the total sum.

Abstract: A method, device and a computer program product for determining a training load distribution of a user is provided. Heart rate is continuously measured by a heart rate sensor. An aerobic training effect and load are calculated using intensity values and divided into categories of Aerobic Low and Aerobic High. An anaerobic training effect and load are calculated using determined characteristics related to high intensity periods of an exercise.

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 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: An apparatus and method for determining injury risk from plurality of exercises using a device with a heart rate sensor, a processor, memory including a resident memory, an output device and software. For example the method may: determine and store values of Training load of each exercise in the resident memory obtaining a register, perform a HRV-based Recovery Test and storing Recovery values in the register, calculate indices depicting Short Term Training Load, ratio of Short Term Training Load to Long Term Training Load, and Recovery, calculate weighting factors for each said index, correct each index with corresponding weighting factor to obtain weighted indices, calculate a value of the Injury Risk using the weighted indices, and display the value of Injury Risk.

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 improving recognition of anaerobic sections of exercise and to providing feedback on training load or training effect reflecting energy systems used and trained during exercise. The method determines an ‘oxygen debt’ like cumulative physiological sum (usually training effect TE as EPOC value) brought on by a change in a body homeostasis and its aerobic and anaerobic values. Particularly anaerobic value may be determined by a procedure, where a total EPOC (or TRIMP) is determined as a total sum and an aerobic part calculated in a known manner, is deducted from the total sum.

Abstract: The invention relates to method and system for controlling a training plan for a user having a chosen aim for training, where at least one parameter describing physical characteristics of the user is determined, and a training plan consists of plurality of days, each day having one or more training sessions or rest, and each performed and coming session having a training load described by one or more parameters a training template is determined according to the aim and the said one or more parameters describing physical characteristics, each training template having a cumulative training load target according to the said parameter and the chosen aim and consisting of one or more training sessions or rest in each day, each training session of the template having a pre-selected training load, and an adapting window is determined, the adapting window consisting of a plurality of days, which include one or more previous sessions and one or more coming sessions according to the training template, and training l

Abstract: The invention relates to method and system for controlling a training plan for a user having a chosen aim for training, where at least one parameter describing physical characteristics of the user is determined, and a training plan consists of plurality of days, each day having one or more training sessions or rest, and each performed and coming session having a training load described by one or more parameters a training template is determined according to the aim and the said one or more parameters describing physical characteristics, each training template having a cumulative training load target according to the said parameter and the chosen aim and consisting of one or more training sessions or rest in each day, each training session of the template having a pre-selected training load, and an adapting window is determined, the adapting window consisting of a plurality of days, which include one or more previous sessions and one or more coming sessions according to the training template, and training l