Stride frequency adjustment prompting method and device, equipment and storage medium

Abstract

The invention discloses a stride frequency adjustment prompting method and device, equipment and a storage medium, and the method comprises the steps: obtaining the heart rate data of a competitor, determining the change rule of the heart rate data along with the time under the condition that the heart rate value in the heart rate data is greater than a preset heart rate threshold value, and determining the change rule of the heart rate data along with the time; predicting the target track complexity of the track where the competitors are located according to the change rule; mapping the obtained positioning information of the contestants to a track marking map, and determining the actual track complexity of the contestants according to a mapping result; and under the condition that the target track complexity is consistent with the actual track complexity, acquiring stride frequency data of the competitors, and determining stride frequency adjustment data of the competitors according to the heart rate data, the actual track complexity and the stride frequency data to prompt the competitors, so that the accuracy of stride frequency guidance can be improved, and the user experience is improved. And the heart rate data is ensured to be within the preset heart rate threshold range, so that the sports safety of the participants can be improved.

Description

Technical Field

[0001] The present application belongs to the field of computer technology, and specifically relates to a cadence adjustment prompt method, device, equipment and storage medium. Background Art

[0002] With the rise of sports enthusiasm, high-intensity endurance sports such as cross-country races, mountain marathons, and outdoor adventures are constantly developing. During competitions, a competitor's cadence is a key indicator affecting exercise efficiency, energy distribution, and sports safety. Providing appropriate cadence adjustment guidance for competitors is crucial for improving performance and ensuring safety.

[0003] Prior art methods for providing cadence adjustment guidance to participants primarily rely on wearable sensors to capture the participant's heart rate and cadence data in real time. The acquired heart rate data is then compared with a preset heart rate alarm threshold. If the heart rate exceeds the threshold, a cadence reduction prompt is triggered. However, prior art only prompts participants to reduce their cadence based on heart rate data. It fails to consider the impact of track complexity on cadence data and cannot determine specific data for cadence adjustment, making it difficult to provide reasonable cadence adjustment prompts to participants. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a cadence adjustment prompt method, device, equipment and storage medium, which solves the problem in the prior art that cadence adjustment prompts cannot be performed reasonably and accurately. By predicting the target track complexity of the track where the contestant is located based on the change pattern of heart rate data over time, when the target track complexity is consistent with the actual track complexity, the contestant's cadence adjustment data is determined based on the heart rate data, the actual track complexity and the cadence data. This can achieve the purpose of providing cadence adjustment guidance in combination with the track complexity and determining the specific data for cadence adjustment, which is beneficial to improving the accuracy of cadence guidance and ensuring that the heart rate data is within the preset heart rate threshold range, which is beneficial to improving the sports safety of the contestants.

[0005] In a first aspect, an embodiment of the present application provides a cadence adjustment prompt method, the method comprising: Obtaining the contestant's heart rate data, and if a heart rate value in the heart rate data exceeds a preset heart rate threshold, determining a temporal variation pattern of the heart rate data, and predicting a target track complexity of the contestant's track based on the variation pattern; Mapping the acquired location information of the contestants to the track annotation map, and determining the actual track complexity of the contestants based on the mapping results; When the target track complexity is consistent with the actual track complexity, the contestant's cadence data is obtained, and the contestant's cadence adjustment data is determined based on the heart rate data, the actual track complexity and the cadence data, which is used to prompt the contestant.

[0006] Furthermore, the target track complexity of the contestant's track is predicted based on the change pattern, including: Determine the contestant's heart rate sudden change moment and heart rate sudden change value based on the change pattern, and determine the contestant's heart rate fluctuation ratio based on the heart rate sudden change value and the contestant's average heart rate before the heart rate sudden change moment; Match the average heart rate and the heart rate fluctuation ratio with the preset track complexity comparison table respectively, and determine the initial track complexity corresponding to the average heart rate and the track complexity fluctuation ratio corresponding to the heart rate fluctuation ratio based on the matching results; The target track complexity of the contestant's track is determined based on the initial track complexity and the track complexity fluctuation ratio.

[0007] Furthermore, the heart rate fluctuation ratio is matched with the preset track complexity comparison table, including: Obtaining the contestant's competition frequency and determining the heart rate sensitivity coefficient corresponding to the competition frequency; The heart rate fluctuation ratio is adjusted based on the heart rate sensitivity coefficient, and the track complexity fluctuation ratio corresponding to the adjustment result of the heart rate fluctuation ratio is determined according to a preset track complexity comparison table.

[0008] Furthermore, the actual track complexity of the contestants is determined based on the mapping results, including: Determine the target motion trajectory of the contestant at the moment of the sudden change in heart rate in the mapping results, as well as the slope type, slope level, track flatness, and number of turns within the trajectory range of the target motion trajectory; determining a first track complexity corresponding to a slope type and a slope level, a second track complexity corresponding to a track flatness, and a third track complexity corresponding to a number of turns; Calculate the weighted sum of the complexity of the first track, the complexity of the second track, and the complexity of the third track to obtain the actual track complexity of the contestant.

[0009] Furthermore, determining the first track complexity corresponding to the slope type and slope level includes: Determining a first track complexity parameter corresponding to the slope level, identifying whether the slope type is downhill, and comparing the slope parameter with a preset impedance slope threshold; When the slope type is downhill and the slope parameter is less than the preset impedance slope threshold, the sign of the first track complexity parameter is determined to be negative, and the first track complexity corresponding to the slope type and slope level is determined according to the first track complexity parameter and the sign.

[0010] Furthermore, the competitor's cadence adjustment data is determined based on the heart rate data, actual track complexity, and cadence data, including: Determine the competitor's baseline cadence data based on the cadence data before the heart rate mutation moment, and determine the first cadence influence coefficient corresponding to the baseline cadence data; Calculating the heart rate difference between the heart rate mutation value and the preset heart rate threshold, determining the heart rate deviation level corresponding to the heart rate difference, and the second step frequency influence coefficient corresponding to the heart rate deviation level; Determine the third cadence influence coefficient corresponding to the actual track complexity, determine the cadence adjustment requirement value based on the heart rate difference, the first step influence coefficient, the second cadence influence coefficient and the third cadence influence coefficient, and determine the contestant's cadence adjustment data based on the cadence adjustment requirement value and the baseline cadence data.

[0011] Furthermore, the consistency check process between the target track complexity and the actual track complexity includes: Expand the complexity range of the actual track complexity according to the preset complexity floating scale to obtain the maximum actual track complexity and the minimum actual track complexity centered on the actual track complexity; The target track complexity is compared with the maximum actual track complexity and the minimum actual track complexity. When the target track complexity is less than or equal to the maximum actual track complexity and the target track complexity is greater than the minimum actual track complexity, it is determined that the target track complexity is consistent with the actual track complexity.

[0012] In a second aspect, an embodiment of the present application provides a cadence adjustment prompting device, the device comprising: The target track complexity prediction module is used to obtain the heart rate data of the contestant. If there is a heart rate value greater than a preset heart rate threshold in the heart rate data, the module determines the change pattern of the heart rate data over time and predicts the target track complexity of the contestant's track based on the change pattern. The actual track complexity determination module is used to map the acquired location information of the contestants to the track annotation map and determine the actual track complexity of the contestants based on the mapping results; The cadence prompt module is used to obtain the contestant's cadence data when the target track complexity is consistent with the actual track complexity, and determine the contestant's cadence adjustment data based on the heart rate data, the actual track complexity and the cadence data, which is used to prompt the contestant.

[0013] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0015] In the fifth aspect, an embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor of the device reads and executes the computer program from the computer-readable storage medium, so that the device performs the method described in the first aspect.

[0016] In an embodiment of the present application, the heart rate data of the contestant is obtained. When there is a heart rate value greater than a preset heart rate threshold in the heart rate data, the change pattern of the heart rate data over time is determined, and the target track complexity of the track where the contestant is located is predicted based on the change pattern; the obtained positioning information of the contestant is mapped to the track annotation map, and the actual track complexity of the contestant is determined based on the mapping result; when the target track complexity is consistent with the actual track complexity, the cadence data of the contestant is obtained, and the cadence adjustment data of the contestant is determined based on the heart rate data, the actual track complexity and the cadence data, which is used to prompt the contestant. The above-mentioned cadence adjustment prompt method solves the problem in the existing technology that cadence adjustment prompts cannot be performed reasonably and accurately. By predicting the target track complexity of the track where the contestant is located based on the change pattern of heart rate data over time, when the target track complexity is consistent with the actual track complexity, the contestant's cadence adjustment data is determined based on the heart rate data, the actual track complexity and cadence data. This can achieve the purpose of providing cadence adjustment guidance in combination with track complexity and determining the specific data for cadence adjustment, which is beneficial to improving the accuracy of cadence guidance and ensuring that the heart rate data is within the preset heart rate threshold range, which is beneficial to improving the sports safety of the contestants. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of a cadence adjustment prompt method provided by an embodiment of the present application; Figure 2 is a schematic diagram of the track marking map provided by this application; Figure 3 This is a flow chart of predicting target track complexity provided by an embodiment of the present application; Figure 4This is a flow chart for determining the actual track complexity provided by an embodiment of the present application; Figure 5 This is a flow chart of determining cadence adjustment data provided by an embodiment of the present application; Figure 6 This is a structural block diagram of a cadence adjustment prompting device provided in an embodiment of the present application; Figure 7 This is a structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] To further clarify the objectives, technical solutions, and advantages of this application, an optional detailed description of specific embodiments of this application is provided below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are intended solely to illustrate this application and are not intended to limit it. It should also be noted that, for ease of description, the drawings only illustrate portions relevant to this application, not all of them. Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts depict the various operations (or steps) as sequential processes, many of the operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process may terminate upon completion of its operations, but may also include additional steps not shown in the accompanying drawings. The process may correspond to a method, function, procedure, subroutine, subprogram, or the like.

[0019] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0020] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0021] First of all, the usage scenario of this solution can be a scenario in which the cadence of the contestants is guided during competitions such as marathons and cross-country races, especially in the scenario in which the contestants are prompted to adjust their cadence based on the contestants' heart rate data and the actual track complexity during high-intensity and high-complexity endurance sports such as mountain marathons and cross-country races. By predicting the target track complexity of the contestant's track based on the change pattern of the heart rate data over time, and determining the contestant's cadence adjustment data based on the heart rate data, the actual track complexity and the cadence data when the target track complexity is consistent with the actual track complexity, the purpose of guiding the cadence adjustment in combination with the track complexity and determining the specific data for the cadence adjustment can be achieved, which is conducive to improving the accuracy of the cadence guidance and ensuring that the heart rate data is within the preset heart rate threshold range, which is conducive to improving the sports safety of the contestants. Based on the above usage scenarios, it can be understood that the execution subject of each step in this solution can be a computer device, which refers to any electronic device with data calculation, processing and storage capabilities, such as a mobile phone, PC (Personal Computer), tablet computer and other terminal devices, or a server and other devices, which are not limited in this embodiment of the present application.

[0022] The following, in conjunction with the accompanying drawings, describes in detail a cadence adjustment prompt method, apparatus, device, and storage medium provided by the embodiments of the present application through specific embodiments and their application scenarios.

[0023] Figure 1 This is a flow chart of a step frequency adjustment prompt method provided by an embodiment of the present application. Figure 1 As shown, the specific steps include: S101, obtaining the contestant's heart rate data, and when there is a heart rate value greater than a preset heart rate threshold in the heart rate data, determining a change pattern of the heart rate data over time, and predicting the target track complexity of the contestant's track based on the change pattern.

[0024] Among them, the preset heart rate threshold can be a pre-set heart rate critical value that represents the contestant's optimal exercise state. The average heart rate of the contestant in the optimal exercise state can be determined based on the contestant's exercise data and heart rate data before the current moment as the preset heart rate threshold. The change pattern of heart rate data over time can be the change of the contestant's heart rate value over time before the current moment. The target track complexity can be the theoretical track passing difficulty corresponding to the contestant's heart rate data. Since the track passing difficulty corresponds to different types, slopes and flatness of tracks, when the contestant passes different tracks at the same speed or step frequency, the heart rate data will be affected by the track passing difficulty, resulting in fluctuations in the heart rate data, and even exceeding the preset heart rate threshold. Therefore, the theoretical track passing difficulty corresponding to the contestant's current track can be predicted based on the change pattern of the contestant's heart rate data as the target track complexity.

[0025] In one embodiment, the heart rate data of a contestant can be obtained in real time, and the size relationship between the heart rate data and a preset heart rate threshold can be compared in real time. If there is a heart rate value in the heart rate data that is greater than the preset heart rate threshold, the change pattern of the heart rate data over time can be determined based on the heart rate values ​​in the time series within a preset time period before the current moment. Based on the change pattern, the duration of the contestant's same heart rate change trend and the maximum heart rate under the trend can be determined. The heart rate change rate can be calculated based on the maximum heart rate and the duration. In addition, a correspondence between a target track complexity and a heart rate change rate range is preset, and the target track complexity of the contestant's current track can be determined based on the target heart rate change rate range to which the heart rate change rate belongs and the corresponding relationship.

[0026] S102: Map the acquired location information of the contestant to the track annotation map, and determine the actual track complexity of the contestant based on the mapping result.

[0027] The positioning information may be the position coordinates of the contestant in the actual spatial coordinate system. For example, the longitude and latitude of the contestant. The track annotation map may be an electronic map that is annotated with various terrain feature data and track attributes of the track. The track annotation map may include information such as the track type, the corresponding kilometer of the track, the track flatness, and the track slope. The mapping result may be the position coordinates obtained by converting the position coordinates of the contestant in the actual spatial coordinate system to the coordinate system of the track annotation map. The actual track complexity may be the actual track difficulty of the contestant's current track.

[0028] Figure 2 This is a schematic diagram of the track marking map provided by this application. Figure 2As shown, the figure includes the track path, track starting point marker, track end marker, supply station marker, uphill starting point marker, uphill end marker, downhill starting point marker, downhill end marker, and turn marker. Each marker stores the corresponding track information. For example, an uphill marker in the figure stores the name of the marker as uphill starting point, the slope is X, the total uphill length is Y, and the road flatness of the uphill stage is K. The terrain, length, and attributes of each track can be determined by reading the data stored in the marker. The figure also includes the position of the contestants on the track annotated map after mapping their positioning information to the track annotated map. The tracks not marked in the figure are all flat tracks.

[0029] In one embodiment, the acquired competitor's location information can be converted to the track annotated map coordinate system based on the conversion relationship between the actual spatial coordinate system and the track annotated map coordinate system determined during the track annotated map construction process to obtain a mapping result. Track attribute information such as the track type, track flatness, and track slope of the competitor's actual track can be determined based on the map annotation data of the competitor's track in the mapping result. The actual track complexity of the competitor can be determined by calculating the sum of the track complexity corresponding to each piece of track attribute information.

[0030] S103, when the target track complexity is consistent with the actual track complexity, the cadence data of the contestant is obtained, and the cadence adjustment data of the contestant is determined based on the heart rate data, the actual track complexity and the cadence data, so as to prompt the contestant.

[0031] Cadence data can be the number of steps a competitor takes per unit time at the current moment. Cadence data can influence a competitor's speed. Cadence adjustment data can represent the cadence value a competitor needs to achieve to adapt to the complexity of the track while maintaining a preset heart rate threshold.

[0032] In one embodiment, since the difficulty of the track and the contestant's own physiological abnormalities may cause the contestant's heart rate to exceed the threshold heart rate threshold, the target track complexity and the actual track complexity can be checked for consistency. When the target track complexity is consistent with the actual track complexity, it can be determined that the contestant's heart rate abnormality is caused by the increase in the track complexity of the track. At this time, the contestant's cadence data at the current moment can be obtained through the cadence sensor, and the difference between the heart rate data and the preset heart rate threshold can be calculated. The ratio of the difference to the preset heart rate threshold is calculated to determine the degree of heart rate deviation. The first cadence adjustment value is determined based on the product of the heart rate deviation degree and the cadence data. The second cadence adjustment value is determined based on the product of the first cadence adjustment value and the actual track complexity. The second cadence adjustment value is rounded to the nearest integer, and the difference between the cadence data and the rounded result is used as the contestant's cadence adjustment data. The cadence adjustment data is sent to the contestant's sports bracelet to prompt the contestant to adjust the cadence and maintain optimal exercise status.

[0033] In one embodiment, the process of performing consistency verification on the target track complexity and the actual track complexity includes: expanding the complexity range of the actual track complexity according to a preset complexity floating scale to obtain the maximum actual track complexity and the minimum actual track complexity centered on the actual track complexity; comparing the target track complexity with the maximum actual track complexity and the minimum actual track complexity, respectively, and determining that the target track complexity is consistent with the actual track complexity when the target track complexity is less than or equal to the maximum actual track complexity and the target track complexity is greater than the minimum actual track complexity.

[0034] Among them, the preset complexity floating scale can be a pre-set threshold that indicates that the actual track complexity is allowed to fluctuate within a certain range. Expanding the complexity range of the actual track complexity by using the preset complexity floating scale can provide flexibility for the consistency judgment of the track complexity, enhance the robustness of the judgment, and avoid the problem of inaccurate complexity consistency judgment results due to estimation errors of the actual track complexity. The preset complexity floating scale can be set based on the deviation between the target track complexity obtained by predicting the change pattern of the historical heart rate data of the contestants over time and the actual track complexity. The maximum actual track complexity can be the maximum value that the actual track complexity is allowed to reach. The minimum actual track complexity can be the minimum value that the actual track complexity is allowed to reach.

[0035] In one embodiment, the actual track complexity can be expanded by adding and subtracting the preset complexity floating scale from the actual track complexity to obtain a maximum and minimum actual track complexity centered on the actual track complexity. The target track complexity is then compared with the maximum and minimum actual track complexities. If the target track complexity is less than or equal to the maximum actual track complexity and greater than the minimum actual track complexity, the target track complexity is determined to be consistent with the actual track complexity.

[0036] This solution expands the complexity range of the actual track complexity according to a preset complexity floating scale, and compares the target track complexity with the boundary values ​​of the complexity range expansion result to determine whether the target track complexity is consistent with the actual track complexity. This can improve the robustness of the consistency judgment, and thus help improve the accuracy of the judgment results on the cause of abnormal heart rate.

[0037] The technical solution provided in the embodiment of the present application obtains the heart rate data of the contestants, and when there is a heart rate value greater than a preset heart rate threshold in the heart rate data, determines the change pattern of the heart rate data over time, and predicts the target track complexity of the track where the contestants are located based on the change pattern; maps the obtained positioning information of the contestants to the track annotation map, and determines the actual track complexity of the contestants based on the mapping result; when the target track complexity is consistent with the actual track complexity, obtains the cadence data of the contestants, and determines the cadence adjustment data of the contestants based on the heart rate data, the actual track complexity and the cadence data, which is used to prompt the contestants. The above-mentioned cadence adjustment prompt method solves the problem in the existing technology that cadence adjustment prompts cannot be performed reasonably and accurately. By predicting the target track complexity of the track where the contestant is located based on the change pattern of heart rate data over time, when the target track complexity is consistent with the actual track complexity, the contestant's cadence adjustment data is determined based on the heart rate data, the actual track complexity and cadence data. This can achieve the purpose of providing cadence adjustment guidance in combination with track complexity and determining the specific data for cadence adjustment, which is beneficial to improving the accuracy of cadence guidance and ensuring that the heart rate data is within the preset heart rate threshold range, which is beneficial to improving the sports safety of the contestants.

[0038] Figure 3 This is a flow chart of predicting the target track complexity provided by the embodiment of the present application. Figure 3 As shown, the specific steps include: S301, determining the contestant's heart rate mutation moment and heart rate mutation value according to the variation rule, and determining the contestant's heart rate fluctuation ratio according to the heart rate mutation value and the contestant's average heart rate before the heart rate mutation moment.

[0039] The heart rate sudden change moment may be the period of time during which the heart rate exceeds a preset heart rate threshold. The heart rate sudden change value may be the heart rate value reported by the athlete's sports wristband at the moment of the sudden change. The heart rate fluctuation ratio may be data indicating the degree to which the heart rate exceeds the preset heart rate threshold.

[0040] In one embodiment, a curve of the contestant's heart rate changes over time can be plotted based on the change pattern, the intersection of the change curve and the line corresponding to the preset heart rate threshold can be identified, and the heart rate reporting moment after the intersection in the change curve and when the heart rate value is greater than the preset heart rate threshold can be identified. The heart rate reporting moment is used as the contestant's heart rate sudden change moment, and the heart rate value corresponding to the heart rate sudden change moment is read to obtain the heart rate sudden change value. The difference between the heart rate sudden change value and the contestant's average heart rate before the heart rate sudden change moment is calculated, and the ratio of the difference to the average heart rate is calculated to obtain the contestant's heart rate fluctuation ratio.

[0041] S302, matching the average heart rate and the heart rate fluctuation ratio with a preset track complexity comparison table respectively, and determining the initial track complexity corresponding to the average heart rate and the track complexity fluctuation ratio corresponding to the heart rate fluctuation ratio according to the matching results.

[0042] The preset track complexity comparison table may include a plurality of pre-set track complexities, the average heart rate range corresponding to each track complexity, the unit track complexity fluctuation ratio, and the unit heart rate fluctuation ratio corresponding to the unit track complexity fluctuation ratio. The initial track complexity may be the track complexity corresponding to the average heart rate before the heart rate sudden change.

[0043] In one embodiment, the average heart rate can be matched against each heart rate average range in a preset track complexity comparison table to determine the target heart rate average range to which the average heart rate belongs and the target track complexity corresponding to the target heart rate average range, thereby obtaining an initial track complexity. The ratio of the heart rate fluctuation ratio to the unit heart rate fluctuation ratio is calculated to obtain the number of unit heart rate fluctuation ratios included in the heart rate fluctuation ratio. Based on the number and the unit track complexity fluctuation ratio, the track complexity fluctuation ratio corresponding to the heart rate fluctuation ratio is determined.

[0044] In one embodiment, the heart rate fluctuation ratio is matched with a preset track complexity comparison table, including: obtaining the competition frequency of the contestants and determining the heart rate sensitivity coefficient corresponding to the competition frequency; adjusting the heart rate fluctuation ratio based on the heart rate sensitivity coefficient, and determining the track complexity fluctuation ratio corresponding to the adjustment result of the heart rate fluctuation ratio according to the preset track complexity comparison table.

[0045] Participation frequency can be the total number of times a contestant participates within a preset statistical period. Participation frequency can indicate a contestant's participation activity and experience. Heart rate sensitivity can be a parameter related to participation frequency that quantifies the degree to which a contestant's heart rate fluctuates due to external influences.

[0046] In one embodiment, the historical competition time of a contestant can be obtained to determine the competition frequency of the contestant, and the heart rate sensitivity coefficient corresponding to the competition frequency can be determined, the heart rate fluctuation ratio can be adjusted according to the heart rate sensitivity coefficient, and the number of unit heart rate fluctuation ratios included in the heart rate fluctuation ratio adjustment result can be calculated, and the track complexity fluctuation ratio corresponding to the heart rate fluctuation ratio adjustment result can be determined based on the number and the unit track complexity fluctuation ratio in the preset track complexity comparison table.

[0047] This solution adjusts the heart rate fluctuation ratio by determining the heart rate sensitivity coefficient corresponding to the contestant's competition frequency, and determines the track complexity fluctuation ratio corresponding to the adjustment result of the heart rate fluctuation ratio according to the preset track complexity comparison table. It can combine the parameter contestant's competition experience to predict the track complexity, thereby improving the accuracy of the track complexity fluctuation ratio calculation.

[0048] S303: Determine the target track complexity of the contestant's track based on the initial track complexity and the track complexity fluctuation ratio.

[0049] In one embodiment, a track complexity fluctuation value of the contestant's track is calculated based on the initial track complexity and the track complexity fluctuation ratio, and a target track complexity of the contestant's track is determined based on the initial track complexity and the track complexity fluctuation value.

[0050] The technical solution provided in the embodiments of the present application determines the average heart rate and heart rate fluctuation ratio of the contestants, matches the average heart rate and heart rate fluctuation ratio with a preset track complexity comparison table, determines the initial track complexity corresponding to the average heart rate, and the track complexity fluctuation ratio corresponding to the heart rate fluctuation ratio, and obtains the target track complexity of the track where the contestants are located, which can improve the accuracy of the target track complexity prediction results.

[0051] Figure 4 This is a flow chart for determining the actual track complexity provided by the embodiment of the present application. Figure 4 As shown, the specific steps include: S401, determining the target motion trajectory of the contestant at the moment of the sudden change in heart rate in the mapping result, as well as the slope type, slope level, track flatness, and number of turns within the trajectory range of the target motion trajectory.

[0052] The target motion trajectory may be a preset motion trajectory corresponding to the location of the contestant at the moment of the sudden change in heart rate. The preset motion trajectory may be a trajectory that the contestant needs to follow when passing each track, which is pre-generated based on the shape and length of each track in the track annotation map. The trajectory range may be the range corresponding to the starting point of the trajectory and the current location of the contestant in the target motion trajectory. The slope type may include flat road, uphill and downhill. The slope level may be data describing the degree of inclination of the track. The track flatness may be data indicating the degree of bumpiness of the track. The higher the track flatness, the less impact it has on the contestant's exercise resistance and heart rate.

[0053] In one embodiment, the target motion trajectory of the contestant at the moment of the sudden change in heart rate can be determined based on the position of the contestant in the track marked map at the moment of the sudden change in heart rate in the mapping results, and the preset motion trajectory to which the position belongs, and the slope type, slope level, track flatness and number of turns of the track within the trajectory range of the target motion trajectory marked in the track marked map can be read.

[0054] S402 : Determine a first track complexity corresponding to the slope type and slope level, a second track complexity corresponding to the track flatness, and a third track complexity corresponding to the number of turns.

[0055] The first track complexity can be the difficulty of navigating a track with a certain slope type and slope level. The second track complexity can be the difficulty of navigating a track with a certain flatness. The third track complexity can be the difficulty of navigating a track with a certain number of turns. The higher the slope type and slope level, the higher the first track complexity. The lower the flatness, the higher the second track complexity. The greater the number of turns, the higher the third track complexity.

[0056] In one embodiment, a first track complexity corresponding to the slope type and slope level, a second track complexity corresponding to the track flatness, and a third track complexity corresponding to the number of turns can be determined based on the correspondence between the track complexity and the factors affecting the track complexity.

[0057] In one embodiment, determining a first track complexity corresponding to a slope type and a slope level includes: determining a first track complexity parameter corresponding to the slope level, identifying whether the slope type is downhill, and comparing the slope parameter with a preset impedance slope threshold; when the slope type is downhill and the slope parameter is less than the preset impedance slope threshold, determining that the sign of the first track complexity parameter is a negative sign, and determining the first track complexity corresponding to the slope type and slope level based on the first track complexity parameter and the sign.

[0058] The preset impedance slope threshold can be a pre-set maximum slope value that reduces the complexity of the track when the slope type is downhill. When the track type is downhill and the slope is small, the contestants can use gravity to save energy, and the track complexity is reduced. When the slope is too steep, the contestants need to bear additional burdens to maintain stability and safety, resulting in increased track complexity.

[0059] In one embodiment, a first track complexity parameter corresponding to the slope level can be determined, and whether the slope type is downhill can be identified. The slope parameter is then compared with a preset impedance slope threshold. If the slope parameter is less than the preset impedance slope threshold, the slope type and slope level are determined to reduce track complexity. If the slope parameter is greater than or equal to the preset impedance slope threshold, the slope type and slope level are determined to increase track complexity. If the slope type is downhill and the slope parameter is less than the preset impedance slope threshold, the sign of the first track complexity parameter can be determined to be negative. Based on the first track complexity parameter and its sign, the first track complexity corresponding to the slope type and slope level is determined.

[0060] This solution determines that the sign of the first track complexity parameter is negative when the slope type of the track is downhill and the slope parameter is less than the preset impedance slope threshold. The first track complexity corresponding to the slope type and slope level is determined based on the first track complexity parameter and sign. This can achieve the purpose of further dividing the track complexity of the downhill track and improve the accuracy of the first track complexity.

[0061] S403 , calculating the weighted sum of the first track complexity, the second track complexity, and the third track complexity to obtain the actual track complexity of the contestant.

[0062] In one embodiment, the actual track complexity of the competitor can be obtained by calculating a weighted sum of the first track complexity, the second track complexity, and the third track complexity based on a first weight corresponding to the first track complexity, a second weight corresponding to the second track complexity, and a third weight corresponding to the third track complexity. The first weight represents the influence of slope type and slope level on track complexity, the second weight represents the influence of track flatness on track complexity, and the third weight represents the influence of the number of turns on track complexity.

[0063] The technical solution provided in the embodiment of the present application obtains the actual track complexity of the contestant by determining the target motion trajectory of the contestant at the moment of sudden change in heart rate in the mapping result, as well as the first track complexity corresponding to the slope type and slope level of the target motion trajectory, the second track complexity corresponding to the track flatness, and the third track complexity corresponding to the number of turns, thereby improving the accuracy of the calculation results of the actual track complexity.

[0064] Figure 5 This is a flow chart of determining the step frequency adjustment data provided by the embodiment of the present application. Figure 5 As shown, the specific steps include: S501, determining the baseline cadence data of the contestant based on the cadence data before the heart rate mutation moment, and determining the first cadence influence coefficient corresponding to the baseline cadence data.

[0065] The baseline cadence data may be the average cadence of the contestant on the current track before the sudden change in heart rate. The baseline cadence data represents the contestant's cadence when their heart rate is stable. The first cadence impact coefficient may be a cadence correction parameter set based on the baseline cadence. Different baseline cadence data correspond to different adjustment sensitivities. For example, when the baseline cadence is high, a small cadence adjustment can significantly affect heart rate, and the first cadence impact coefficient is small. When the baseline cadence is low, a larger cadence adjustment is required to effectively adjust heart rate, and the first cadence impact coefficient is large.

[0066] In one embodiment, the baseline cadence data of the contestant can be determined based on the cadence data before the heart rate mutation moment, and the first cadence influence coefficient corresponding to the baseline cadence data can be determined based on the magnitude of the baseline cadence data.

[0067] S502, calculating the heart rate difference between the heart rate mutation value and the preset heart rate threshold, determining the heart rate deviation level corresponding to the heart rate difference, and the second cadence influence coefficient corresponding to the heart rate deviation level.

[0068] The second cadence influence coefficient may be the degree of influence of the heart rate deviation on the cadence adjustment. The greater the heart rate deviation, the greater the cadence adjustment required, and the greater the second cadence influence coefficient.

[0069] In one embodiment, the heart rate difference between the heart rate mutation value and the preset heart rate threshold can be calculated, and the heart rate deviation level corresponding to the heart rate difference can be determined based on the correspondence between the heart rate deviation level and the heart rate difference range, and the second step frequency influence coefficient corresponding to the heart rate deviation level can be determined based on the size of the heart rate deviation level.

[0070] S503, determining a third cadence influence coefficient corresponding to the actual track complexity, determining a cadence adjustment requirement value based on the heart rate difference, the first cadence influence coefficient, the second cadence influence coefficient, and the third cadence influence coefficient, and determining the contestant's cadence adjustment data based on the cadence adjustment requirement value and the baseline cadence data.

[0071] The third cadence influence coefficient can represent the degree to which track complexity affects cadence adjustment. The greater the track complexity, the greater the required cadence adjustment and the larger the third cadence influence coefficient. The required cadence adjustment value can represent the total cadence adjustment required to bring the heart rate within a preset heart rate threshold.

[0072] In one embodiment, a third cadence influence coefficient corresponding to the actual track complexity can be determined based on the actual track complexity, and the product of the heart rate difference, the first step influence coefficient, the second cadence influence coefficient, and the third cadence influence coefficient can be calculated to obtain a cadence adjustment requirement. The competitor's cadence adjustment data can then be determined based on the cadence adjustment requirement and the baseline cadence data. For example, if the first cadence influence coefficient is 1.0, the heart rate difference is 20 beats / minute, the second cadence influence coefficient is 1.5, and the third cadence influence coefficient is 1.3, the cadence adjustment requirement = heart rate difference × first cadence influence coefficient × second cadence influence coefficient × third cadence influence coefficient = 20 beats / minute × 1.0 × 1.5 × 1.3 = 39, meaning an adjustment of 39 steps / minute is required.

[0073] The technical solution provided in the embodiment of the present application determines the cadence adjustment requirement value by determining the first cadence influence coefficient corresponding to the baseline cadence data before the heart rate mutation moment, the second cadence influence coefficient corresponding to the heart rate deviation level, and the third cadence influence coefficient corresponding to the actual track complexity, and determines the cadence adjustment data of the contestant based on the cadence adjustment requirement value and the baseline cadence data, thereby achieving the purpose of multi-dimensional cadence adjustment and improving the accuracy of the cadence adjustment results.

[0074] Figure 6 This is a structural block diagram of a step frequency adjustment prompt device provided by an embodiment of the present application. Figure 6 As shown, specifically including the following: The target track complexity prediction module 601 is configured to obtain the heart rate data of the contestant, determine the temporal variation of the heart rate data if the heart rate value exceeds a preset threshold, and predict the target track complexity of the contestant's track based on the temporal variation of the heart rate data. The actual track complexity determination module 602 is used to map the acquired location information of the contestant to the track annotation map, and determine the actual track complexity of the contestant based on the mapping result; The cadence prompt module 603 is used to obtain the cadence data of the contestant when the target track complexity is consistent with the actual track complexity, and determine the contestant's cadence adjustment data based on the heart rate data, the actual track complexity and the cadence data to prompt the contestant.

[0075] Furthermore, the target track complexity prediction module 601 is specifically configured to: Determine the contestant's heart rate sudden change moment and heart rate sudden change value based on the change pattern, and determine the contestant's heart rate fluctuation ratio based on the heart rate sudden change value and the contestant's average heart rate before the heart rate sudden change moment; Match the average heart rate and the heart rate fluctuation ratio with the preset track complexity comparison table respectively, and determine the initial track complexity corresponding to the average heart rate and the track complexity fluctuation ratio corresponding to the heart rate fluctuation ratio based on the matching results; The target track complexity of the contestant's track is determined based on the initial track complexity and the track complexity fluctuation ratio.

[0076] Furthermore, the target track complexity prediction module 601 is specifically configured to: Obtaining the contestant's competition frequency and determining the heart rate sensitivity coefficient corresponding to the competition frequency; The heart rate fluctuation ratio is adjusted based on the heart rate sensitivity coefficient, and the track complexity fluctuation ratio corresponding to the adjustment result of the heart rate fluctuation ratio is determined according to a preset track complexity comparison table.

[0077] Furthermore, the actual track complexity determination module 602 is specifically configured to: Determine the target motion trajectory of the contestant at the moment of the sudden change in heart rate in the mapping results, as well as the slope type, slope level, track flatness, and number of turns within the trajectory range of the target motion trajectory; determining a first track complexity corresponding to a slope type and a slope level, a second track complexity corresponding to a track flatness, and a third track complexity corresponding to a number of turns; Calculate the weighted sum of the complexity of the first track, the complexity of the second track, and the complexity of the third track to obtain the actual track complexity of the contestant.

[0078] Furthermore, the actual track complexity determination module 602 is specifically configured to: Determining a first track complexity parameter corresponding to the slope level, identifying whether the slope type is downhill, and comparing the slope parameter with a preset impedance slope threshold; When the slope type is downhill and the slope parameter is less than the preset impedance slope threshold, the sign of the first track complexity parameter is determined to be negative, and the first track complexity corresponding to the slope type and slope level is determined according to the first track complexity parameter and the sign.

[0079] Furthermore, the cadence prompt module 603 is specifically configured to: Determine the competitor's baseline cadence data based on the cadence data before the heart rate mutation moment, and determine the first cadence influence coefficient corresponding to the baseline cadence data; Calculating the heart rate difference between the heart rate mutation value and the preset heart rate threshold, determining the heart rate deviation level corresponding to the heart rate difference, and the second step frequency influence coefficient corresponding to the heart rate deviation level; Determine the third cadence influence coefficient corresponding to the actual track complexity, determine the cadence adjustment requirement value based on the heart rate difference, the first step influence coefficient, the second cadence influence coefficient and the third cadence influence coefficient, and determine the contestant's cadence adjustment data based on the cadence adjustment requirement value and the baseline cadence data.

[0080] Furthermore, the cadence prompt module 603 is further configured to: Expand the complexity range of the actual track complexity according to the preset complexity floating scale to obtain the maximum actual track complexity and the minimum actual track complexity centered on the actual track complexity; The target track complexity is compared with the maximum actual track complexity and the minimum actual track complexity. When the target track complexity is less than or equal to the maximum actual track complexity and the target track complexity is greater than the minimum actual track complexity, it is determined that the target track complexity is consistent with the actual track complexity.

[0081] The technical solution provided in the embodiments of the present application includes a target track complexity prediction module for obtaining the heart rate data of a contestant, and when a heart rate value in the heart rate data is greater than a preset heart rate threshold, determining the change pattern of the heart rate data over time, and predicting the target track complexity of the contestant's track based on the change pattern; an actual track complexity determination module for mapping the obtained positioning information of the contestant to a track annotation map, and determining the actual track complexity of the contestant based on the mapping result; and a cadence prompt module for obtaining the cadence data of the contestant when the target track complexity is consistent with the actual track complexity, and determining the cadence adjustment data of the contestant based on the heart rate data, the actual track complexity and the cadence data, for prompting the contestant. The above-mentioned cadence adjustment prompt device solves the problem in the prior art of being unable to provide cadence adjustment prompts reasonably and accurately. By predicting the target track complexity of the track where the contestant is located based on the change pattern of heart rate data over time, when the target track complexity is consistent with the actual track complexity, the contestant's cadence adjustment data is determined based on the heart rate data, the actual track complexity and cadence data. This can achieve the purpose of providing cadence adjustment guidance in combination with the track complexity and determining the specific data for cadence adjustment, which is beneficial to improving the accuracy of cadence guidance and ensuring that the heart rate data is within the preset heart rate threshold range, which is beneficial to improving the sports safety of the contestants.

[0082] A cadence adjustment prompt device in an embodiment of the present application can be configured in a device, or in a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. The non-mobile electronic device can be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc., and the embodiments of the present application do not specifically limit this.

[0083] In the embodiment of the present application, a cadence adjustment prompting device may be an operating system, which may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0084] The cadence adjustment prompt device provided in the embodiment of the present application can implement the various processes implemented in the above-mentioned method embodiments. To avoid repetition, they will not be described here.

[0085] like Figure 7 As shown, an embodiment of the present application also provides an electronic device 700, including a processor 701, a memory 702, and a program or instruction stored in the memory 702 and executable on the processor 701. When the program or instruction is executed by the processor 701, each process of the above-mentioned step frequency adjustment prompt method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0086] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0087] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned embodiment of the step frequency adjustment prompt method are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0088] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk.

[0089] The present application also provides a program product comprising program code. When the program product is executed on a computer device, the program code is configured to cause the computer device to execute the steps of the methods described above in accordance with various exemplary embodiments of the present application. For example, the computer device may execute a cadence adjustment prompt method described in an embodiment of the present application. The program product may be implemented using any combination of one or more readable media.

[0090] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0091] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of this application, or the part that contributes to the existing technology, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of this application.

[0092] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

[0093] The above are only preferred embodiments of the present application and the technical principles employed. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that are possible for those skilled in the art will not depart from the scope of protection of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments and may include more other equivalent embodiments without departing from the concept of the present application. The scope of the present application is determined by the scope of the claims.

Claims

1. A method for prompting a cadence adjustment, applied to a background server, characterized in that: The method comprises: obtaining heart rate data of the contestant, and if a heart rate value in the heart rate data is greater than a preset heart rate threshold, determining a change pattern of the heart rate data over time, and predicting a target track complexity of the track on which the contestant is located based on the change pattern; Mapping the acquired location information of the contestant to a track annotated map, and determining the actual track complexity of the contestant based on the mapping result; When the target track complexity is consistent with the actual track complexity, the cadence data of the contestant is obtained, and the cadence adjustment data of the contestant is determined according to the heart rate data, the actual track complexity and the cadence data, so as to prompt the contestant.

2. The method for prompting cadence adjustment according to claim 1, wherein: The predicting of the target track complexity of the contestant's track based on the change rule includes: Determining the contestant's heart rate sudden change moment and heart rate sudden change value based on the change pattern, and determining the contestant's heart rate fluctuation ratio based on the heart rate sudden change value and the contestant's average heart rate before the heart rate sudden change moment; Matching the heart rate average value and the heart rate fluctuation ratio with a preset track complexity comparison table respectively, and determining an initial track complexity corresponding to the heart rate average value and a track complexity fluctuation ratio corresponding to the heart rate fluctuation ratio according to the matching results; The target track complexity of the track where the contestant is located is determined according to the initial track complexity and the track complexity fluctuation ratio.

3. The method for prompting cadence adjustment according to claim 2, wherein: Matching the heart rate fluctuation ratio with a preset track complexity comparison table includes: Obtaining a competition frequency of the contestant and determining a heart rate sensitivity coefficient corresponding to the competition frequency; The heart rate fluctuation ratio is adjusted based on the heart rate sensitivity coefficient, and a track complexity fluctuation ratio corresponding to the adjustment result of the heart rate fluctuation ratio is determined according to a preset track complexity comparison table.

4. The method for prompting cadence adjustment according to claim 2, wherein: Determining the actual track complexity of the contestant according to the mapping result includes: Determining the target motion trajectory of the contestant at the moment of the sudden change in heart rate in the mapping result, as well as the slope type, slope level, track flatness, and number of turns within the trajectory range of the target motion trajectory; determining a first track complexity corresponding to the slope type and the slope grade, a second track complexity corresponding to the track flatness, and a third track complexity corresponding to the number of turns; A weighted sum of the first track complexity, the second track complexity, and the third track complexity is calculated to obtain the actual track complexity of the contestant.

5. The method for prompting cadence adjustment according to claim 4, characterized in that: The determining of a first track complexity corresponding to the slope type and the slope level includes: determining a first track complexity parameter corresponding to the slope level, identifying whether the slope type is downhill, and comparing the slope parameter with a preset impedance slope threshold; When the slope type is downhill and the slope parameter is less than a preset impedance slope threshold, the sign of the first track complexity parameter is determined to be negative, and a first track complexity corresponding to the slope type and the slope level is determined based on the first track complexity parameter and the sign.

6. The method for prompting cadence adjustment according to claim 2, wherein: The determining of the contestant's cadence adjustment data based on the heart rate data, the actual track complexity, and the cadence data includes: Determining the baseline cadence data of the contestant based on the cadence data before the moment of the sudden change in heart rate, and determining a first cadence influence coefficient corresponding to the baseline cadence data; Calculating a heart rate difference between the heart rate mutation value and the preset heart rate threshold, determining a heart rate deviation level corresponding to the heart rate difference, and a second cadence influence coefficient corresponding to the heart rate deviation level; Determine a third cadence influence coefficient corresponding to the actual track complexity, determine a cadence adjustment requirement value based on the heart rate difference, the first step influence coefficient, the second cadence influence coefficient, and the third cadence influence coefficient, and determine the cadence adjustment data of the contestant based on the cadence adjustment requirement value and the baseline cadence data.

7. The method for prompting cadence adjustment according to claim 1, wherein: The process of performing consistency check on the target track complexity and the actual track complexity includes: Expanding the complexity range of the actual track complexity according to a preset complexity floating scale to obtain a maximum actual track complexity and a minimum actual track complexity centered on the actual track complexity; The target track complexity is compared with the maximum actual track complexity and the minimum actual track complexity respectively. If the target track complexity is less than or equal to the maximum actual track complexity and the target track complexity is greater than the minimum actual track complexity, it is determined that the target track complexity is consistent with the actual track complexity.

8. A cadence adjustment prompting device, characterized in that: The device comprises: a target track complexity prediction module, configured to obtain the heart rate data of a contestant, determine a temporal variation pattern of the heart rate data when a heart rate value in the heart rate data is greater than a preset heart rate threshold, and predict the target track complexity of the contestant's track based on the temporal variation pattern; an actual track complexity determination module, configured to map the acquired location information of the contestant to a track annotation map, and determine the actual track complexity of the contestant based on the mapping result; A cadence prompt module is used to obtain the cadence data of the contestant when the target track complexity is consistent with the actual track complexity, and determine the cadence adjustment data of the contestant based on the heart rate data, the actual track complexity and the cadence data, so as to prompt the contestant.

9. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and running on the processor. When the program or instruction is executed by the processor, the steps of the cadence adjustment prompt method as described in any one of claims 1 to 7 are implemented.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the cadence adjustment prompt method according to any one of claims 1 to 7 are implemented.

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