Method and an apparatus for determining training status
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.
1. A method for determining a training status of a user from plurality of physical exercises and recovery state measurements using a portable device with a heart rate sensor, the device having a processor, a memory containing runtime and resident memory, and software, the determined training status being selected from a fixed group of alternatives depicting a unique physical condition of the user, comprising:
measuring heart rate data during each exercise using the heart rate sensor and storing heart rate data into a runtime memory;
measuring heart rate data frequently during recovery state measurements using the heart rate sensor and storing heart rate data into a runtime memory;
determining chosen characteristics of each executed physical exercise;
determining chosen characteristics of each of each recovery state measurement; and
storing into a resident memory the determined characteristics of each executed exercise and determined recovery state, respectively after each exercise/recovery state measurement,
wherein the chosen characteristics including values of at least the following variables:
for each physical exercise:
a date stamp of physical exercise; and
a value depicting training load of exercise;
and for each recovery state measurement, respectively:
a date stamp of each recovery state measurement; and
a value depicting instantaneous person's recovery state; and
calculating values of selection variables using the stored characteristics in the resident memory, when the plurality of exercises and recovery state measurements have been executed, and storing calculated values into runtime memory; and
determining the training status using sequential pre-determined selection rules, each rule being connected to one unique variable of said selection variables, wherein each selection rule uses a calculated value of its selection variable to limit a number of remaining alternatives and, after all selection rules have been sequentially used, only one alternative is selected.
2. The method according to claim 1 , wherein the recovery state is depicted by a heart rate parameter calculated using a heart rate variability variable.
3. The method according to claim 1 , wherein the recovery state value is measured during sleep.
4. The method according to claim 1 , wherein there are three selection rules with three selection variables, namely one depicting Heart Rate Variability (HRV) and two variables depicting directly or indirectly Short Training Load (ACUTE) and Short/Long Training Load Ratio (TLR).
5. The method according to claim 1 , wherein the recovery values are personally scaled by taking into account the typical values and range of HRV for each person.
6. The method according to claim 1 , wherein the number of training status alternatives is at least 5, these alternatives comprising at least detraining, maintaining, recovery, overreaching and productive.
7. The method according to claim 1 , wherein an output device is implemented in at least one of the following: a heart rate monitor, a fitness device, a mobile phone, a PDA device, a wrist top computer, a tablet computer or a personal computer.
8. The method according to claim 1 , further comprising a selection of additional information according to at least one additional variable depicting at least one of: number of HRV-data, fitness level (VO2max), anaerobic training effect, training variability or high intensity training count.
9. The method according to claim 1 , wherein a type of exercise is stored as part of the characteristics of each exercise.
10. The method according to claim 9 , wherein at least one selection variable is calculated using data of a same exercise type.
11. The method according claim 1 , wherein values of selected variables of each day are recorded and summed in a sliding window of a plurality of past days, the selected variables including at least a recovery state value, a sum of peaks of training loads, and the recovery state trend being calculated from the daily recovery state values.
12. An apparatus for determining a training status of a user from a plurality of exercises and recovery state measurements, comprising: a device with a heart rate sensor, the device having a processor, a memory including runtime and resident memory and software, the determined training status being an alternative of a fixed group of alternatives each of them depicting a unique physical condition of the user, said software being arranged:
to monitor each exercise using the heart rate sensor;
to determine chosen exercise characteristics of each executed exercise/recovery state measurement; and
to store them in a resident memory,
wherein the chosen exercise characteristics including values of at least:
for each physical exercise:
a date stamp of physical exercise; and
a value depicting training load of exercise;
and for each recovery state measurement:
a date stamp of each recovery state measurement;
a value depicting instantaneous person's recovery state; and
said software is adapted to validate the training status calculation, when the plurality of exercises and recovery state measurements have been executed and calculate values of selection variables using the stored exercise characteristics in the resident memory, and
when called, to determine the training status using sequential pre-determined selection rules, each rule being connected to one unique variable of said selection variables, where each selection rule using a calculated value of its selection variable is limiting the number of remaining alternatives and to select one alternative representing the training status after all selection rules have been sequentially used.
13. The apparatus according to claim 12 , wherein the apparatus is at least one of: a heart rate monitor, a fitness device, a mobile phone, a PDA device, a wrist top computer, a tablet computer or a personal computer.
14. The apparatus according to claim 12 , wherein a dynamic memory in a RAM memory is allocated 100-400 bytes (×8 bits) for calculation of training status in a child process.
15. The apparatus according to claim 12 , wherein the software includes a basic library (ETE) for monitoring the exercises/recovery state measurements and determining characteristics of the plurality of exercises in a host process using a runtime memory and storing the exercise characteristics in a resident memory, and an auxiliary library software (THA) for determining the training status as a child process using characteristics in the resident memory.