• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The invention relates to a platform (1) for planning and analyzing sports training for one or more athletes, comprising: - a tool (2) configured to calculate or measure one or more physiological parameter values for each athlete, - one or multiple generic libraries (5b, 6a) adapted to store generic training exercises (5a), - a calendar (6b) adapted to store a training plan for the one or more athletes, - a user interface based on drag-and-drop that allows an authorized user to add blocks to an athlete's training plan, each block representing a generic training exercise from the generic libraries, and - a training plan module (6) adapted to automatically create a generic training exercise (5d) added to an athlete's training plan through the drag-and-drop interface individualizing by length e, adjust the volume and / or intensity of the training exercise based on the one or more physiological parameter values (2) that are individually calculated or measured for the athlete, in order to achieve the training plan (6b) of the athlete in question. individualize.
    公开号:BE1021931B1
    申请号:E2014/0552
    申请日:2014-07-11
    公开日:2016-01-27
    发明作者:Johan Marie Jozef Jaak Strobbe；Koenraad Marie Marcel Norbert Strobbe；Jorn Hans-Jürgen Lully
    申请人:Iqo2 Bvba；
    IPC主号:
    专利说明:

    PLATFORM FOR PLANNING AND ANALYZING SPORTS TRAINING FOR ONE OR MULTIPLE ATHLETES
    Field of the Invention The present invention relates generally to a platform for planning and analyzing sports training for one or more athletes. These athletes can be trained or untrained athletes and professional or non-professional athletes.
    This invention relates more specifically to such a platform comprising a tool configured to calculate or measure one or more physiological parameter values for each athlete.
    Background of the Invention At present, tools have been developed that are coupled to portable devices that are capable of monitoring the performance of an individual wearing such a portable device during training. These portable devices can send and receive a range of information to remote Server computers via networks to support the individual in achieving their goals. Sports brands such as Nike and Adidas have developed such tools.
    For example, in US 2012/0015779, Adidas AG describes a computer-implemented method to provide a new training for an athlete using a fitness monitoring service. The method includes the steps of granting an athlete access to an account at the fitness monitoring service, maintaining a training schedule to be completed for the athlete linked to the account, receiving the new training from a coach, adding the new training to the training schedule and exchanging information regarding the new training with a portable fitness monitoring device.
    In US 2006/0136173, Nike describes Ine. for example, athletic performance monitoring systems and methods, many of which use Global Positioning System (GPS) data to provide data and information to athletes and / or to equipment used by athletes during a sporting event. Such systems and methods may provide route information to athletes and / or their trainers, e.g. for pre-event planning, goal setting and calibration purposes. Such systems and methods may optionally provide real-time information to the athlete while the event is taking place, e.g., to support achievement of predetermined goals. In addition, data and information collected by such systems and methods may be useful during post-event analysis for athletes and their trainers, eg to evaluate past performance and to help improve future performance. Paragraphs - [0091] of US 2006/0136173 state that physical or physiological sensor data can be included in the database. The physical or physiological sensor data is physiological data that is detected by a sensor during an exercise, eg heart rate or pulse rate, blood pressure, body temperature, etc. They are not physiological parameter values of the athlete. It can be understood from paragraphs [0089] and [0091] of US 2006/0136173 that the system can suggest a future training plan and, for example, make a selection of potential routes, but the selection of future training and routes is not based on the physiological sensor data. , let alone the physiological parameter values of an athlete.
    [06] The disadvantage of these tools is that scheduling the training for multiple team members using such existing tools is a time-consuming and repetitive task for the coaches and the technical staff.
    [07] U.S. Patent Application US 2008/0147422 entitled "Systems and Methods for Integrating Sports Data and Processes of Sports Activities and
    Organizations on a Computer Network "describes a platform with improved data collection for team players or athletes of a sports organization. As stated in par. [0013] of US 2008/0147422, the platform also improves communication between coach and players via an interactive calendar with events that accessible to coaches, staff members, players, etc. Section [0057] states that the event data consists of planable data that can be assigned to a date on the calendar, and the platform further supports a protocol to enter training data and players can keep their coach informed of the fact that a planned training session has been completed so that new training sessions can be allocated.
    [08] Also in US 2008/0147422, scheduling individual training for multiple players or athletes is a cumbersome, time-consuming, repetitive task that must be performed by coaches, physiologists, psychological counselors, etc.
    [09] European patent application EP 2 260 910 entitled "Portable Fitness Monitoring Systems with Color Displays and Applications ThereoF describes a portable system consisting of a heart rate sensor that monitors the heart rate of an individual and a display module that is controlled to display a color associated with More generally, in paragraph [0037], EP 2 260 910 describes the measurement of a physiological parameter such as heart rate, body temperature, blood flow, fluid content, etc. Paragraph [0143] describes comparing the detected physiological parameter values with certain thresholds, e.g., the ventilation threshold or the lactate threshold to determine the zone in which the individual is currently training and to determine the corresponding color to be displayed.
    [10] Although EP 2 260 910 describes the measurement of physiological parameters, it does not explain how such measurements can be used to improve the efficiency of planning / analyzing training schedules for a team of athletes.
    [11] International Patent Application WO 2012/075505 entitled "Targeting Advertisements to Athletes" describes a platform for targeting advertising messages to an athlete, depending on sporting performance information obtained and stored in the athlete's account. The platform known from WO 2012/075505 does not describe or suggest any possibility to plan the training of the athlete and certainly does not offer a solution for efficient training planning for a team of athletes by the technical staff.
    [12] Accordingly, there is a need for a platform for planning and analyzing sports training that enables efficient coaching, ie planning and analyzing training, of an athlete or a team of athletes by a multidisciplinary team of physiologists, among others. technical staff, coaches, paramedics, psychological counselors, etc. There is also a need to provide such a platform that makes it possible to efficiently plan the training for several team members.
    Summary of the Invention [13] In the present invention, the above identified shortcomings of existing tools are solved by providing a platform for planning and analyzing sports training for one or more athletes, including the platform - a tool configured to allow for calculate or measure one or more physiological parameter values for each athlete, - one or more generic libraries adapted to save generic training exercises, - a calendar adapted to save a training plan for the one or more athletes, - a user interface based on drag-and-drop adapted to allow an authorized user of the platform to add blocks to the training plan of the one or more athletes in the calendar, each block representing one of the generic training exercises of the one or more generic libraries, - a trainingpl module adapted to automatically individualize a generic training exercise that has been added to an athlete's training plan through the drag-and-drop user interface by adjusting the length, volume and / or intensity of the training exercise based on the one or more physiological parameter values that have been calculated or measured separately for the athlete, in order to individualize the training plan of the athlete in question.
    [14] The advantage of this platform is that a multidisciplinary platform is obtained that can be used by physiotherapists, technical staff, coaches, paramedics, etc. around an athlete or a team of athletes. Moreover, it enables a team coach to efficiently plan training exercises for multiple team members based on generic training exercises that are automatically individualized for individual team members. This avoids repetition when drawing up training schedules, which saves a lot of time for a team coach.
    [15] In a preferred embodiment of a platform according to the invention, the one or more physiological parameter values comprise an anaerobic threshold of the one or more athletes, and the platform further comprises a training zone definition module that is configured to define a plurality of training zones for the one or more athletes representing a different training intensity, and each of the training zones is defined as a percentage interval of the anaerobic threshold.
    [16] The anaerobic threshold (ANT) is defined as the training intensity at which a rapid rise in blood lactate occurs, indicating the upper limit of the balance between lactate production and removal. This ANT therefore forms the transition between the aerobic and the anaerobic lactic energy supply.
    [17] The ANT varies from person to person and, for a specific person, from sport to sport. Untrained individuals have a low ANT (approximately 55% of VO2 max) and elite endurance athletes have a high ANT (approximately 80 - 90% of VO2 max). V02 max is the maximum amount of oxygen that can be consumed by an athlete during one minute at sea level. The oxygen consumption is directly proportional to the energy consumption. This means that when oxygen consumption is measured, the maximum capacity of an athlete is also indirectly measured to deliver aerobic efforts. 95% of the endurance athlete's effort consists of aerobic effort. The higher the V02 max, the more talent an athlete has to become an endurance athlete. The later an athlete reaches the ANT, the better his endurance. This point is also called the maximum lactate steady state. An athlete can train his body to better remove lactate and make more aerobic mitochondrial enzymes to increase ANT.
    [18] Efforts under the ANT can be sustained for quite a long time. Efforts with an intensity above the ANT will have to be stopped quickly. Accumulation of lactate limits performance to periods of 30 seconds to 15 minutes. Exhaustion is the result of the disruption of the internal biochemical management of the working muscles and the entire body, caused by a high acidosis.
    [19] In a more preferred embodiment of a platform according to the invention, the one or more training zones are sport-specific. In such an embodiment, the percentage of the anaerobic threshold related to a respective zone is determined based on one or more predetermined definitions that depend on the respective sport.
    [20] In a possible embodiment of a platform according to the invention, the tool configured to calculate or measure one or more physiological parameters comprises a training intensity calculation module configured to calculate the anaerobic threshold of a respective athlete based on of predetermined fitness levels that are linked to the age, gender, resting heart rate and maximum heart rate of the athlete in question.
    [21] In another possible embodiment of a platform according to the invention, the tool configured to calculate or measure one or more physiological parameters comprises a lactate test module configured to analyze the relationship between the power, the speed, the heart rate and lactate value of the athlete tested, and which is configured to calculate the anaerobic threshold of the athlete in question based on that.
    [22] In yet another possible embodiment of a platform according to the invention, the tool configured to calculate or measure one or more physiological parameters comprises a functional threshold module configured to analyze data from a tested athlete being monitored. during a training exercise at an optimal intensity, and which is configured to calculate the anaerobic threshold of the athlete in question based on this.
    [23] This monitoring device preferably includes a power monitor adapted to measure the power of the legs of the athlete in question during training and the heart rate of the athlete in question during training in case the sport discipline is cycling; and / or a speed monitor adapted to measure the speed and heart rate of the athlete in question during training in case the sport discipline is running or swimming.
    [24] In a preferred embodiment of a platform according to the invention, the training plan module is adapted to calculate a meso cycle based on a respective training plan by adding volume and / or intensity of one or more training exercises in the individualized training plan of an athlete.
    [25] A mesocycle represents a training phase with a duration of between 2 and 6 weeks or microcycles, but this can depend on the sport discipline. During the preparation phase, a mesocycle usually consists of 4 to 6 microcycles, but during the competition phase, the mesocycle usually consists of 2 to 4 microcycles depending on the competition calendar. The goal of the planner is to fit the mesocycle into the general time schedule so that each mesocycle ends at one of the phases and then to determine the workload and work type of each cycle based on where in the general plan the specific mesocycle falls . The underlying goal is to ensure that the body peaks for the priority competitions by improving each cycle along the way.
    [26] In an advantageous embodiment of a platform according to the invention, the training plan module is further adapted to determine a macro cycle on the basis of the individualized training plan that represents an annual plan with the training volume, intensity, period and / or type of training exercise. .
    [27] A macro cycle refers to an annual plan that works towards a peak moment for the most important competition of the year.
    [28] A further disadvantage of the known monitoring devices used to collect data related to athletic performance, for example monitoring devices from RIM, Polar, SRM, Garmin, CycleOps, Suunto etc. is that each of these devices has its own data format and way of data registration. The devices of the SRM training system, for example, register per second, Garmin devices apply intelligent registration, etc. Consequently, it is difficult to compare data from different team members when using different devices.
    [29] This disadvantage is solved in an advantageous embodiment of a platform according to the invention, comprising a device data extraction module adapted to extract data from one or more monitoring devices worn by an athlete during one or more training exercises, wherein the device data extraction module is further adapted to convert the data extracted from the one or more monitoring devices into a proprietary format that can be used in the various modules of the platform.
    [30] This provides a platform that is independent of the device or devices used by the athlete or athletes and leads to a uniform analysis of all devices thanks to its own format.
    [31] In a preferred embodiment of a platform according to the invention, the platform comprises an analytical module adapted to compare data extracted from the one or more monitoring devices with data extracted from the individualized training plan of the athlete in question.
    [32] This offers the possibility to optimize the training plan of an athlete based on these comparisons.
    [33] The data extracted from the one or more monitoring devices preferably includes the volume and / or intensity of the training exercise as it is performed by the athlete in question.
    [34] In addition, various internet-based applications are already available for planning and analyzing sports training. Examples are TrainingPeaks and Asicoach.com. Various device manufacturers also offer such web-based applications. Examples are polarpersonaltrainer.com from Polar and Garmin Connect from Garmin.
    [35] These Internet-based applications, however, require a connection to a network. The athlete must go online regularly, which is not possible if the athlete follows a training plan in a remote location where there is no or a poor network connection.
    [36] It is a further need to provide such a platform that is not dependent on a network connection and can therefore be used both online and offline.
    [37] This need is met by a platform according to the invention, further comprising an application running on a desktop computer. The application can be activated at a time when a user is offline, but also at a time when the user is online.
    [38] Preferably, the application is configured to upload data from one or more monitoring devices, the application being configured to automatically upload the data uploaded from the one or more monitoring devices to a server or the Internet when the user of the application is online, or as soon as a user of the application has logged into the application to be online.
    [39] The application is furthermore preferably configured to allow multiple users to use the platform simultaneously.
    BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 illustrates a flow chart of the various modules of an embodiment of a platform according to the invention.
    FIG. 2 illustrates a flowchart diagram of the common fields in all datasets of the database to support online / offline synchronization.
    Detailed Description of the Embodiment (s) [42] As can be seen in Figure 1, a platform (1) according to the invention for planning and analyzing sports training includes a tool (2) configured to have one or more for each athlete calculate or measure physiological parameter values. These one or more physiological parameter values preferably include the anaerobic threshold (ANT) (as explained in detail above).
    [43] This ANT can be determined in three different ways, namely 1. by means of a Training Intensity Calculator (TIC) module that is configured to calculate the ANT of an athlete in question based on predefined fitness levels (poor, good, average, excellent) that are linked to the age, gender, resting heart rate and maximum heart rate of the athlete in question; 2. by means of a lactate test module that is configured to analyze the relationship between the ability, speed, heart rate and the lactate value of the athlete in question, on the basis of which the ANT can be determined; 3. by means of a functional threshold module configured to analyze data from the tested athlete who is being monitored by a monitoring device (not shown in the figures) during an optimal intensity training (field performance), based on which the ANT of the athlete in question can be determined.
    [44] When the sports discipline is cycling, this monitoring device preferably comprises a power monitor adapted to measure the power of the legs of the athlete in question during training and the heartbeat of the athlete in question during training. When the sport discipline is running or swimming, the monitoring device includes a speed monitor adapted to measure the speed and heart rate of the athlete in question during training.
    [45] The platform (1) according to the invention comprises a module (7) for extracting device data to extract data (7a) from these monitoring devices worn by an athlete during one or more training exercises. This device data extraction module (7) is further adapted to convert the data (7b) extracted from these one or more monitoring devices into a proprietary data format (7c) that is stored in the different modules (2-8) of the platform ( 1) can be used that is independent of the different monitoring devices.
    [46] The data from the monitoring device or devices is stored in a format that is the same for all devices and sports. In Table 1, the fields of a training data set become weather data as stored in the uniform data set.
    Table 1 [47] This format is extensible and adaptable. If the format changes or fields are added, the format saved on a server or locally is automatically converted to the most recent format. When data is stored, the data is first encoded to minimize the number of bytes required to store each row in the data set. This is done by scanning the data and calculating the minimum and maximum values of each column. The ID, accuracy, minimum and maximum values are stored in the header of the coded data. The number of bytes required to store the data of a column is calculated on the basis of (maximum - minimum) * 10 Accuracy and of the actual data, the difference is calculated with the minimum value. This ensures that a minimum amount of bytes is used for each row, without sacrificing the compression ratio in the next step. Only columns with data are saved. The format is a variable format since the metadata (ID and accuracy, for example) of the actual columns are stored. Finally, an LZMA compression algorithm (Lempel-Ziv-Markov chain algorithm) is applied to the coded data before it is stored in the database. The data is also given a version and changing compression algorithms are possible.
    The platform (1) according to the invention comprises a training zone module (3) that is configured to enable a user of the platform (1) to select the way in which the ANT is determined.
    [49] The platform (1) further comprises a training zone definition module (4) configured to define a multiple number of training zones of the one or more athletes that differ in training intensity. Each of these training zones is defined as a percentage of the ANT and is sport specific. The platform (1) comprises a training zone definitions module (4) comprising these predefined fixed training zone definitions. After the ANT was determined by one of the methods described above, this ANT is used by the training zone definitions module (4), or in other words the training zone definitions are applied in the training zone module (3) resulting in individualized training zones (9).
    [50] Table 2 below shows an example of a number of running training zones for sports discipline, with for each of these training zones the range of heart rate (expressed in beats per minute), the percentage of the ANT heart rate, the percentage of the maximum heart rate, the speed (in km / h) and the percentage of ANT speed are displayed.
    Tabe 2 [51] The platform (1) according to the invention comprises a training building module (5) configured to build one or more generic libraries (5b, 6a) comprising a plurality of generic training exercises (5a).
    [52] The platform (1) also includes a training plan module (6) that enables an authorized user of the platform (1) to compile a training plan for an athlete or team of athletes on the athlete's or athletes' calendar. in question, based on generic training exercises (5a) that are stored in one or more generic libraries (5a, 6b). A training plan can include one or a multiple number of trainings / training exercises. These generic training exercises (5a) form blocks that can be added to the calendar (6b) and that are categorized, such as warm-up, cooldown, exercise, group exercises, repetition group, etc., which enables semi-automatic recognition, addition and classification of training exercises. The addition of a generic training exercise (5a) to the calendar (6b) of an athlete is preferably carried out by means of a user interface based on drag-and-drop, but this method does not exclude any other suitable method for generating generic training exercises (5a) to add to the calendar. When a generic training exercise (5a) is added to the athlete's calendar, this generic training exercise (5a) is automatically adjusted based on the athlete's ANT that has been calculated or measured in advance by one of the methods described above and determined by the user of the platform (1) in the training zone module (3) as already described above. In this way a calendar is obtained with an individualized training plan (6b).
    [53] If, for example, it is assumed that an athlete wants to run a marathon, a lactate test is performed and after analysis of the lactate performance curve it is determined that that athlete is running on his ANT at 11.5 km / h, then different ANT and higher lower limits of the different training zones. When the coach places a running schedule in his calendar for that athlete, all training sessions of this plan will be automatically adjusted to the training zones of that athlete. One training contains several exercises that the athlete must perform each time in the correct training zone. If the marathon takes place in 16 weeks, the coach will place a 16-week schedule in that athlete's calendar. After 8 weeks of training, the athlete can have a field test performed. He is then instructed to run fully for 20 minutes with a GPS device. The data from the GPS device can be loaded and via an analysis system one can analyze the field test of 20 minutes. A new ANT speed can be calculated from this analysis, for example 12.3 km / h, which teaches something about the effect of the training on that athlete. In this concrete example, the fitness level of this athlete has been improved. His ANT speed has increased from 11.5 km / h to 12.3 km / h. This new ANT speed can now be used to redefine the training zones so that the training zones are adjusted to the current performance level of this athlete. Once the new training zones have been determined, all training assignments that follow will be adjusted with these new training zones.
    [54] In another example, for example, a different physiological parameter changes with a cyclist. For example, a cyclist receives the assignment within a 30-minute training at 4 Watt / kg. If his training changes his weight from 75 kg to 70 kg, this factor will automatically lead to an adjustment of the training schedule. At 75 kg the cyclist will have to climb 300 watts while at 70 kg he will only have to climb 280 watts.
    [55] The training plan module (6) is furthermore arranged to calculate a meso cycle (6c) based on the respective calendar with the individualized training plan (6b) by adding the volume and / or intensity of one or more training exercises in the individualized training plan . A macro cycle can also be determined on the basis of the individualized training plan that proposes an annual plan of volumes, intensity, period and / or type of training exercises. The definitions of mesocycle and macrocycle have already been given above.
    [56] The platform (1) according to the invention also comprises an analytical module (8) that is configured to extract data extracted from the one or more monitoring devices, preferably the volume and / or intensity of the training exercise (s). it was performed by the athlete in question, comparable to the data from the planned individualized training plan.
    [57] This analytical module (8) is further adapted to calculate an athlete's overtraining. Overtraining is a physical, behavioral, and emotional state that occurs when the volume and intensity of an athlete's training exercise exceeds his / her recovery capacity. The athlete is no longer making progress and may even begin to lose strength and fitness. The platform (1) according to the invention may comprise a display module (not shown in the figures) adapted to visualize an athlete's fatigue.
    [58] The platform (1) according to the invention preferably comprises an application that runs on a desktop computer, the application being configured to run when a user is offline, but which can also run when the user user is online. The application is further configured to allow multiple users to work offline at the same time in the same file of a respective athlete.
    [59] This application is preferably configured to upload data from one or more monitoring devices, the application being configured to automatically upload the data from the one or more monitoring devices to a server or the Internet when the user of the application is online , or as soon as a user of the application has logged into the application to be online.
    [60] This application is furthermore preferably configured to allow multiple users to use the application both online and offline at the same time.
    [61] As can be seen in Figure 2, all data sets in the database share common items to enable synchronization. All IDs are GUIDs (Global Unique IDentifiers), so it makes no difference whether they were created locally or remotely.
    [62] The common fields in all datasets of the database to support online / offline synchronization (10) are: primary key id: a GUID that identifies the file; activation agent: a GUID that identifies the active user (user account that was used to log in); asset subject: a GUID that identifies the active athlete; createdon: a time stamp of the creation date of the file; modifiedon: a time stamp of the last change of the file; deletedon: a time stamp of the moment of deleting the file.
    [63] Consultation of data online or offline is transparent in the software through the use of interfaces. The interface describes the functions of the storage object, there can be several implementations of this interface, for example online storage (11) and offline storage (12). The storage technology can be completely changed by writing a new implementation.
    [64] There are two entities that define to which user account data is linked, namely, agent is the user account that is logged in; asset subject is the user account used for training data (training, training zones, calendar, periodic data, etc.).
    After logging in, the agent is the same as the activity subject until the user selects another athlete's account in the client management. For example, a coach may have multiple linked accounts (14) from different athletes.
    [65] In a single-user environment, if the user does not have linked accounts (14), the agent will always be the same as the asset subject. In a multi-user environment, where linked accounts (14) are linked to one or more other active accounts (13), they will refer to different user accounts, or with other one user changing data in another user's account. As soon as a user logs in, an active account (13) is obtained.
    [66] Text figure 1:
    [67] Text figure 2:
    Although the present invention has been illustrated with reference to specific embodiments, it will be understood by those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be practiced with various modifications and modifications without leaving the scope of the invention. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being described by the appended claims and not by the foregoing description, and all modifications falling within the meaning and scope of the claims, are therefore included here. In other words, it is assumed that this covers all changes, variations or equivalents that fall within the scope of the underlying basic principles and whose essential attributes are claimed in this patent application. In addition, the reader of this patent application will understand that the words "comprising" or "include" do not exclude other elements or steps, that the word "a" does not exclude a plural, and that a single element, such as a computer system, a processor or other integrated unit can fulfill the functions of different tools mentioned in the claims. Any references in the claims should not be construed as limiting the claims in question. The terms "first", "second", "third", "a", "b", "c" and the like, when used in the description or in the claims, are used to distinguish between similar elements or steps and do not necessarily describe a sequential or chronological order. Similarly, the terms "top", "bottom", "over", "under" and the like are used for the purposes of the description and do not necessarily refer to relative positions. It is to be understood that those terms are interchangeable under proper conditions and that embodiments of the invention are capable of functioning in accordance with the present invention in sequences or orientations other than described or illustrated above.
    权利要求:
    Claims (15)
    [1]
    CONCLUSIONS
    A platform (1) for planning and analyzing sports training for one or more athletes, the platform (1) comprising: - a tool (2) configured to calculate or measure one or more physiological parameter values for each athlete, one or more generic libraries (5b, 6a) adapted to store generic training exercises (5a); a calendar adapted to store a radiation plan for said one or more athletes; a drag-and-drop user interface adapted to enable an authorized user of said platform to add blocks to said training plan of said one or more athletes in said calendar, wherein each block is one of said generic training exercises represents said one or more generic libraries; a training plan module (6) adapted to automatically individualize a generic training exercise (5d) added to a training plan of an athlete by means of said user interface with drag-and-drop by the length, volume and / or intensity of said training exercise (5d) to be adjusted based on said one or more physiological parameter values (2) calculated or measured separately for said athlete, so as to individualize said athlete's training plan (6b).
    [2]
    A platform (1) according to claim 1, wherein said one or more physiological parameter values (2) comprise an anaerobic threshold of the one or more athletes, said platform (1) further comprising: - a training zone definition module (4) that is configured to define a plurality of training zones for the one or more athletes, said training zones representing a different intensity of training, and each of said training zones is defined as a percentage interval of said anaerobic threshold.
    [3]
    A platform (1) according to claim 2, wherein said training zone definitions module (4) is further adapted to define sport-specific training zones.
    [4]
    A platform (1) according to claim 2 or 3, wherein said tool (2) comprises a training intensity calculation module for calculating the anaerobic threshold of a respective athlete on the basis of predetermined fitness levels linked to age, gender, the resting heart rate and the maximum heart rate of the athlete in question.
    [5]
    A platform (1) according to claim 2 or 3, wherein said tool (2) comprises a lactate test module configured to analyze the relationship between the ability, speed, heart rate and lactate value of the tested athlete, and which is configured to calculate the anaerobic threshold of the athlete in question based on this.
    [6]
    A platform (1) according to claim 2 or 3, wherein said tool (2) comprises a functional threshold module configured to analyze data from a tested athlete who was monitored during an exercise at an optimum intensity, and configured to calculate the anaerobic threshold of the athlete in question based on this.
    [7]
    A platform (1) according to claim 6, wherein said monitoring device comprises: when the sports discipline is cycling, a power monitor adapted to measure the power of the legs of the athlete in question during training and the athlete's heartbeat in issue during training; and / or when the sport discipline is running or swimming, includes a speed monitor adapted to measure the speed and heart rate of the athlete in question during training.
    [8]
    A platform (1) according to any of claims 1 to 7, wherein said training plan module (6) is adapted to calculate a meso cycle (6c) based on a respective training plan by volume and / or intensity of one or more add training exercises to an athlete's training plan.
    [9]
    A platform (1) according to claim 8, wherein said training plan module (6) is further adapted to determine a macro cycle (6c) based on one or more individualized training plans that represent an annual plan of training volume, intensity, period and / or the type of training exercise.
    [10]
    A platform (1) as claimed in any one of claims 1 to 9, said platform (1) further comprising: - a module (7) for extracting device data adapted to extract data (7a) from one or more monitoring devices worn by an athlete during one or more training exercises, said device data extraction module (7) being further adapted to convert said data (7b) extracted from the one or more monitoring devices into its own format (7c) ) that can be used in the different modules (2 - 8) of said platform (1).
    [11]
    A platform (1) according to claim 10, further comprising: - an analytical module (8) adapted to compare data extracted from the one or more monitoring devices with data extracted from the individualized training plan (6b) of the athlete in question.
    [12]
    A platform (1) according to claim 10 or 11, wherein said data extracted from the one or more monitoring devices comprises the volume and / or intensity of the training exercise as performed by the athlete in question.
    [13]
    A platform (1) according to any of claims 1 to 12, further comprising: - an application running on a desktop computer.
    [14]
    A platform (1) according to claim 13, wherein said application is configured to upload data from one or more monitoring devices, and wherein the application is configured to automatically transfer the data uploaded from the one or more monitoring devices to a server or the upload the internet when the user of the application is online, or as soon as a user of the application has logged into the application to be online.
    [15]
    A platform (1) according to claim 13 or 14, wherein the application is configured to enable multiple users to use the platform (1) simultaneously.
    类似技术:
    公开号 | 公开日 | 专利标题
    Passfield et al.2017|Knowledge is power: Issues of measuring training and performance in cycling
    Schneider et al.2018|Heart rate monitoring in team sports—a conceptual framework for contextualizing heart rate measures for training and recovery prescription
    Gallo et al.2015|Characteristics impacting on session rating of perceived exertion training load in Australian footballers
    US9918646B2|2018-03-20|Sensor fusion approach to energy expenditure estimation
    US20060228681A1|2006-10-12|Automated processing of training data
    US10646151B2|2020-05-12|Exercise system and method
    DK2710503T3|2016-03-07|OPTICAL DATA RECORDING EXERCISE DATA TO PROMOTE A HEALTH SCORE CALCULATION
    US8182424B2|2012-05-22|Diary-free calorimeter
    US8092381B2|2012-01-10|Threshold training system
    US20150088006A1|2015-03-26|Method for determining aerobic capacity
    US20150209615A1|2015-07-30|Zoning Method of Processing Threshold and Metabolic and Heart Rate Training Data and Sensors and Apparatus for Displaying the Same
    Tran et al.2015|Convergent validity of a novel method for quantifying rowing training loads
    US20180279950A1|2018-10-04|Methods, media, and apparatus for optimizing physical training based on lactate concentrations
    Fonseca et al.2010|The association of various speed indices to training responses in Thoroughbred flat racehorses measured with a global positioning and heart rate monitoring system
    US20190009134A1|2019-01-10|Methods, systems, and non-transitory computer readable media for estimating maximum heart rate and maximal oxygen uptake from submaximal exercise intensities
    Morais et al.2020|Stability analysis and prediction of pacing in elite 1500 m freestyle male swimmers
    Altini et al.2017|Relation between estimated cardiorespiratory fitness and running performance in free-living: an analysis of HRV4Training data
    BE1021931B1|2016-01-27|PLATFORM FOR PLANNING AND ANALYZING SPORTS TRAINING FOR ONE OR MULTIPLE ATHLETES
    CN109922719A|2019-06-21|For quantifying system, the method and computer program of the physical fatigue of object
    Delaney et al.2018|Training efficiency and athlete wellness in collegiate female soccer
    Dadeliene et al.2020|Analysis of top kayakers’ training-intensity distribution and physiological adaptation based on structural modelling
    Crouch et al.2021|Relationship between pre-training wellness scores and internal and external training loads in a Division I women’s lacrosse team
    US20210169351A1|2021-06-10|Healthcare device and healthcare system using same
    Cassini2021|A data-driven analysis of training habits in amateur endurance runners
    US20210394022A1|2021-12-23|Method, an apparatus and a computer program product for providing a next workout recommendation
    同族专利:
    公开号 | 公开日
    EP2824614A1|2015-01-14|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20060136173A1|2004-12-17|2006-06-22|Nike, Inc.|Multi-sensor monitoring of athletic performance|
    US20090152349A1|2007-12-17|2009-06-18|Bonev Robert|Family organizer communications network system|
    EP2260910A1|2009-05-18|2010-12-15|Adidas Ag|Portable fitness monitoring systems with colour displays and applications thereof|
    US20120015779A1|2010-07-14|2012-01-19|Adidas Ag|Fitness Monitoring Methods, Systems, and Program Products, and Applications Thereof|
    US20080147422A1|2006-12-15|2008-06-19|Van Buskirk Thomast C|Systems and methods for integrating sports data and processes of sports activities and organizations on a computer network|
    WO2012075505A2|2010-12-03|2012-06-07|Athletepath, Inc.|Targeting advertisements to athletes|
    法律状态:
    2021-04-28| MM| Lapsed because of non-payment of the annual fee|Effective date: 20200731 |
    优先权:
    申请号 | 申请日 | 专利标题
    EP13176248.6A|EP2824614A1|2013-07-12|2013-07-12|Platform for planning and analyzing sports training for one or more athletes|
    EP131762486|2013-07-12|
    [返回顶部]