METHOD AND SYSTEM FOR DETERMINING THE FITNESS INDEX OF A PERSON

Abstract

The invention relates to a method and system for determining the cardiorespiratory fitness level of a person, with the aid of freely performed exercise, in which training: the physiological intensity of the person is measured periodically during the exercise session, the external work output of the exercise session is measured simultaneously relative to the measured intensity, from each period's measured intensity value and external work output, the representativeness of the values measured is determined, in order to determine the fitness level using the following criteria: the physiological intensity should be stabilized relative to the external work output, the external work output should be within a selected range, the physiological intensity should be greater than a selected lower limit, in which case, a fitness level estimate is defined for each accepted period as well as a fitness from several estimates.

Claims

1. A method for determining the cardiorespiratory fitness level of a person, with the aid of freely performed exercise, comprising: measuring by a first sensor, a physiological intensity of the person during the exercise session in periods and storing each measured physiological intensity in computation registers; measuring by a second sensor an external work output of the exercise session simultaneously relative to the measured physiological intensity on each period, and storing each measured external output in the computation registers; determining by an assembly built around a central processing unit (CPU), at each period whether the physiological intensity has stabilized relative to the external work output on the measured period in order to accept the period using a following criteria: the physiological intensity is stabilized relative to the external work output, and the external work output is within a selected range; defining by the assembly built around the central processing unit, a fitness level estimate for each accepted period using a modeled function by entering into it the relative heart rate and external work of the accepted segment and the stored physiological intensity and the stored measured external output in the computation registers, and storing each defined fitness level estimate as accepted data points; counting the total duration/number of accepted periods; and if said total duration/number exceeds a selected time/value, computing by the assembly built around the central processing unit, a fitness index with the aid of the fitness level estimates in the accepted data as an average with the aid of the defined fitness level estimates, if the total duration/number of accepted periods exceeds a selected time/value.

2. The method according to claim 1, wherein a variable depicting the change in cumulative homeostasis, is calculated continuously, and the value of the variable depicting homeostasis should be increasing, in order for the period to be accepted.

3. The method according to claim 1, wherein each value of the fitness level (FIn) is obtained from the modelled function by entering into it the relative heart rate and external work of the accepted segment.

4. The method according to claim 1, wherein a sum of energy consumption kcal is calculated by steps of: correcting heartbeat interval data by automatic error correction, RR data being always between two consecutive heartbeats; calculating respiratory frequency information from the heartbeat interval data; calculating heart rate per minute from the heartbeat interval data; converting the heart rate to % of the person's maximum heart rate, using the person's maximum heart rate, where the maximum heart rate is defined on the basis of the person's age, if the person does not know it directly; calculating the on/off kinematic information (loading stage) on the basis of the respiratory frequency and % HRmax; calculating % VO2max or METmax intensity as percentages relative to the person's maximum, where the RQ (respiratory quotient) value is calculated giving a ratio of fats and carbohydrates as energy sources; calculating the RQ relates to a known way to calculate energy consumption on the basis of oxygen consumption, wherein oxygen consumption (litre/minute) is multiplied by five, giving the energy consumption in calories; converting the relative intensity % VO2max to absolute oxygen consumption by multiplying it by the person's VO2max (maximum oxygen consumption), wherein if the person does not know their VO2max value, calculating it using Jackson et al.'s 1990 equation, on the basis of the person's background data, or obtaining VO2max value on the basis of an automatic fitness test; calculating a calorific equivalent is calculated telling on the basis of the RQ value how much energy is produced per litre of oxygen consumed; calculating the momentary energy consumption kcal/min; and calculating the sum of energy consumption kcal is calculated from plurality of momentary.

5. A system for determining the level of the cardiorespiratory fitness level of a person, with the aid of freely performed exercise, comprising: an interface device containing input devices for entering optional user-specific starting parameters before training, and a feedback device for providing feedback; a memory register for recording the values of the said parameters and the calculation variables; first means for measuring and recording a variable proportional to physiological intensity in periods and for storing each measured physiological intensity in the memory register; second means for registering and recording external work output simultaneously relative to the measured physiological intensity on each period, and storing each measured external output in the memory register; third means for determining whether the physiological intensity has stabilized relative to the external work output on the measured period in order to accept the period; fourth means for determining the representativeness of the values of the intensity and external work recorded from simultaneous periods, in order to determine an accepted period in terms of fitness level, where the representative periods are those periods that have the following properties: the physiological intensity must have stabilized relative to the external work output, the external work output must be within a preselected range, and the physiological intensity must be greater than a set criterion (x % HRmax); and fifth means for defining a fitness-level estimate for each accepted period, using a modelled function and the stored physiological intensity and stored measured external output in the memory register, and for storing each defined fitness level estimate as accepted data and to define a fitness index in the memory register as an average of the defined fitness level estimates 2.

6. The system according to claim 5, wherein the system includes means for calculating continuously a variable, depicting the change in cumulative homeostasis, in which case the fourth means are arranged to accept periods, in which the variable depicting the change in homeostasis is increasing.

7. The system according to claim 5, further comprising: means to determine the user's activity class, with the aid of initial data and a defined fitness index, using preselected criteria.

8. The system according to claim 7, wherein the said preselected criterion for determining the activity class comprises a 3-dimensional table with the following variables: sex, age, and fitness index.

9. The system according to claim 5, wherein the external work output is arranged to be determined on the basis of running speed and slope.

10. The system according to claim 5, wherein the system is arranged to perform updating of the fitness index after each training session.

11. The system according to claim 10, wherein the system is arranged to calculate the fitness index from two or more training sessions and to weight the fitness index of each training session according to how many accepted periods are found from the training session.

12. The system according to claim 5, wherein the system is arranged to calculate the energy consumption during training.

13. The system according to claim 5, wherein the system is arranged to calculate the training effect (TE) caused by the training.

14. The system according to claim 5, wherein the system is arranged to define a training program according to the calculated fitness index.

15. The system according to claim 7, wherein the system includes means to determine the user's activity class, with the aid of initial data and a defined fitness index, using preselected criteria.

Description

DESCRIPTION OF THE DRAWINGS

[0035] FIG. 1 shows a flow diagram of a system monitoring a user's physical state,

[0036] FIG. 2 shows the system of FIG. 1 applied to guiding training,

[0037] FIG. 3 shows graphically the determining of the fitness level,

[0038] FIG. 4 shows a flow diagram in the calculation of energy consumption,

[0039] FIG. 5 shows a flow diagram in the calculation of training effect,

[0040] FIG. 6 shows a set of curves for determining training effect,

[0041] FIG. 7 shows a way to calculate a fitness index, and

[0042] FIG. 8 shows a block diagram of the system in a wristop device.

DETAILED DESCRIPTION OF THE INVENTION

[0043] According to FIG. 1, in the system according to the invention, additional attention is paid to the start-up 1, compared to the start-up 1 of conventional use. After the loading 2 of the program and the initiation of the registers, during the first operating session the optional default values are generated, point 3. Later, loading 2 the program leads directly to processing 4 of the computation registers, in which at the same time measurement 5 of intensity and measurement 6 of external work output are initiated, for example (position and altitude data obtained from a GPS service). The computation registers contain continuous real-time information on the user's intensity and external work output. The user's intensity is usually the measured heart rate value. The external work output can be obtained in many ways, depending on the kind of the exercise and the devices used. A GPS device used in connection with wristop devices provides altitude data, which is one alternative. The altitude data is optional and is not necessary if the exercise session takes place on level ground. The exercise device, such as, for example, a bicycle ergometer, can provide the external work output directly.

[0044] In a preferred embodiment, after initiation of the program has been commenced, on the first time it asks the user for external data, such as sex, age, weight, and height. Alternatively, these too are default values, which the user corrects if they wish.

[0045] Conventionally, the device has some selected operating mode 7, i.e. manner of use, which aims at some desired end result, for example a selected level of energy consumption, and provides feedback 9 on it.

[0046] Because particularly the fitness level is required in the calculation of many of the target variables, it is calculated automatically with the aid of calculation devices 8 belonging to the system. Other data, such as maximum heart rate HRmax and the activity class, are preferably updated in the same way.

[0047] In FIG. 2, the usual operating mode 7 of FIG. 1 is exercise guidance. The target of the exercise can be, for example, achieving a selected training effect, or exercise for reducing weight. In order to achieve the target, the user is provided with continuous feedback, i.e. whether the intensity is suitable or too high/low for achieving the target within the set time. The guidance feedback is calculated on the basis of the register data at point 10. The provision of the guidance feedback 11 is checked by a conditional statement 11, if the exercise has been completed. If the exercise is still under way, a return is made to the calculation of the guidance feedback, otherwise exit to the end 12 of the routine. In FIG. 2, it should be noted that the automatic update routine (8, 8) can also obtain a parameter value from the exercise, which is automatically updated in the computation register. This can be, for example, the value of the fitness index, which is calculated only after the exercise and not continuously.

[0048] FIG. 3 illustrates the calculation of the fitness level value by means of a preferred method. The graph in the upper part of the figure shows the momentary speed (km/h) in running exercise and its mean value as the exercise proceeds. In the lower part of the figure, the relative heart rate value % HRmax (0-100% of the maximum heart rate value), the altitude in metres, and the computed fitness level estimates (FI.sub.n) (VO.sub.2max ml/kg/min), calculated in five-second intervals, are shown on the same time scale. At about four minutes, the acceptable data are sufficient and there is a thick line in the graph showing the fitness level computed from the points e obtained. Each value of the fitness level (FI.sub.n) is obtained from the modelled function f(W, Int) by entering into it the relative heart rate (Int) and external work (W) of the accepted segment. The modelled function f(W, Int) is obtained with the aid of numerous test exercise sessions performed by test persons. The exercise sessions of the selected group were monitored for a period of several months and at regular intervals their fitness level was measured using a clinical method. From the data obtained and previously known information on the relation between the external work output and oxygen consumption, a modelled function depicting fitness level was formed, with heart rate and external work as the variables. The data collected also included sex, age, and weight, by means of which the modelled function can be focussed more precisely on each user.

[0049] The calculation of the fitness level estimate from simultaneous physiological-intensity and external-work values is computed, in one embodiment, as follows. It is generally known, that, by comparing the HRmax heart rate the theoretical work output and in turn by extrapolating the maximum heart rate, a rough estimate of m the fitness level can be obtained.

[0050] In the literature, a basic equation is known for running exercise:

VO.sub.2max (ml/kg/min)=11.1*speed_ms+5.3333

[0051] Here, the following equation is derived from it, which takes slope into account:

VO.sub.2max=(c1*hr/maximal_hr+(1+c1))*(11.1*(c2*angled+1)*speed_ms+5.3333)

VO.sub.2max ml/kg/min, the momentary VO.sub.2max value i.e. estimate hr BPM instantaneous, momentary heart rate level maximum hr BPM, the person's background parameter (maximum heart rate level)
angles in radians, momentary running angle
speed_ms m/s, momentary running speed
c1, c2, parameters optimized from empirical material

[0052] A corresponding equation is created for each form of external work output, in such a way that the calculated VO.sub.2max corresponds to the real value.

Example of Application 1 (FIG. 4). Calculation of Energy Consumption

[0053] Automatic determining of the fitness level can be used, for example, in the calculation of energy consumption. The calculation of energy consumption generally requires the person's age, height, weight, sex, and the activity class that depicts the level of the person's physical activity. On the basis of these data, it is possible to estimate, using, for example, the equation developed by Jackson et al. (1990), the person's fitness level, i.e. the maximum oxygen consumption (VO.sub.2max or METmax), which can be used in calculating the energy consumption, see FIG. 4.

[0054] In an automatic system, a person can only be asked, for example, their age, sex, and weight, so that the rest of the person's background data are set as certain default values, on the basis of which calculation of VO.sub.2max takes place using the aforementioned Jackson equation. On the basis of age, it is possible to use the traditional equation to calculate the maximum heart rate 210(age*0.65)=maximum heart rate HRmax, which is the necessary variable for performing a fitness test. After this, VO.sub.2max is computed from exercise performed by the person, which gives a more precise value for the original estimate of VO.sub.2max. This more precise estimate of VO.sub.2max is then used in the calculation of the energy consumption.

[0055] Age and weight can also be preset, in which case the person will not need to enter any personal background data. The automatically calculated and updated VO.sub.2max keeps the system accurate.

[0056] Oxygen consumption can also be calculated in a corresponding manner to energy consumption.

[0057] FIG. 4 shows an example of the computation model for energy consumption, in which the VO.sub.2max value calculated automatically from exercise sessions reduces or entirely eliminates the entering of the personal background data set at the start. Thus the product is considerably easier to start up, and in addition the product always produces m accurate information on energy consumption, even though the person's fitness changes. [0058] 1. RR data, i.e. a time series of the time always between two consecutive heartbeats. [0059] 2. The heartbeat interval data is corrected by automatic error correction. [0060] 3 Respiratory frequency information is calculated from the heartbeat interval data. [0061] 4. The heart rate per minute is calculated from the heartbeat interval data. [0062] 5. The heart rate is converted to % of the person's maximum heart rate, using the person's maximum heart rate. The maximum heart rate is defined on the basis of the person's age, if the person does not know it directly. [0063] 6. The on/off kinematic information (loading stage) is calculated on the basis of the respiratory frequency and % HRmax. [0064] 7. % VO.sub.2max or METmax intensity is calculated, i.e. the physical loading exertion level as percentages relative to the person's maximum. [0065] 8. The RQ (respiratory quotient) value is calculated, which gives the ratio of fats and carbohydrates as energy sources. [0066] The RQ relates to a known way to calculate energy consumption on the basis of oxygen consumption. Generally, oxygen consumption (litre/minute) is multiplied by five, giving the energy consumption in calories. [0067] 9. The relative intensity % VO.sub.2max is converted to absolute oxygen consumption by multiplying it by the person's VO.sub.2max (maximum oxygen consumption). If the person does not know their VO.sub.2max value, it can be calculated using Jackson et al.'s 1990 equation, on the basis of the person's background data. The VO.sub.2max value can also be obtained on the basis of an automatic fitness test. All the person's background data can be set as default values, in which case the automatic fitness test will make the VO.sub.2max value more precise, as exercise sessions accumulate. [0068] 10. The calorific equivalent is calculated, which tells on the basis of the RQ value how much energy is produced per litre of oxygen consumed. [0069] 11. The momentary energy consumption kcal/min is calculated. [0070] 12. The sum of energy consumption kcal is calculated.

Example 2 of Application (FIG. 5). Calculation of Training Effect

[0071] The automatic determining of fitness level can be used, for example, in the calculation of the training effect. Typically, age and activity class from the person's background data are used in the calculation of the training effect, see FIGS. 5 and 6. The activity class can be determined on the basis of the result of a free fitness test, VO.sub.2max, together with age and sex, so that the person need not known their activity class, see Table 1.

[0072] FIG. 5. Calculation of training effect. [0073] 1. RR data, i.e. a time series of the time always between two consecutive heartbeats. [0074] 2. The heartbeat interval data is corrected by automatic error correction. [0075] 3 Respiratory frequency information is calculated from the heartbeat interval data. [0076] 4. The heart rate per minute is calculated from the heartbeat interval data. [0077] 5. The heart rate is converted to % of the person's maximum heart rate, using the person's maximum heart rate. The maximum heart rate is defined on the basis of the person's age, if the person does not know it directly. [0078] 6. The on/off kinematic information (loading stage) is calculated on the basis of the respiratory frequency and % HRmax. [0079] 7. % VO.sub.2max or METmax intensity is calculated, i.e. the physical exertion level as percentages relative to the person's maximum. [0080] 8.-10. EPOC (Excess Post-exercise Oxygen Consumption) is calculated at the present moment t, using VO.sub.2max intensity (7), as well as the previous EPOC value (8) and the duration (9) of the time interval being examined. [0081] 11. The exercise's EPOC peak, i.e. the highest EPOC value so far, is calculated. [0082] 12. The EPOCpeak value is converted to Training Effect by using the activity class according to FIG. 3. If the person does not know their activity class, it is set to a specific value as a default, or is calculated from the VO.sub.2max value in the manner of Table 1, using either an automatic fitness test, or the VO.sub.2max value estimated by Jackson et al. 1990. All of the person's background data can be set to be default values, in which case the automatic fitness test will make the VO.sub.2max value more precise as training accumulates.

[0083] According to FIG. 6, the training effect can be determined on the basis of the training's highest EPOC value as well as the person activity class. The person's activity class can be determined automatically on the basis of the automatically updated fitness level (VO.sub.2max). The following Table 1 shows the VO.sub.2max values according to age and sex for determining the activity class. These two sub-tables together form a 3-dimensional table, in which the axes are age, sex, and activity class. In each cell contains a VO.sub.2max value determined by these variables. The activity class is found by searching for the correct column with the aid of age and sex, from which the known VO.sub.2max value is sought, on the row of which the activity class is sought.

TABLE-US-00001 TABLE 1 Age <29 30-39 40-49 50-59 >60 Men Act. 0 34.5 32.5 30.9 28 23.1 class 1 37.1 35.4 33 30.2 26.5 2 39.5 37.4 35.1 32.2 28.7 3 41 38.9 36.7 33.8 30.2 4 42.5 41 38.1 35.2 31.8 5 44.2 42.4 39.9 36.7 33.6 6 46.8 44.6 41.8 38.5 35.3 7 51.4 50.4 48.2 45.3 42.5 7.5 61 61 61 61 61 8 65 65 65 65 65 8.5 69 69 69 69 69 9 73 73 73 73 73 9.5 77 77 77 77 77 10 81 81 81 81 81 Women Act. 0 28.4 26.5 25.1 22.3 20.8 Class 1 30.6 28.7 26.5 24.3 22.8 2 32.3 30.5 28.3 25.5 23.8 3 33.8 32.3 29.5 26.9 24.5 4 35.2 33.8 30.9 28.2 25.8 5 36.7 34.6 32.3 29.4 27.2 6 38.1 36.7 33.8 30.9 29.4 7 44.2 41 39.5 35.2 33 7.5 55 55 55 55 55 8 59 59 59 59 59 8.5 63 63 63 63 63 9 67 67 67 67 67 9.5 71 71 71 71 71 10 75 75 75 75 75

[0084] From Table 1, the person's activity class VO.sub.2max can be determined on the basis of sex and age. The activity class can, in turn, be used, for example, to determine the training effect from the EPOC value.

Example 3 of Application. Selection of Training Programme

[0085] The automatically determined fitness level can be used in the selection or adjustment of the training programme. Typically, the person must estimate their activity class, or the activity class is determined on the basis of the person's activity history. On the basis of the result VO.sub.2max of the fitness test determined on the basis of a free fitness test, the training programme can be selected directly to suit the person's fitness level, or the activity class can be calculated on the basis of Table 1 and the programme determined on its basis, see Table 2. Table 2 shows training programmes (table row). The desired training programme can be selected on the basis of the activity class calculated (Table 1) from VO.sub.2max (original activity class in the table).

[0086] In a preferred solution, the VO.sub.2max data obtained on the basis of an automatic fitness test from several training sessions by the same person is used. In the best case, the reliability of the estimation of the VO.sub.2max of each individual training session, and how much reliable material has been found temporally from the training, can be used in the weighting. If the amount of reliable data is 5, 10, 15, 20, 25, 30, 40, or 50 minutes, the corresponding weighting coefficients as percentages are 10, 20, 30, 40, 50, 60, 80, and 100%, in that order. For example, if reliable material has been obtained from 4 minutes of the entire training in the automatic test, this new VO.sub.2max value is added to the VO.sub.2max average values of the previous test using a weighting coefficient of 8%, and correspondingly the amount of reliable material by 30 min with a weighting coefficient of 60%. Naturally, it is preferable for the VO.sub.2max of the first training session to be calculated with a weighting coefficient of 100%, because it probable that this value will be more correct than the preselected VO.sub.2max value, the VO.sub.2max value calculated using the equation of Jackson et al. 1990 on the basis of the person's background data, or the VO.sub.2max value calculated using the equation of Jackson et al. 1990 on the basis of the person's preselected background data.

[0087] FIG. 7 shows the calculation of a fitness index, for example, during running or walking. The person's maximum heart rate (HRmax), heart rate (heartbeats per minute), speed (e.g., m(k)/h), and altitude (metres) are entered in the computation register. Each period being examined must be reliable, in order to create a fitness index. Reliability can be examined, for example, by setting reliability for known influencing factors, in this example external work (W), angle altitude, EPOC gradient, physiological intensity, limit values (c1, c2 . . . c9), within the framework of which the variables must remain during the period being examined, for the period to be accepted. If the period is determined to be reliable, a fitness index is calculated for it, with the aid of external work (W) and physiological intensity (Int). So that the real fitness index can be shown reliably, the total time or number of the accepted periods must exceed the time/value (c10) regarded as reliable.

[0088] According to FIG. 8, in a typical application (e.g., wristop device) the implementation comprises an assembly built around a central processing unit (CPU) 32. A bus 36 transmits data between the central unit 32 and the other units. The input unit 31, ROM memory 31.1, RAM memory 31.2, keypad 18, PC connection 37, and output unit 34 are connected to the bus.

[0089] The heartrate sensor 12 and some sensor 30 registering external output are connected to the input unit 31, which handles the sensor's data traffic to the bus 36. Optionally, the PC is connected to a PC connection 37. The output device, for example a display 15, is connected to the output unit 34. In some embodiments, voice feedback is created with the aid of a voice synthesizer and a loudspeaker 35, instead or, or in addition to the feedback on the display. The sensor 30 measuring external work can, in fact, comprise a group of sensors, which are used together to define the external work done by the user.

[0090] All of the default values of the optional parameters are preferably stored in a ROM memory, or more specifically, e.g. in an EEPROM (Electrically Erasable Programmable Read-Only Memory) memory.

For example, the user's external data:
sex man, age 35 years, weight 75 kg, height 180 cm.
User's more demanding data:
fitness level (VO.sub.2max) 40 ml/kg/min; Activity class 4.

[0091] In a web service, the default values of the parameters are preferably recorded in self-service software.

[0092] In these embodiments, it would be as such also possible to use some other method than that described above as a fitness test. However, the fitness test according to the invention provides several advantages in terms of automatic updating. It can be completely integrated in many standard-model wristop devices and demands substantially fewer calculation stages than the method according to the WO publication.

[0093] The invention can be applied, for example, in the following applications: wristop device, mobile/cellphone application or device, fitness device, computer software, or web service.

REFERENCES

[0094] Jackson, A.; Blair, S.; Mahar, M.; Weir, L.; Ross, R.; and Stuteville, J.; 1990: Prediction of functional aerobic capacity without exercise testing. Medicine and Science in Sports and Exercise, 22(6): 863-870. [0095] McArdle, W. D.; Katch, F. I.; and Katch, V. L.; 2000: Exercise Physiology: energy, nutrition, and human performance, 5.sup.th ed. Baltimore, Williams and Wilkins.

TABLE-US-00002 TABLE 2 DURATION OF NUMBER OF ORIGINAL MINIMUM TRAINING STAGE SESSIONS/ HOURS/ ACTIVITY ACTIVITY NAME STAGE 1 2 3 4 5 6 7 (WEEK) WEEK WEEK CLASS CLASS Start 1 TE 2 3 2 4 3 1.33 0-2 0 Durat. 30 25 25 Improving 1 2 TE 2 3 2 4 3 1.5 3 3 Durat. 30 25 35 Improving 2 3 TE 1 2 3 2 4 4 3 4 4 Durat. 45 60 30 45 Improving 3 4 TE 2 3 1 3 4 4 3.75 5-7 5 Durat. 75 60 45 45 Improving 4 5 TE 3 2 2 3 1 4 5 5.25 7.5 --> 6 Durat. 35 85 75 60 60 Maintain 6 TE 4 2 4 3 3 1 5 4.83 7 HARD Durat. 60 45 50 75 60 Maintain 7 TE 2 1 2 1 1 4 4.75 EASY Durat. 75 80 70 60 Maintain 8 TE 3 2 1 2 3 1 1 6 6.5 MODERATE Durat. 50 90 45 90 70 45