A method and system for analyzing competition results data

Abstract

This invention provides a method and system for analyzing race performance data, belonging to the field of data processing technology. The method includes: acquiring race performance data of road cyclists; obtaining the race route of the cyclists based on a race map and location information; correcting the race route based on video image information; comparing the corrected race route with the theoretically optimal route on the race map; extracting physiological parameter information and speed information at corresponding time points for sections with discrepancies; and obtaining optimization suggestions for the cyclists' race actions based on the extracted physiological parameter information and speed information. This method enables comprehensive analysis of the cyclists' race performance data, analyzing their performance from different perspectives, thereby more effectively identifying problems and providing more accurate and effective suggestions.

Description

Technical Field

[0001] This invention relates to the field of automatic navigation technology, and more specifically, to a method and system for analyzing competition results data. Background Technology

[0002] Analyzing athlete performance is of paramount importance, not only for evaluating athletic achievements but also for providing valuable guidance for future training and competition strategies. With continuous advancements in technology, these advancements have significantly improved the accuracy and depth of athletic performance evaluation. Whether it's the dynamic monitoring of athletes' physiological parameters or sensor- and camera-based sensing technologies, both enhance the comprehensiveness and precision of monitoring the entire competition process.

[0003] Therefore, how to provide an analytical method that can conduct in-depth analysis of athletes' competition process based on the acquired competition results data, and provide athletes with more accurate and effective suggestions, is an urgent problem to be solved. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a method and system for analyzing competition results data.

[0005] A first aspect of this invention provides a method for analyzing competition results data, the method comprising:

[0006] Acquire race performance data of road cyclists, including physiological parameters, location information, speed information, and video image information captured by cameras at various time points during the race.

[0007] The participants' race route is obtained based on the race map and the location information, and the race route is corrected based on the video image information;

[0008] The revised race route is compared with the theoretically optimal route on the map.

[0009] For road sections with discrepancies, extract physiological parameter information and speed information at the corresponding time points;

[0010] Based on the extracted physiological and speed information, optimization suggestions for the participants' competition movements are obtained.

[0011] Optionally, the step of correcting the race route based on the video image information specifically includes:

[0012] The video image information is used to determine the location of the participants in the track.

[0013] Compare the video image location with the location information according to the time point;

[0014] If any inconsistencies exist, the race route will be corrected based on the location of the video image.

[0015] Optionally, the step of comparing the corrected race route with the theoretically optimal route on the race map specifically includes:

[0016] The theoretical optimal route is obtained based on the game map, and the theoretical optimal route includes multiple optimal path locations ordered chronologically.

[0017] Compare the optimal path location with the location information that constitutes the race route;

[0018] The set of location information that differs is called the differential road segment.

[0019] Optionally, the speed information includes instantaneous speed and speed direction, and the step of obtaining optimization suggestions for the participants' competition movements based on the extracted physiological parameter information and speed information specifically includes:

[0020] Based on the specific differences between the optimal path location and the location information, the optimized actions are obtained at each location of the different road segments. The optimized actions include speed adjustment actions and direction adjustment actions.

[0021] Obtain quantified physical fitness information of participants;

[0022] Based on the physical fitness information, determine whether the participant is able to complete the optimized movement;

[0023] If possible, the optimized movements will be used as suggestions for improving the movements in the competition;

[0024] If not, the optimized movement will be adjusted to a feasible movement based on the limitations of the physical fitness information, and the adjusted optimized movement will be used as a suggestion for optimizing the competition movement.

[0025] Optionally, the physiological parameter information includes at least one of heart rate and human output power, and the step of determining whether the participant can complete the optimized movement based on the physical fitness information specifically includes:

[0026] Calculate the remaining available physical strength of the participants at their current position based on the physical fitness information and the physiological parameter information;

[0027] Determine whether the remaining available physical strength supports the completion of the optimized action.

[0028] Optionally, the step of obtaining optimization suggestions for the participants' competition movements based on the extracted physiological parameter information and speed information further includes:

[0029] After obtaining the quantified physical fitness information of the participants, calculate the optimal individual competition action plan based on the physical fitness information. The optimal individual competition action plan includes multiple optimal individual competition actions ordered in chronological order.

[0030] Calculate the theoretical physiological parameters of each participant when performing their optimal move in the competition.

[0031] Based on the video image information and the speed information, obtain the actual competition action at the optimal action time point for each individual in the competition;

[0032] Based on the specific differences between the optimal movements in individual competitions and the movements in actual competitions, suggestions for movement optimization are derived.

[0033] Based on the specific differences between theoretical physiological parameters and extracted physiological parameter information, suggestions for optimizing physiological parameters are derived.

[0034] Optionally, the step of calculating the optimal individual competition movement plan based on the physical fitness information specifically includes:

[0035] Starting from the starting point of the race, the amount of physical energy allocated to reach each optimal path position is calculated sequentially based on the aforementioned physical fitness information;

[0036] Calculate the optimal individual competition action required to reach each optimal path position based on the aforementioned energy allocation;

[0037] The optimal move scheme for an individual competition is obtained by combining the best moves from all individual competitions.

[0038] Optionally, the step of obtaining the quantified physical fitness information of the participants specifically includes:

[0039] Acquire the training data of the participants, including maximum heart rate, maximum heart rate duration, maximum human output power, and maximum human output power duration;

[0040] The training data is quantified according to the preset quantification rules to obtain the quantified physical fitness information of the participants.

[0041] Optionally, the step of adjusting the optimized movement to a feasible movement based on the limitations of the physical fitness information specifically includes:

[0042] Based on the aforementioned physical fitness information, the range of movements that the participants can support is determined.

[0043] The optimized action is adjusted to be the action whose range is closest to the optimized action.

[0044] A second aspect of the present invention provides a competition results data analysis system, comprising:

[0045] The data acquisition unit is used to acquire the race performance data of road cyclists. The race performance data includes the physiological parameter information, location information, speed information, and video image information captured by the camera at various time points during the race.

[0046] The route determination unit is used to obtain the participants' race route based on the race map and the location information, and to correct the race route based on the video image information.

[0047] The route comparison unit is used to compare the corrected race route with the theoretically optimal route on the race map.

[0048] The information extraction unit is used to extract physiological parameter information and speed information at corresponding time points for road sections with differences;

[0049] The analysis and optimization unit is used to generate optimization suggestions for the participants' competition movements based on the extracted physiological parameter information and speed information.

[0050] In summary, this invention provides a method and system for analyzing competition results data, which can comprehensively analyze the competition results data of participants, analyze the performance of participants from different perspectives, and thus more effectively identify problems and provide more accurate and effective suggestions. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of the competition results data analysis method according to an embodiment of the present invention;

[0053] Figure 2 This is a functional block diagram of the competition results data analysis system according to an embodiment of the present invention.

[0054] Figure label:

[0055] Data acquisition unit 110; route determination unit 120; area detection unit 130; information extraction unit 140; analysis and optimization unit 150. Detailed Implementation

[0056] Analyzing athlete performance is of paramount importance, not only for evaluating athletic achievements but also for providing valuable guidance for future training and competition strategies. With continuous advancements in technology, these advancements have significantly improved the accuracy and depth of athletic performance evaluation. Whether it's the dynamic monitoring of athletes' physiological parameters or sensor- and camera-based sensing technologies, both enhance the comprehensiveness and precision of monitoring the entire competition process.

[0057] Therefore, how to provide an analytical method that can conduct in-depth analysis of athletes' competition process based on the acquired competition results data, and provide athletes with more accurate and effective suggestions, is an urgent problem to be solved.

[0058] In view of this, the inventors of this invention have designed a method and system for analyzing competition results data.

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0060] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0061] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0062] In the description of this invention, it should be noted that the terms "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use. They are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. In addition, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0063] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0064] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0065] The following is a detailed description of a competition results data analysis method provided in this embodiment.

[0066] Please see Figure 1 This embodiment provides a method for analyzing competition results data, which includes:

[0067] Step S101: Obtain the race performance data of the road cyclists. The race performance data includes the participants' physiological parameters, location information, speed information, and video image information captured by cameras at various time points during the race.

[0068] During road cycling races, positioning modules (such as GPS and BeiDou modules) installed on participants' bikes can obtain real-time location information, while sensors (such as accelerometers and gyroscopes) can acquire speed information. Devices carried by participants can collect real-time physiological parameters such as heart rate and respiratory rate. Simultaneously, cameras installed above or along the track can capture video images of all participants throughout the race.

[0069] The data mentioned above enables a comprehensive record of the participants' performance throughout the competition. By conducting thorough and in-depth analysis of this data, we can not only evaluate the participants' performance but also provide valuable guidance for future training and competition strategies.

[0070] Step S102: Based on the competition map and the location information, the competition route of the participants is obtained, and the competition route is corrected according to the video image information.

[0071] The race map includes detailed information such as the track layout, curves, gradients, and elevation changes. By combining this with location information, the coordinates of the participants on the race map can be obtained.

[0072] In road cycling races, there are fixed course layouts, but these courses have a certain width. The specific race routes taken by participants are determined through continuously acquired location data. Different race routes affect race results. For example, riding closer to the inside of a corner can shorten the distance traveled, but it also increases the risk of falling, especially on wet or uneven surfaces. Choosing the appropriate route is crucial in such situations. Therefore, the choice of race route by participants is very important for different sections of the course.

[0073] It's important to note that because participants are constantly moving at high speeds during the race, the positioning module may experience positioning errors, leading to inaccurate location information. However, the video images recorded by the cameras can capture the participants' specific positions on the track, allowing the analysis of the race route derived from the location information to confirm the accuracy of the positioning data.

[0074] Specifically, as a preferred embodiment of the present invention, step S102 specifically includes:

[0075] The video image information is used to determine the location of the participants in the track.

[0076] Compare the video image location with the location information according to the time point;

[0077] If any inconsistencies exist, the race route will be corrected based on the location of the video image.

[0078] When determining the participants' positions on the track based on video image information, keyframes are first extracted from the video. Then, computer vision algorithms (such as YOLO, SSD, etc.) are used to detect participants and other landmarks (such as road signs, dividing lines, etc.) in the video to confirm the exact position of the participants, i.e., their video image position. The timestamps of the keyframes are then aligned with the timestamps of the data collected by the positioning module to ensure that the two are compared within the same timeframe.

[0079] When a significant deviation is found between the video image position and the location information, the race route must be corrected. The specific correction method can be one of the following:

[0080] 1. Interpolation method: Insert more points between two known location information to make the race route smoother.

[0081] 2. Reprojection method: Recalculate the participants' race route based on their actual positions in the video and map it back onto the map.

[0082] 3. Kalman Filter: The Kalman filter is used to fuse multi-source data (such as GPS data and video data) to improve the accuracy of race route calculation.

[0083] By following the steps above, we can effectively utilize the race map, location information, and video image information to obtain a more accurate race route.

[0084] Step S103: Compare the corrected race route with the theoretically optimal route of the race map.

[0085] There are two common methods for obtaining the theoretically optimal route based on the race map. One method is based on historical race results data. This involves obtaining the best historical data on the race map, extracting the routes from this historical data, and then making appropriate corrections to sections with obvious problems to arrive at the theoretically optimal route. The other method is based on an optimization mathematical model. The goal is to minimize the time to complete the entire race while minimizing energy consumption. An objective function is defined, and relevant information from the race map is used as conditions to construct an optimization model. Then, a suitable algorithm (such as the shortest path algorithm or genetic algorithm) is selected for calculation. Simulation results are then used to obtain the optimal route, along with information on the speed, power output, and estimated time for each section.

[0086] By comparing the actual route with the theoretically optimal route, participants' performance can be quantitatively evaluated, identifying which sections performed exceptionally well and which require improvement. Analyzing sections with significant deviations reveals technical weaknesses under specific conditions, such as cornering and climbing techniques. If substantial discrepancies are found between actual and theoretical performance on certain sections, race strategies can be adjusted to optimize performance on those sections. Furthermore, personalized training plans can be developed based on the comparison results, focusing on improving participants' weaknesses, such as strength and endurance training.

[0087] Specifically, as a preferred embodiment of the present invention, step S103 specifically includes:

[0088] The theoretical optimal route is obtained based on the game map, and the theoretical optimal route includes multiple optimal path locations ordered chronologically.

[0089] Compare the optimal path location with the location information that constitutes the race route;

[0090] The set of location information that differs is called the differential road segment.

[0091] When making comparisons, the first step is time synchronization, meaning the timestamps of the race route location information must match the timeframe of the optimal path location to ensure comparisons are performed at the same point in time. Next is spatial coordinate alignment, using GIS tools to spatially match the location information with the theoretically optimal path location on a map, ensuring both are compared within the same geographic coordinate system.

[0092] In addition, the race route and the theoretically optimal route can be visualized and overlaid on the map, which allows for a more intuitive view of the differences between the two.

[0093] You can set appropriate comparison thresholds as needed. Only when the difference between the two exceeds the threshold is it considered a discrepancy. By setting different thresholds, you can filter out road sections with differences and identify key road sections with significant differences (such as uphill sections, sharp turns, and sprint sections) for detailed analysis.

[0094] Based on the above scheme, as a preferred embodiment of the present invention, in addition to route comparison, performance index comparison can be further performed, including time comparison, speed comparison, and energy consumption comparison, to screen out road segments with performance differences. Specifically, the time comparison method is to calculate the difference between the actual time and the theoretical optimal time for each road segment, and identify the road segments with longer travel times. The speed comparison method is to compare the actual speed with the theoretical optimal speed to evaluate the speed control of the participants on different road segments. The energy consumption comparison method is to estimate the difference between the actual energy consumption and the theoretical optimal energy consumption based on the power output model to determine whether the participants have allocated their physical strength reasonably.

[0095] Step S104: For road sections with differences, extract physiological parameter information and speed information at the corresponding time points.

[0096] Through the above steps, the sections of road where the participants performed poorly were identified. Based on this, further adjustments were made according to the participants' specific performance on these sections. Therefore, it was necessary to extract the participants' physiological parameters and speed information at the corresponding time points when they were driving on these sections.

[0097] Step S105: Based on the extracted physiological parameter information and speed information, optimization suggestions for the participants' competition movements are obtained.

[0098] The methods for obtaining suggestions for optimizing competition actions can be selected based on the optimization direction of the participants. There are two main methods. One method is to provide optimization suggestions based on the best performance on the current competition map. In this case, the participants' physical fitness information does not need to be considered. The optimization suggestions obtained include both optimizations for competition actions and suggestions for improving physical fitness.

[0099] Another approach is to provide optimization suggestions for the competition movements that the participants can currently support and complete, based on their own physical fitness information. The optimization suggestions mainly include optimization of the competition movements at each time point, reasonable adjustment of physiological parameters, and reasonable allocation of physical strength, so that the participants can achieve the best competition results based on their current physical fitness.

[0100] Specifically, as a preferred embodiment of the present invention, step S105 specifically includes:

[0101] Based on the specific differences between the optimal path location and the location information, the optimized actions are obtained at each location of the different road segments. The optimized actions include speed adjustment actions and direction adjustment actions.

[0102] Obtain quantified physical fitness information of participants;

[0103] Based on the physical fitness information, determine whether the participant is able to complete the optimized movement;

[0104] If possible, the optimized movements will be used as suggestions for improving the movements in the competition;

[0105] If not, the optimized movement will be adjusted to a feasible movement based on the limitations of the physical fitness information, and the adjusted optimized movement will be used as a suggestion for optimizing the competition movement.

[0106] In practice, the first method involves directly comparing the optimal path location with the location information to derive corresponding optimization actions. These optimization actions include adjustments to both speed and direction. Speed ​​adjustments allow for more efficient use of the terrain and energy allocation, while direction adjustments ensure the route better matches the optimal path. Furthermore, as a preferred implementation, optimization actions may also include adjustments to heart rate, respiratory rate, and power output.

[0107] After obtaining the optimized movements, the physical fitness of the participants is further considered to determine whether they are capable of completing them. For example, if the optimized movements require the participants to increase their speed, but given their physical fitness, they may no longer be able to increase their speed, then the optimized movements need to be adjusted to make them achievable for the participants.

[0108] When judging whether a participant can complete the optimized action based on physical fitness information, it is necessary to base the assessment on the participant's quantified physical fitness information and the specific location of the current difference section on the competition map.

[0109] Specifically, as a preferred embodiment of the present invention, the step of obtaining the quantified physical fitness information of the participants specifically includes:

[0110] Acquire the training data of the participants, including maximum heart rate, maximum heart rate duration, maximum human output power, and maximum human output power duration;

[0111] The training data is quantified according to the preset quantification rules to obtain the quantified physical fitness information of the participants.

[0112] Physical fitness information is primarily obtained through training data recorded from past training sessions. Alternatively, historical competition performance data can be used. Among these, maximum heart rate, maximum heart rate duration, maximum power output, and maximum power output duration are the most convenient and accurate parameters in actual competition. These parameters can be directly obtained from commonly available smart wearable devices and are applicable to most types of sports. Other physical fitness information may include parameters such as heart rate variability, blood lactate concentration, oxygen saturation, muscle activation patterns, respiratory rate and depth, and core temperature.

[0113] After obtaining training data or historical performance data, this data is quantized and analyzed according to appropriate quantization rules to facilitate subsequent calculations. The choice of quantization rules is related to the subsequent parameter calculation steps. Commonly used quantization rules include:

[0114] Heart rate reserve percentage (HRR): Calculated using the formula (current heart rate - resting heart rate) / (maximum heart rate - resting heart rate) × 100. Used to assess exercise intensity.

[0115] Maximum heart rate duration (D-MHR): Records the time an athlete can maintain near or at their maximum heart rate, usually in seconds or minutes.

[0116] Average Heart Rate (AHR): The average heart rate during the entire training or competition period, reflecting the overall intensity of exercise.

[0117] Normalized Power (NP): Used to measure average power output during cycling, taking into account the impact of power fluctuations.

[0118] Functional Threshold Power (FTP): refers to the maximum average power that an athlete can continuously output over an hour, and is an important indicator of endurance.

[0119] Maximum Power Output Duration (D-MPO): Records the time an athlete can maintain near or at maximum power output, usually in seconds or minutes.

[0120] Based on quantified physical fitness information, at any point in time or along any section of the course during the competition, the actions that participants can currently perform can be estimated based on the parts of the competition they have already completed.

[0121] Specifically, in a preferred embodiment of the present invention, the physiological parameter information includes at least one of heart rate and human output power, and the step of determining whether the participant can complete the optimized movement based on the physical fitness information specifically includes:

[0122] Calculate the remaining available physical strength of the participants at their current position based on the physical fitness information and the physiological parameter information;

[0123] Determine whether the remaining available physical strength supports the completion of the optimized action.

[0124] Based on the participant's current location, we can determine how much of the race they have completed. Then, based on their performance in the completed portion (including speed, route, and power output in each section), we can calculate their remaining available physical strength or energy reserves. If the requirements of the optimized action exceed what their current available physical strength can support, it means that the participant cannot complete the optimized action at their current location, and the optimized action needs to be adjusted.

[0125] Specific adjustment methods include:

[0126] Based on the aforementioned physical fitness information, the range of movements that the participants can support is determined.

[0127] The optimized action is adjusted to be the action whose range is closest to the optimized action.

[0128] When adjusting movements, it is necessary to classify and process the specific content of the optimized movements. One category is directly related to the limitations of physical fitness. If increasing speed or output power is impossible to complete under the limitations of physical fitness, it should be adjusted to a range that can be supported. The other category is not directly related to the limitations of physical fitness, such as adjusting direction, maintaining or reducing speed, or reducing output power, which do not require adjustment.

[0129] After adjustments, the optimized movements that the participants can perform are obtained. By merging all the adjusted optimized movements with those that do not need adjustment, we obtain optimization suggestions for the entire competition.

[0130] As a preferred embodiment of the present invention, for the second method of obtaining competition action optimization suggestions described above, there is another implementation method. Specifically, step S105 further includes:

[0131] After obtaining the quantified physical fitness information of the participants, calculate the optimal individual competition action plan based on the physical fitness information. The optimal individual competition action plan includes multiple optimal individual competition actions ordered in chronological order.

[0132] Calculate the theoretical physiological parameters of each participant when performing their optimal performance in the competition.

[0133] Based on the video image information and the speed information, obtain the actual competition action at the optimal action time point for each individual in the competition;

[0134] Based on the specific differences between the optimal movements in individual competitions and the movements in actual competitions, suggestions for movement optimization are derived.

[0135] Based on the specific differences between theoretical physiological parameters and extracted physiological parameter information, suggestions for optimizing physiological parameters are derived.

[0136] When obtaining the optimal movements, the quantified physical fitness information of the participants is first referenced. Then, based on the competition map, an individual optimal movement plan is derived based on this physical fitness information. Since the individual optimal movement plan is generated based on the participants' physical fitness information, each individual optimal movement is within the participants' physical capabilities. Therefore, there is no need to consider whether the participants can complete the suggested movements; instead, movement optimization suggestions are derived directly based on the specific differences between the individual optimal movements and the actual competition movements. Simultaneously, to complete all the individual optimal movements within the individual optimal movement plan, participants need to adjust their physiological parameters accordingly, keeping them as consistent as possible with the theoretical physiological parameters required to achieve each individual optimal movement. Therefore, it is necessary to compare the theoretical physiological parameters with the extracted physiological parameter information, identify the differences, and then propose optimization suggestions for adjusting the physiological parameters.

[0137] The calculation of the optimal action plan for an individual competition can adopt the same approach as obtaining the theoretical optimal route, i.e., establishing a mathematical model for calculation. The difference lies in that, in addition to minimizing the time to complete the entire competition as the objective, it is also necessary to use the participant's physical fitness information as a constraint for simulation. Specifically, the steps for calculating the optimal action plan for an individual competition based on the physical fitness information include:

[0138] Starting from the starting point of the race, the amount of physical energy allocated to reach each optimal path position is calculated sequentially based on the aforementioned physical fitness information;

[0139] Calculate the optimal individual competition action required to reach each optimal path position based on the aforementioned energy allocation;

[0140] The optimal move scheme for an individual competition is obtained by combining the best moves from all individual competitions.

[0141] In the same competition map, the theoretical optimal route and the optimal path positions that constitute the theoretical optimal route are the same. However, considering that the physical fitness information of different participants is different, the amount of physical exertion required for different participants to reach each optimal path position is also different. Correspondingly, the individual optimal action to be performed to reach each optimal path position will also be different. It is necessary to conduct detailed simulation and calculation based on the specific quantitative values ​​of physical fitness information.

[0142] After obtaining the optimal action plan for an individual competition, the participant's performance in this competition is compared with the plan to obtain action optimization suggestions and physiological parameter optimization suggestions for different road sections.

[0143] The following is a specific example to illustrate this:

[0144] There is one participant with the following physical fitness data:

[0145] Maximum heart rate (MHR): 190 bpm

[0146] Resting heart rate (RHR): 50 bpm

[0147] Functional Threshold Power (FTP): 350 W

[0148] Maximum power output (MPO): 1000 W

[0149] Maximum heart rate duration (D-MHR): 60 seconds

[0150] Maximum human output power duration (D-MPO): 10 seconds

[0151] The race route is as follows:

[0152] Total distance: 100 kilometers

[0153] Flat road: 60 kilometers

[0154] Climbing: 20 kilometers

[0155] Downhill: 15 km

[0156] Sharp turn: 5 km

[0157] The real-time competition data for the participants is as follows:

[0158] Current heart rate (CHR): 170 bpm

[0159] Current power output (CPO): 280 W

[0160] Current speed (CS): 35 km / h

[0161] Current location (CP): 30 km completed

[0162] The following real-time analysis and action suggestions are provided:

[0163] (1) Flat road section:

[0164] The current speed is 35 km / h, slightly lower than the theoretical optimal speed (38 km / h).

[0165] The current power output ratio is 280 / 350 = 0.8, indicating room for improvement.

[0166] It is recommended to appropriately increase the cadence and power output to around 300 W to increase the speed to close to 38 km / h.

[0167] By taking advantage of the following effect within a large group, wind resistance is reduced and physical effort is saved.

[0168] (2) Uphill sections:

[0169] We are about to enter an uphill section, which is expected to be 10 kilometers long.

[0170] The current heart rate is 170 bpm, which is close to 89% of the maximum heart rate ((170−50)(190−50)×100(190−50)(170−50)×100).

[0171] It is recommended to adjust the gear ratio and use a lower gear to maintain a stable cadence and avoid premature fatigue.

[0172] Increase the power output to around 320 W, but avoid excessive physical exertion.

[0173] (3) Downhill section:

[0174] If there is a downhill section ahead, it is recommended to release the brakes and make full use of the downhill momentum to increase the speed to about 45 km / h.

[0175] Maintaining a low center of gravity and a stable posture reduces air resistance and improves downhill efficiency.

[0176] (4) Sharp bends:

[0177] Try to ride close to the inside to shorten the distance, but make sure you have enough grip to avoid falling.

[0178] Adjust your speed in advance based on road conditions and curve radius to ensure a smooth passage through curves.

[0179] Finally, the above analysis results and action suggestions were compiled into a detailed report for coaches and athletes to refer to.

[0180] In summary, the competition results data analysis method provided by this invention can comprehensively analyze the competition results data of participants, analyze their performance from different perspectives, and thus more effectively identify problems and provide more accurate and effective suggestions.

[0181] like Figure 2 As shown, the competition results data analysis system provided by this invention includes:

[0182] Data acquisition unit 110 is used to acquire race performance data of road cyclists. The race performance data includes physiological parameter information, location information, speed information and video image information captured by camera at various time points during the race.

[0183] The route determination unit 120 is used to obtain the competition route of the participants based on the competition map and the location information, and to correct the competition route according to the video image information;

[0184] The route comparison unit 130 is used to compare the corrected race route with the theoretically optimal route of the race map.

[0185] The information extraction unit 140 is used to extract physiological parameter information and speed information at corresponding time points for road sections with differences;

[0186] The analysis and optimization unit 150 is used to generate optimization suggestions for the participants' competition movements based on the extracted physiological parameter information and speed information.

[0187] The competition results data analysis system provided in this embodiment of the invention is used to implement the above-mentioned competition results data analysis method. Therefore, the specific implementation method is the same as the above method, and will not be repeated here.

[0188] In summary, this invention provides a method and system for analyzing competition results data, which can comprehensively analyze the competition results data of participants, analyze the performance of participants from different perspectives, and thus more effectively identify problems and provide more accurate and effective suggestions.

[0189] In the embodiments disclosed in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0190] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0191] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for analyzing competition results data, characterized in that, The method includes: Acquire race performance data of road cyclists, including physiological parameters, location information, speed information, and video image information captured by cameras at various time points during the race. The participants' race route is obtained based on the race map and the location information, and the race route is corrected based on the video image information; The revised race route is compared with the theoretically optimal route on the map. For road sections with discrepancies, extract physiological parameter information and speed information at the corresponding time points; Based on the extracted physiological and speed information, optimization suggestions for the participants' competition movements are obtained. The step of comparing the corrected race route with the theoretically optimal route on the race map specifically includes: The theoretical optimal route is obtained based on the game map, and the theoretical optimal route includes multiple optimal path locations ordered chronologically. Compare the optimal path location with the location information that constitutes the race route; The set of location information that differs is the differential road segment; The speed information includes instantaneous speed and speed direction. The step of obtaining optimization suggestions for the participants' competition movements based on the extracted physiological parameter information and speed information specifically includes: Based on the specific differences between the optimal path location and the location information, the optimized actions are obtained at each location of the different road segments. The optimized actions include speed adjustment actions and direction adjustment actions. Obtain quantified physical fitness information of participants; Based on the physical fitness information, determine whether the participant is able to complete the optimized movement; If possible, the optimized movements will be used as suggestions for improving the movements in the competition; If not, the optimized movement will be adjusted to a feasible movement based on the limitations of the physical fitness information, and the adjusted optimized movement will be used as a suggestion for optimizing the competition movement. After obtaining the quantified physical fitness information of the participants, calculate the optimal individual competition action plan based on the physical fitness information. The optimal individual competition action plan includes multiple optimal individual competition actions ordered in chronological order. Calculate the theoretical physiological parameters of each participant when performing their optimal performance in the competition. Based on the video image information and the speed information, obtain the actual competition action at the optimal action time point for each individual in the competition; Based on the specific differences between the optimal movements in individual competitions and the movements in actual competitions, suggestions for movement optimization are derived. Based on the specific differences between theoretical physiological parameters and extracted physiological parameter information, suggestions for optimizing physiological parameters are derived.

2. The method for analyzing competition results data according to claim 1, characterized in that, The step of correcting the race route based on the video image information specifically includes: The video image information is used to determine the location of the participants in the track. Compare the video image location with the location information according to the time point; If any inconsistencies exist, the race route will be corrected based on the location of the video image.

3. The method for analyzing competition results data according to claim 2, characterized in that, The physiological parameter information includes at least one of heart rate and human output power. The step of determining whether a participant can complete the optimized movement based on the physical fitness information specifically includes: Calculate the remaining available physical strength of the participants at their current position based on the physical fitness information and the physiological parameter information; Determine whether the remaining available physical strength supports the completion of the optimized action.

4. The method for analyzing competition results data according to claim 2, characterized in that, The steps for calculating the optimal individual competition movement plan based on the physical fitness information specifically include: Starting from the starting point of the race, the amount of physical energy allocated to reach each optimal path position is calculated sequentially based on the aforementioned physical fitness information; Calculate the optimal individual competition action required to reach each optimal path position based on the aforementioned energy allocation; The optimal move scheme for an individual competition is obtained by combining the best moves from all individual competitions.

5. The method for analyzing competition results data according to any one of claims 3-4, characterized in that, The steps for obtaining quantified physical fitness information of participants specifically include: Acquire the training data of the participants, including maximum heart rate, maximum heart rate duration, maximum human output power, and maximum human output power duration; The training data is quantified according to the preset quantification rules to obtain the quantified physical fitness information of the participants.

6. The method for analyzing competition results data according to claim 5, characterized in that, The step of adjusting the optimized movement to a feasible movement based on the limitations of the physical fitness information specifically includes: Based on the aforementioned physical fitness information, the range of movements that the participants can support is determined. The optimized action is adjusted to be the action whose range is closest to the optimized action.

7. A competition results data analysis system, characterized in that, include: The data acquisition unit is used to acquire the race performance data of road cyclists. The race performance data includes the physiological parameter information, location information, speed information, and video image information captured by the camera at various time points during the race. The route determination unit is used to obtain the participants' race route based on the race map and the location information, and to correct the race route based on the video image information. The route comparison unit is used to compare the corrected race route with the theoretically optimal route on the race map. The information extraction unit is used to extract physiological parameter information and speed information at corresponding time points for road sections with differences; The analysis and optimization unit is used to generate optimization suggestions for the participants' competition movements based on the extracted physiological parameter information and speed information; The route comparison unit is specifically used for: The theoretical optimal route is obtained based on the game map, and the theoretical optimal route includes multiple optimal path locations ordered chronologically. Compare the optimal path location with the location information that constitutes the race route; The set of location information that differs is the differential road segment; The analysis and optimization unit is specifically used for: Based on the specific differences between the optimal path location and the location information, the optimized actions are obtained at each location of the different road segments. The optimized actions include speed adjustment actions and direction adjustment actions. Obtain quantified physical fitness information of participants; Based on the physical fitness information, determine whether the participant is able to complete the optimized movement; If possible, the optimized movements will be used as suggestions for improving the movements in the competition; If not, the optimized movement will be adjusted to a feasible movement based on the limitations of the physical fitness information, and the adjusted optimized movement will be used as a suggestion for optimizing the competition movement. After obtaining the quantified physical fitness information of the participants, calculate the optimal individual competition action plan based on the physical fitness information. The optimal individual competition action plan includes multiple optimal individual competition actions ordered in chronological order. Calculate the theoretical physiological parameters of each participant when performing their optimal performance in the competition. Based on the video image information and the speed information, obtain the actual competition action at the optimal action time point for each individual in the competition; Based on the specific differences between the optimal movements in individual competitions and the movements in actual competitions, suggestions for movement optimization are derived. Based on the specific differences between theoretical physiological parameters and extracted physiological parameter information, suggestions for optimizing physiological parameters are derived.

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