Patent Application
20220047222
The present invention relates to a method for monitoring an exercise of a user, and more particularly to a method for determining an injury risk of a user taking exercise.
Overtraining may increase injury risk in an exercise session; therefore, monitoring training load is very important in preventing the user from getting injured. Recently, ACWR (Acute Chronic Workload Ratio) is a parameter used for estimating the injury risk of the exercise. This parameter is a ratio of the accumulated training load in the short-term to the accumulated training load in the long-term.
However, this parameter doesn't take the fitness condition (e.g., fitness performance level; the parameter of the fitness performance level is preferably VO2max) of the user into account. Take this case for example. The paper indicates that there is more injury risk as the positive value, equal to 1.5 subtracted from ACWR, is more. If the user A of more fitness performance level and the user B of less fitness performance level having the same age as the user A (i.e., the user A and the user B have the same age-based heart-rate zones. The age-based heart-rate zones is determined as follows: first, compute the maximum heart rate according to the formula, such as 220 minus the user's age (unit: beats per minute (BPM)); second, each of the personalized heart-rate zones is determined according to the ratio range of the maximum heart rate, and the ratio range is based on the common knowledge in the exercising field.) have performed the same exercise training for 28 days (i.e., TRIMP (training impulse) of the user A is the same as TRIMP of the user B everyday), ACWR of the user A is also the same as ACWR of the user B. At this time, if ACWR of the user A and ACWR of the user B are both 1.6, the user B of less fitness performance level may feel injury risk but the user A of more fitness performance level may feel no injury risk; further, the user A of more fitness performance level may still want to increase exercise intensity and continuously takes exercise to further improve his fitness performance level; however, a hint from ACWR may make the user A of more fitness performance level lose motivation for training psychologically.
Accordingly, the present invention proposes a method for determining an injury risk of a user taking exercise to overcome the above-mentioned disadvantages.
In the present invention, determine the injury risk of the user who has performed the exercise training for a first duration based on a comparison between the indication mode representing the training condition and the criterion of the injury risk. The criterion of the injury risk is determined based on the high-exercise-intensity training load (i.e., a first portion of the training load above the threshold of the exercise intensity) adjusted according to the fitness condition of the user.
In the present invention, the threshold of the exercise intensity adjusted according to the fitness condition of the user is a technical feature which takes the fitness condition (e.g., fitness performance level) of the user into account. In other words, the different criterion of the injury risk is determined for the users with different fitness conditions based on the high-exercise-intensity training load (i.e., a first portion of the training load above the threshold of the exercise intensity) adjusted according to the fitness condition of the user by this technical feature. Once the fitness condition of the user is determined, the criterion of the injury risk for the user can be precisely determined and the injury risk of the user who has performed the exercise training for the first duration can be precisely determined by this technical feature.
In a preferred embodiment of the present invention, the training load is determined based on a plurality of exercise intensity zones adjusted based on the fitness condition (e.g., fitness performance level) of the user. Besides the criterion of the injury risk determined in the preceding paragraph takes the fitness condition (e.g., fitness performance level) of the user into account, the indication mode determined based on at least one parameter associated with the training load also takes the fitness condition (e.g., fitness performance level) of the user into account because the training load is determined based on a plurality of exercise intensity zones adjusted based on the fitness condition (e.g., fitness performance level) of the user. Once the fitness condition of the user is determined, the injury risk of the user who has performed the exercise training for the first duration can be precisely determined based on the comparison between the indication mode representing the training condition and the criterion of the injury risk.
By the algorithm implemented in the computer of the present invention, the computer of the present invention performs operations described in claims or the following descriptions to precisely the injury risk of the user who has performed the exercise training for the first duration.
In one embodiment, the present invention discloses a method for determining an injury risk of a user who has performed an exercise training for a first duration. The method comprises: dividing, by a processing unit, the first duration into a plurality of time segments; determining, by the processing unit, the training load in each of the plurality of time segments, wherein a first portion of the training load is above a threshold of an exercise intensity adjusted according to a fitness condition of the user; performing, by the processing unit, an algorithm to determine an indication mode representing a training condition of the exercise training of the user in the first duration based on at least one first parameter associated with the training load; determining, by the processing unit, a criterion of the injury risk based on at least one second parameter associated with the first portion of the training load and the algorithm determining the indication mode; and determining, by the processing unit, the injury risk of the user who has performed the exercise training for the first duration based on a comparison between the indication mode representing the training condition and the criterion of the injury risk.
In one embodiment, the present invention discloses a method for determining an injury risk of a user who has performed an exercise training for a first duration. The method comprises: dividing, by a processing unit, a first duration into a plurality of time segments; determining, by the processing unit, the training load in each of the plurality of time segments, wherein the training load is determined based on a plurality of exercise intensity zones, wherein each of the plurality of exercise intensity zones has a first portion of the training load, wherein the training load is a sum of the first portions of the plurality of exercise intensity zones, wherein a second portion of the training load is above a threshold of an exercise intensity, wherein the plurality of exercise intensity zones and the threshold of the exercise intensity are adjusted according to the fitness condition of the user; performing, by the processing unit, an algorithm to determine an indication mode representing a training condition of the exercise training of the user in the first duration based on at least one first parameter associated with the training load; determining, by the processing unit, a criterion of the injury risk based on at least one second parameter associated with the second portion of the training load; and determining, by the processing unit, the injury risk of the user who has performed the exercise training for the first duration based on a comparison between the indication mode representing the training condition and the criterion of the injury risk.
The detailed technology and above preferred embodiments implemented for the present invention are described in the following paragraphs accompanying the appended drawings for people skilled in the art to well appreciate the features of the claimed invention.
The foregoing aspects and many of the accompanying advantages of this invention will become more readily appreciated as the same becomes better understood by reference to the following detailed description when taken in conjunction with the accompanying drawings, wherein:
The detailed explanation of the present invention is described as following. The described preferred embodiments are presented for purposes of illustrations and description and they are not intended to limit the scope of the present invention.
Fitness Condition
The fitness condition may be defined by the fitness performance level. The fitness performance level of one user may be different from that of the other user; if two users want to achieve the same training effect, one user of more fitness performance level needs acuter exercise guiding and higher exercise intensity than the other user of less fitness performance level. The fitness performance level may include health-related fitness and sport/skill-related fitness which can be also improved by engaging in physical activities or exercise training. For example, the parameter of the fitness performance level may be VO2max or METmax (maximum oxygen uptake capacity relative to resting oxygen consumption: equal to VO2max/3.5), and VO2max is preferred. Generally, a unit of the VO2max can be represented in an absolute way, such as oxygen uptake (ml/min), or in a relative way, such as oxygen uptake based on weight (ml/kg/min).
Exercise Intensity
The exercise intensity may refer to how much energy is expended when exercising. The exercise intensity may define how hard the body has to work to overcome a task/exercise. Exercise intensity may be measured in the form of the internal workload. The parameter of the exercise intensity associated with the internal workload may be associated with a heart rate, an oxygen consumption, a pulse, a respiration rate and RPE (rating perceived exertion). The exercise intensity may be measured in the form of the external workload. The parameter of the exercise intensity associated with the external workload may be associated with a speed, a power, a force, a motion intensity, a motion cadence or other kinetic data created by the external workload resulting in energy expenditure. The heart rate may be often used as a parameter of the exercise intensity.
The method in the present invention can be applied in all kinds of apparatuses, such as an exercise measurement system, a wrist top device, a mobile device, a server or a combination of at least one of the exercise measurement system, the wrist top device, the mobile device and the server.
In Step 202: determining the training load in each of the plurality of time segments (by the processing unit 102). For convenience of description, the period of each time segment is 1 day in the present invention; however, the present invention is not limited to this case. In the present invention, the training load is calculated everyday.
The threshold of the exercise intensity is adjusted according to the fitness condition (e.g., fitness performance level; the parameter of the fitness performance level is preferably VO2max) of the user. In other words, the threshold of the exercise intensity is adjusted based on the different fitness performance levels.
The training load may be determined based on a plurality of exercise intensity zones. Each of the exercise intensity zones has a second portion of the training load (e.g., the product of the exercise intensity and the exercise time), wherein the training load is a sum of the second portions of the exercise intensity zones. At least one of the exercise intensity zones is adjusted according to the fitness condition of the user or adjusted based on the different fitness performance levels. All of the exercise intensity zones are adjusted according to the fitness condition of the user or adjusted based on the different fitness performance levels. In one embodiment, the training load is determined based on a plurality of exercise intensity zones in U.S. application Ser. No. 16/733,180 which can be incorporated by reference therein. Obviously, U.S. application Ser. No. 16/733,180 discloses a plurality of exercise intensity zones adjusted according to the fitness condition (e.g., fitness performance level) of the user or adjusted based on the different fitness performance levels (see two-dimensional exercise intensity zones 500 in
In one embodiment, the training load may be represented in the form of an TRIMP (training impulse); however, the present invention is not limited to this case.
In step 203: performing an algorithm to determine an indication mode representing a training condition of the exercise training of the user in the first duration based on at least one first parameter Wi associated with the training load (by the processing unit 102). To understand the training condition (e.g., training time or training distribution) of the exercise training of the user in the first duration, the indication mode may be determined by performing an algorithm. In one embodiment, one of at least one parameter Wi may be further associated with the accumulated training load. The parameter Wi may be presented in a relative way or in an absolute way by using the accumulated training load as the input of the parameter Wi. The algorithm may adopt the parameter Wi presented in an absolute way, such as the accumulated training load during the past several days or 28 days. The algorithm may adopt the parameter Wi presented in a relative way, such as the ratio of the short-term accumulated training load to the long-term accumulated training load (e.g., ACWR: Acute Chronic Workload Ratio); the long-term may be a first duration (e.g., 28 days) and the short-term may be a second duration (e.g., 7 days).
In a further embodiment, the indication mode may be determined further based on at least one parameter Vi associated with a recover condition (e.g., recovery time or recovery distribution). The recover condition may comprise a succession of time segments each of which doesn't have the training load therein (i.e., the training load is 0). For example, the algorithm may adopt a combination of the parameter Wi and the parameter Vi, such as a weighed synthetic index (e.g., a*Wi+b*Vi, each of the coefficients a, b may be fixed or variable according to the observation of the physiological phenomenon) of the parameter Wi and the parameter Vi; the parameter Vi associated with the recover condition may be a parameter V1 representing the number of a succession of days each of which has no training load therein before the current training load or a parameter V2 representing the number of the days each of which has no training load therein in a duration before the current training load. For example, see
In Step 204: determining a criterion of the injury risk based on at least one second parameter Xi associated with the first portion of the training load and the algorithm determining the indication mode (by the processing unit 102). The criterion of the injury risk may be dynamically determined. The criterion of the injury risk may be determined relative to a predetermined criterion associated with the algorithm. The predetermined criterion may be fixed. For example, the paper indicates that there is more injury risk as the positive value, equal to 1.5 subtracted from ACWR, is more and then the predetermined criterion may be 1.5 when the algorithm only adopts ACWR (Acute Chronic Workload Ratio) to represent a training condition of the exercise training of the user in the first duration in step 203. In another example, the predetermined criterion may be variable. Furthermore, the predetermined criterion may be user-defined.
The parameter X1 associated with the first portion of the training load may be presented in an absolute way, such as the current first portion of the training load. The parameter X2 associated with the first portion of the training load may be presented in a relative way, such as the ratio of the current first portion of the training load to the current overall training load. The parameter X3 associated with the first portion of the training load may be the number of the days each of which has the first portion of the training load therein in a duration before the current first portion of the training load. For example, see
In one embodiment, when the algorithm only adopts ACWR (Acute Chronic Workload Ratio) to represent a training condition of the exercise training of the user in the first duration in step 203, the criterion of the injury risk may be determined by using: (1) the criterion of the injury risk=function f(X1)=c1*X1; or (2) the criterion of the injury risk=function f(X2)=c2*X2; or (3) the criterion of the injury risk (a combination of X2 and X3)=function f(X2, X3)=c3*X2+c4*X3. Each of the coefficients c1, c2, c3, c4 may be fixed or variable according to the observation of the physiological phenomenon. Take the case (I) for example: the criterion of the injury risk (a combination of X2 and X3)=function f(X2, X3)=c3*X2+c4*X3; each of the coefficients c3, c4 is positive. The more the parameter X2 is, the less the criterion of the injury risk is adjusted to be, which will increase the injury risk. The more the parameter X3, the less the criterion of the injury risk is adjusted to be, which will increase the injury risk. The more the parameter X2 and the parameter X3 are both at the same time, the less the criterion of the injury risk adjusted to be, which will increase the injury risk.
Further, the criterion of the injury risk may be determined further based on at least one parameter Yi associated with a recover condition. The recover condition comprises a succession of time segments each of which doesn't have the first portion of the training load therein (i.e., the first portion of the training load is 0). The parameter Yi associated with the recover condition may be a parameter Yi representing the number of a succession of days each of which has no first portion of the training load therein before the current first portion of the training load or a parameter Y2 representing the number of the days each of which has no first portion of the training load therein in a duration before the current first portion of the training load. For example, see
In one embodiment, when the algorithm only adopts ACWR (Acute Chronic Workload Ratio) to represent a training condition of the exercise training of the user in the first duration in step 203, the criterion of the injury risk may be determined by using the criterion of the injury risk (a combination of X2 and Y1)=function f(X2,Y1)=c5*X2=c6*Y1. Each of the coefficients c5, c6 may be fixed or variable according to the observation of the physiological phenomenon. For example, each of the coefficients c5, c6 is positive. The more the parameter X2 is, the less the criterion of the injury risk is adjusted to be, which will increase the injury risk. The more the parameter Y1 is, the more the criterion of the injury risk is adjusted to be, which will decrease the injury risk. When the parameter X2 and the parameter Yi both increase at the same time, the criterion of the injury risk depends on the competence of the parameter X2 and the parameter Yi of the function f(X2, Yi).
Finally, in Step 205: determining the injury risk of the user who has performed the exercise training for the first duration based on a comparison between the indication mode representing the training condition and the criterion of the injury risk (by the processing unit 102). Take the case (I) for example: the criterion of the injury risk (a combination of X2 and X3)=function f(X2, X3)=c3*X2+c4*X3; each of the coefficients c3, c4 is positive.
In the above description, the indication mode and the criterion of the injury risk are numerically represented in the form of value or index. If the indication mode is less than the criterion of the injury risk, there is no injury risk or less injury risk; on the contrary, if the indication mode is more than the criterion of the injury risk, there is injury risk or more injury risk. The indication mode and the criterion of the injury risk may be presented in any suitable form. For example, the indication mode and the criterion of the injury risk are respectively presented in the form of the pattern 1 and in the form of the pattern 2; and then the comparison between the indication mode representing the training condition and the criterion of the injury risk may be based on the shift between the pattern 1 and the pattern 2.
The above disclosure is related to the detailed technical contents and inventive features thereof. People skilled in the art may proceed with a variety of modifications and replacements based on the disclosures and suggestions of the invention as described without departing from the characteristics thereof. Nevertheless, although such modifications and replacements are not fully disclosed in the above descriptions, they have substantially been covered in the following claims as appended.
