Bicycle pedaling roundness detection method, system and equipment

Abstract

The invention provides a bicycle pedaling roundness detection method, system and equipment, and the method comprises the steps: obtaining motion data in bicycle pedaling, and collecting the motion data through IMU equipment; based on the motion data, calculating a bicycle crank average angular velocity, a left foot stepping crank angular velocity average value and a right foot stepping crank angular velocity average value; calculating a whole-course pedaling technology smooth coefficient, a left pedaling technology smooth coefficient, a right pedaling technology smooth coefficient and a left-right pedaling balance index; based on the whole-course pedaling technology smoothness coefficient, the left pedaling technology smoothness coefficient, the right pedaling technology smoothness coefficient and the left and right pedaling balance index, the bicycle pedaling technology smoothness is judged. According to the scheme, the bicycle pedaling roundness is detected only through the data collected by the IMU equipment, the pedaling technology roundness can be accurately evaluated, and objective and effective data reference is provided for exercise training.

Description

Technical Field

[0001] The present invention relates to the fields of motion data detection, motion data processing and motion data application, and in particular to a method, system and device for detecting the smoothness of bicycle pedaling. Background Art

[0002] In the field of track cycling, the slight deformation of the technical movements during the sport will directly affect the athlete's athletic performance, and in the detection of athlete movements, the detection of the smoothness of the pedaling technique is one of the important items. Researchers studied the pedaling technique of track cycling athletes in the starting phase and found that athletes will have a "dead point" phenomenon during pedaling due to the influence of the limb joint structure. This phenomenon will cause the crank angular velocity to drop significantly. The study pointed out that the more uniform the angular velocity of the athlete's pedaling crank at each position, the better the athlete's pedaling technique. In summary, the smoothness of the pedaling technique is particularly important both in the process of sports training and in the analysis of the final results.

[0003] In the study of evaluating the pedaling technique of track cyclists, SRM equipment and video shooting and analysis methods are often used to detect and analyze the pedaling technique of athletes. In the field of pedaling technique smoothness evaluation research, most of the two-dimensional plane shooting methods are used to study the unilateral sagittal plane pedaling technique of athletes in the starting phase. It is difficult to accurately collect the data of the smoothness of the pedaling technique of athletes throughout the whole cycling process, and it is impossible to accurately evaluate the smoothness of the athletes' pedaling technique with quantitative indicators.

[0004] The smoothness of the pedaling technique of track cycling is a manifestation of the change in crank angular velocity. The smoothness of the athlete's pedaling technique also reflects the level of the athlete's pedaling technique. When athletes are doing field training cycling, accurately evaluating the smoothness of the athlete's pedaling technique is of great significance to the improvement of the athlete's pedaling technique. At present, researchers mainly use SRM equipment to accurately collect data that can reflect the pedaling technique, such as the cadence, power and speed of athletes riding throughout the field; and use two-dimensional plane video shooting and analysis technology to collect data such as the crank angular velocity, riding speed and body joint angle changes of athletes riding bicycles. However, this technology also has two obvious disadvantages. First, it can only collect the start-up riding stage parallel to the shooting screen, and second, when shooting athletes, it can only capture the data of the pedaling technique on one side. Summary of the invention

[0005] In response to the deficiencies in the prior art, the present application collects the changes in the angular velocity of the bicycle crank of track cyclists during the entire riding process, and uses the full-course pedaling technique smoothness coefficient, left-foot pedaling technique smoothness coefficient, right-foot pedaling technique smoothness coefficient and left-right pedaling balance index in the constructed detection model to comprehensively detect the smoothness of the pedaling technique of track cyclists during the entire riding process, to provide assistance for scientific training.

[0006] Specifically, the present invention provides the following technical solutions:

[0007] In one aspect, the present invention provides a method for detecting bicycle pedaling smoothness, the method comprising:

[0008] S1. Acquire motion data during bicycle pedaling, wherein the motion data includes: a real-time angular velocity of a bicycle crank, a real-time angular velocity of a left crank angle, and a real-time angular velocity of a right crank angle; the motion data is collected by an IMU device, and the IMU device also collects Euler angle data;

[0009] S2. Based on the motion data, calculate the average angular velocity of the bicycle crank, the average angular velocity of the left foot pedaling crank and the average angular velocity of the right foot pedaling crank, and count the total number of bicycle crank angular velocity data N and the total number of real-time crank angular velocity data N of the left foot pedaling bicycle L The total amount of real-time crank angular velocity data N of the right foot pedaling the bicycle R ;

[0010] S3, calculating the smoothness coefficient of the whole pedaling technique based on the coefficient of variation of the bicycle crank angular velocity; calculating the smoothness coefficient of the left pedaling technique based on the coefficient of variation of the left foot pedaling crank angular velocity; calculating the smoothness coefficient of the right pedaling technique based on the coefficient of variation of the right foot pedaling crank angular velocity; calculating the left and right pedaling balance indexes based on the left and right pedaling technique smoothness coefficients;

[0011] S4. The smoothness of bicycle pedaling technique is evaluated based on the smoothness coefficient of the whole pedaling technique, the smoothness coefficient of the left foot pedaling technique, the smoothness coefficient of the right foot pedaling technique and the left and right pedaling balance index.

[0012] Preferably, in S3, the rounding coefficient FRC of the whole pedaling technique is calculated as follows:

[0013]

[0014]

[0015] Among them, X i represents the real-time angular velocity of the ith crank collected, is the average angular velocity of the crank.

[0016] Preferably, in S3, the left foot pedaling technique smoothness coefficient LFC is calculated as follows:

[0017]

[0018]

[0019] in, represents the real-time angular velocity of the i-th left crank angle collected, It represents the mean angular velocity of the left foot pedaling the crank.

[0020] Preferably, in S3, the right foot pedaling technique smoothness coefficient RFC is calculated as follows:

[0021]

[0022]

[0023] in, represents the real-time angular velocity of the i-th right crank angle collected, Represents the mean angular velocity of the right foot pedaling the bicycle crank.

[0024] Preferably, in S3, the left and right pedaling balance index PBI is calculated as follows:

[0025] PBI=LFC--RFC

[0026] Among them, LFC represents the smoothness coefficient of left foot pedaling technique, and RFC represents the smoothness coefficient of left foot pedaling technique.

[0027] Preferably, in S4, the smoothness of bicycle pedaling technique is judged as follows:

[0028] The closer the absolute value of the left and right pedaling balance index is to 0, the higher the similarity of the left and right pedaling techniques is, and the smoother the bicycle pedaling technique is;

[0029] The smaller the smoothness coefficient of the whole pedaling technique, the smoother the bicycle pedaling technique;

[0030] The smaller the smoothness coefficient of the left foot pedaling technique, the smoother the bicycle pedaling technique;

[0031] The smaller the smoothness coefficient of the right foot pedaling technique, the smoother the bicycle pedaling technique.

[0032] Preferably, in S1, the IMU device is fixed on the inner side of the bicycle crank and parallel to the bicycle crank, the lateral long axis of the IMU device is parallel to the long axis of the bicycle crank, and the Z axis of the IMU device is perpendicular to the inner surface of the bicycle crank.

[0033] Preferably, the S2 further includes:

[0034] Calculate real-time pedaling frequency CAD:

[0035]

[0036]

[0037]

[0038] Among them, k represents the acquisition frequency of the IMU device, in Hertz (Hz); dθ represents the real-time angle change of the bicycle crank, in degree (°); t represents the riding time, θ represents the bicycle crank angle; dt represents the time taken by the IMU device to collect data each time, in seconds (s); ω is the angular velocity of the crank, in radians per second (rad / s).

[0039] Preferably, the S2 further includes:

[0040] Calculate the real-time riding speed v:

[0041]

[0042]

[0043]

[0044] Among them, k represents the acquisition frequency of the IMU device, in Hertz (Hz); dθ represents the real-time angle change of the bicycle crank, in degree (°); t represents the riding time, θ represents the bicycle crank angle, C represents the circumference of the bicycle wheel, and G represents the fixed gear ratio of the bicycle; dt represents the time taken by the IMU device to collect data each time, in seconds (s); ω is the angular velocity of the crank rotation, in radians per second (rad / s).

[0045] Preferably, the S1 further comprises: filtering and denoising the motion data.

[0046] Preferably, in S2, the method for calculating the average angular velocity of the bicycle crank, the average angular velocity of the left foot pedaling the crank and the average angular velocity of the right foot pedaling the crank is: taking the frames before the complete seconds recorded by the IMU device as advance frames, averaging the data corresponding to the advance frames, and then averaging the data corresponding to the frames within the complete seconds recorded by the IMU device; then averaging the average value of the advance frame data and the average value of the data within the complete seconds, and performing the final average calculation.

[0047] Preferably, S1 also includes segmenting the left and right foot pedaling data of the motion data collected by the IMU device to obtain the real-time angular velocity of the left crank angle of the bicycle and the real-time angular velocity of the right crank angle of the bicycle. The specific method is: subtracting the two adjacent Euler angles collected by the IMU device, if the difference is greater than 0, it is determined to be an ascending posture, if the difference is less than 0, it is determined to be a descending posture; and then combining with the fixed position of the IMU device, the motion data is divided into the left foot and the right foot, so as to obtain the corresponding real-time angular velocity of the left crank angle and the real-time angular velocity of the right crank angle of the bicycle.

[0048] Preferably, the IMU device can be replaced by an SRM device.

[0049] On the other hand, the present invention also provides a bicycle pedaling smoothness detection system, the system comprising:

[0050] Multiple training timing modules (i.e. electronic timing systems) to record the time during riding;

[0051] An IMU device is used to collect motion data, wherein the motion data includes: a real-time angular velocity of a bicycle crank, a real-time angular velocity of a left crank angle of a bicycle, and a real-time angular velocity of a right crank angle of a bicycle;

[0052] A camera module for acquiring motion images during riding;

[0053] Display, used to display time and test data information;

[0054] A data processing module is used to calculate the smoothness coefficient of the whole pedaling technique, the smoothness coefficient of the left foot pedaling technique, the smoothness coefficient of the right foot pedaling technique and the left and right pedaling balance index;

[0055] The system is used to execute the bicycle pedaling smoothness detection method as described above.

[0056] In another aspect, the present invention further provides a bicycle pedaling smoothness detection device, the device comprising a timing device, an IMU device, a processor and a memory;

[0057] The timing device and the IMU device send the collected data to the processor;

[0058] The processor calls the computer instructions in the memory to execute the bicycle pedaling smoothness detection method as described above.

[0059] Compared with the existing technology, this solution can detect the smoothness of bicycle pedaling only through the data collected by the IMU device, and the data collected by the solution can accurately reflect the objective posture during riding, and can accurately evaluate the smoothness of pedaling technology, providing objective and effective data reference for sports training; the multi-data fusion processing of the high-precision and high-collection frequency IMU device ensures the accuracy of the calculation of pedaling smoothness; this system only needs to fix an IMU device on one side of the crank of the bicycle, which has the advantages of portability, easy operation and easy installation; the rapid calculation of pedaling smoothness can enable the rider to timely understand the characteristics of his pedaling technology during riding, which is conducive to the improvement of riding technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 Schematic diagram of the experimental verification process of an embodiment of the present invention;

[0062] Figure 2 A schematic diagram of a reference coordinate system in which an IMU according to an embodiment of the present invention is fixed on a bicycle crank;

[0063] Figure 3 A schematic diagram of a model verification site experiment plan of an embodiment of the present invention;

[0064] Figure 4 A schematic diagram of a floor plan of an application verification experiment site of an embodiment of the present invention;

[0065] Figure 5 It is a schematic diagram of the effects before and after filtering of the angular velocity of the gyroscope Z axis according to an embodiment of the present invention;

[0066] Figure 6 A schematic diagram of the variation range of the Euler angle when the IMU according to an embodiment of the present invention is fixed on the crank;

[0067] Figure 7 A partial comparison diagram of the Z-axis angular velocity and Y-axis Euler angle variation of the IMU gyroscope according to an embodiment of the present invention;

[0068] Figure 8 This is a schematic diagram of an embodiment of the present invention after the IMU collects data within 1 second and performs left and right foot segmentation;

[0069] Fig. 9 This is a flow chart of a pedaling smoothness detection method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. It should be clear that the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0071] Those skilled in the art should know that the following specific embodiments or specific implementations are a series of optimized settings listed by the present invention to further explain the specific content of the invention, and these settings can be combined or used in association with each other, unless the present invention clearly states that some or a specific embodiment or implementation cannot be associated or used together with other embodiments or implementations. At the same time, the following specific embodiments or implementations are only used as the most optimized settings, and are not to be understood as limiting the scope of protection of the present invention.

[0072] The smoothness of pedaling technique can well reflect the smoothness of the athlete's pedaling technique during the entire cycling cycle of pedaling the bicycle crank, and is evaluated based on the coefficient of variation of the bicycle crank angular velocity change during the cycling cycle. This scheme collects the changes in the bicycle crank angular velocity of track cycling athletes during the entire cycling process, and uses the full-cycle pedaling technique smoothness coefficient, left-foot pedaling technique smoothness coefficient, right-foot pedaling technique smoothness coefficient and left-right pedaling balance index in the constructed detection model to comprehensively detect the smoothness of the pedaling technique of track cycling athletes during the entire cycling process.

[0073] In this embodiment, the coefficient of variation is set as the ratio of the standard deviation of a set of data to its mean, which is used to measure the relative discreteness of the measured data and is suitable for comparison between multiple sets of data. The use of the coefficient of variation can accurately evaluate the change in the crank angular velocity of the bicycle, and can solve the influence of the average on the evaluation results when using indicators such as variance and standard deviation. In this embodiment, the coefficient of variation is used as a basic detection method for evaluating the smoothness of the pedaling technique of field bicycles. In a preferred method, combined with the characteristics of bicycle pedaling, we set the following indicators:

[0074] (1) Smoothness coefficient of pedaling technique throughout the entire process

[0075] The Full Range Coefficient (FRC) is used to reflect the smoothness of the pedaling technique of track cyclists at the start and end of track cycling. FRC is the coefficient of variation of the change in the crank angular velocity of the bicycle during the pedaling cycle, and the calculation formula is as follows:

[0076] The standard deviation of the crank angular velocity of the bicycle during the whole pedaling process is:

[0077]

[0078] Where N represents the total number of bicycle crank angular velocity data collected by the IMU in a single ride; X i Indicates the real-time angular velocity of the bicycle crank collected by the sensor, in rad / s; It represents the average angular velocity of the crank during the riding cycle, in rad / s.

[0079] In this embodiment, as a preferred implementation, the above-mentioned real-time angular velocity of the crank refers to the real-time angular velocity of the crank collected throughout the whole process, that is, all angular velocities collected by the IMU from the beginning to the end of riding, the left crank angular velocity is all angular velocity data of the left foot pedaling selected from the crank angular velocity data of the whole process, and the remaining data are all angular velocity data of the right foot pedaling, or all angular velocity data of the right foot pedaling can be first selected from the real-time angular velocity data of the crank throughout the whole process, then the remaining data are all angular velocity data of the left foot pedaling. In this case, in fact, the IMU only needs to collect the real-time angular velocity of the crank, and then the real-time angular velocity data of the left and right feet pedaling can be distinguished based on the difference in data such as the angle of the left and right feet pedaling, such as the method in this embodiment, so as to perform subsequent calculations. It should be made clear here that there may be multiple methods for distinguishing or screening the real-time angular velocity data of the left and right foot pedaling. In addition to the method in this embodiment, they can also be distinguished by, for example, adding multiple sets of IMU equipment or screening or calculating by angle tilt conditions, etc. This embodiment is only used as the optimal implementation method, and should not be understood as the optimal method is an indispensable limitation of the present invention, nor should it be understood as the only way to achieve the distinction or screening of the real-time angular velocity values ​​of the left and right feet. Those skilled in the art can perform corresponding calculations based on other methods in the prior art.

[0080] In this embodiment, preferably, placing the IMU sensor on the left crank can not only collect the angular velocity data of the left crank, but also collect the angular velocity data of the right crank, because the crank is symmetrically opposite to the left crank by 180 degrees and is a metal rigid body. When riding, the crank performs circular motion. At this time, the left leg does not exert force entirely on the left leg during the pedaling cycle, but also on the right leg. In this embodiment, the sensor records the rising stage of the Euler angle data as the right foot pedaling stage, and the falling stage of the Euler angle data as the left foot pedaling stage, that is, the IMU is installed on the left crank. Of course, when the IMU is installed on the right crank, the rising stage of the Euler angle data recorded at this time can be judged as the left foot pedaling stage, and the falling stage of the Euler angle data is the right foot pedaling stage; the specific splitting of the left and right foot data will be described in detail later in conjunction with this embodiment.

[0081] Full pedaling technology smoothness coefficient FRC:

[0082]

[0083] The judging criteria for the smoothness coefficient FRC of the whole pedaling technique are as follows: the smaller the coefficient result, the smaller the speed dispersion of the bicycle crank angle during the whole pedaling process, which means that the athlete's pedaling crank speed fluctuation is small during the whole cycling pedaling cycle, and the pedaling technique is stable. This indicator is crucial for the athlete's ability to maintain a high speed. The smaller the FRC, the smoother the athlete's pedaling technique is. This coefficient also represents the pedaling technique level of the athlete during the cycling process. This standard can be used as a reference for discovering the pedaling technique of excellent athletes.

[0084] (2) Smoothness coefficient of left and right pedaling technique

[0085] In this embodiment, the left foot pedaling technique smoothness coefficient (Left Foot Coefficient, LFC) and the right foot pedaling technique smoothness coefficient (Right Foot Coefficient, RFC) are based on the full pedaling technique smoothness coefficient, and the angular velocities of the athlete's left foot and right foot pedaling the bicycle crank during the cycling process are distinguished and compared and analyzed one by one. Therefore, LFC and RFC respectively represent the advantages and disadvantages of the athlete's left foot and right foot pedaling techniques during the full pedaling cycle of cycling training. The LFC and RFC indicators can be used to analyze the technical characteristics of the left and right feet during the cycling pedaling process, and the difference in the left and right foot pedaling techniques can be comprehensively analyzed. The calculation formula is as follows:

[0086] The total number of crank angular velocity data collected by the IMU (Inertial Measurement Unit) during the riding cycle is N:

[0087] N=N L +N R (3)

[0088] Where N L is the total number of real-time crank angular velocity data collected by the IMU during the riding cycle when the left foot pedals the bicycle, N R It is the total number of real-time crank angular velocity data of the right foot pedaling the bicycle collected by the IMU during the riding cycle.

[0089] Standard deviation of left foot pedal crank angular velocity σ L :

[0090]

[0091] In the formula, Indicates the real-time angular velocity of the left crank angle collected by the IMU device (in rad / s). It represents the mean angular velocity of the left foot pedaling the crank (in rad / s).

[0092] Left foot pedaling technique smoothness coefficient LFC:

[0093]

[0094] Standard deviation of right foot pedal crank angular velocity σ R :

[0095]

[0096] In the formula, It represents the real-time angular velocity of the right crank angle collected by the IMU (in rad / s). It represents the mean angular velocity of the right foot pedaling the bicycle crank (in rad / s).

[0097] Right foot pedaling technology smoothness coefficient RFC:

[0098]

[0099] The evaluation criteria of LFC and RFC in formulas (5) and (7) are consistent with the evaluation criteria of FRC, that is, the smaller the coefficient, the smoother the pedaling technique in this cycling cycle.

[0100] (3) Pedaling balance index

[0101] In this embodiment, the pedaling balance index (PBI) is obtained by subtracting the pedaling smoothness coefficients of the left and right feet based on the coefficient of variation of the bicycle crank angular velocity during the pedaling cycle of the left and right feet. The preferred calculation method is as follows:

[0102] Pedaling Balance Index (PBI):

[0103] PBI=LFC-RFC (8)

[0104] The judging criteria of the left and right pedaling balance index PBI are as follows: the closer the absolute value of PBI is to 0, the higher the similarity of the left / right foot pedaling technique is, which also represents the high coordination and stability of the left and right feet of the athlete during riding; if the absolute value of PBI is larger, it means that the crank angular velocity fluctuations on the left and right sides of the bicycle are larger, which indirectly reflects that the smoothness and coordination of the pedaling technique of the left and right feet of the athlete are poor, and further analysis is needed. Based on the above formula (8), in this embodiment, if PBI>0, it reflects that the crank angular velocity fluctuations on the left side of the bicycle are larger than those on the right side, indicating that the athlete's left foot pedaling technique is not as good as the right foot; if PBI<0, it reflects that the crank angular velocity fluctuations on the right side of the bicycle are larger than those on the left side, indicating that the athlete's right foot pedaling technique is not as good as the left foot, and the left foot pedaling technique is more stable than the right foot. It should be noted here that the calculation method of the pedaling balance index PBI proposed in this embodiment is a preferred calculation method. Those skilled in the art can use other mathematical methods to define or calculate PBI based on the calculation of LFC and RFC in the present invention, such as by calculating the weighted relationship between LFC and RFC, calculating by the difference between the two, etc. Such methods should be regarded as falling within the protection scope of the present invention, and the above-mentioned method for calculating PBI should not be regarded as the only method for calculating PBI proposed by the present invention.

[0105] Based on the calculation method of the key detection indicators given above, the detection process is described in detail below. Figure 1 , Fig. 9 As shown, a track bicycle pedaling experiment is taken as an example. When collecting experimental data, in this embodiment, a data collection system is first constructed.

[0106] 1. Data Acquisition System Construction

[0107] In this embodiment, the system mainly includes the following modules:

[0108] (1) Training timing module (also called electronic timing system), in this embodiment, the timing accuracy of the training timing module used is 1ms, which is used to record the time in the test. The training timing module is generally set to multiple, and in this embodiment, for example, it is set to 7.

[0109] (2) SRM module. In this embodiment, the SRM device can be, for example, the 9th generation bicycle sports performance measurement device commonly used in the prior art. The SRM module is used for experimental data comparison and for verifying that the solution of the present invention can also collect basic data through the SRM device.

[0110] (3) Inertial measurement module, i.e., IMU module (or IMU device). In this embodiment, a nine-axis inertial sensor may be used. For example, its maximum acquisition frequency is 120 Hz, and the accumulated drift of the gyroscope is 10° / h.

[0111] (4) Camera module, used to obtain the moving images under test.

[0112] (5) Display, used to display test data, time data, etc.

[0113] In addition, a test vehicle is included, which is ridden by the test athlete. When the test is performed, the flywheel of the bicycle is locked and the gear ratio is not changed during the test.

[0114] In the present embodiment, it is preferred that the SRM and IMU modules can be selectively installed. In the present embodiment, we verify the accuracy of each model index in the test method proposed in the present scheme by respectively setting two devices, namely the SRM and the IMU, and also verify the reliability of the pedaling smoothness detection by only combining the IMU module and the test model index proposed in the present scheme by only setting the IMU module. Therefore, it can be understood that in actual detection applications, the data acquisition system can only install and use the IMU module, or can also set the IMU and SRM modules at the same time, or only set the SRM module to detect the pedaling smoothness, and such adjustments should be deemed to fall within the scope of protection of the present application.

[0115] 2. Installation and calibration of system equipment

[0116] In this embodiment, the SRM module and the IMU module are installed at the same time as an example, so as to verify the reliability of the model of this solution through experimental data. For the above-mentioned system equipment modules, the system equipment is preferentially adjusted and debugged appropriately.

[0117] (1) Install and debug SRM and IMU equipment

[0118] In this embodiment, it is preferred to install the SRM power meter on the experimental bicycle, use the GARMIN code table to configure the data acquisition mode and calibrate the SRM device. Because the IMU device can collect changes in data such as various attitude angles and accelerations in space, it is preferred in this embodiment to fix the IMU device on the inner side of the crank on the toothless side and fix it parallel to the crank (of course, the installation position can also be set on the crank on the toothed side, which can be adjusted based on the specific bicycle structure and experimental tests). The installation position requires that the lateral long axis of the IMU device is parallel to the long axis of the crank, the Z axis is perpendicular to the inner surface of the crank, and it is fixed as close to the center point of the pedal as possible. In the application verification experiment, only the IMU device needs to be installed, and it is preferred to fix the IMU device on the inner side of the crank on the toothless side and fix it parallel to the crank. The application verification experiment is mainly used to verify the reliability of the detection model proposed in this scheme in actual application tests when only the IMU device is used.

[0119] (2) IMU reference coordinate system calibration and initial orientation calibration

[0120] The X-axis of the IMU reference coordinate system is along the long side of the sensor, the Y-axis is along the short side of the sensor, and the Z-axis is the positive vertical direction of the sensor. On the other hand, the spin Euler angle and free acceleration of the sensor are relative to the earth reference system, and the earth reference system is defined as: the X-axis points to the east, the Y-axis points to the north, and the Z-axis is vertically upward. In this embodiment, the initial direction calibration of the IMU device is performed according to the above coordinate system.

[0121] Based on the coordinate system and installation position of the IMU device in this embodiment, Figure 2 As shown in the figure, it can be seen that the direction coordinate axis of the IMU based on its own coordinate system has changed in space, and the Z axis that originally pointed vertically to the sky has been converted to be consistent with the Y axis direction of the bicycle crank's earth coordinate system. Therefore, when observing the movement of the IMU in the experiment and analyzing the experimental data, the changes in data such as the Euler angle of the Y axis based on the earth coordinate system as the standard reference system and the changes in data such as the Z axis attitude angle based on the own coordinate system as the standard reference system are mainly observed.

[0122] 3. Data Collection

[0123] Combination Figure 1 ,In this embodiment, we first verify the reliability of the model proposed in this ,scheme, and then verify the reliability in actual use through the ,application verification phase using only the IMU device. Therefore, we divide the data ,collection into two stages, namely the data collection in the ,model verification process and the data collection in the ,application verification process.

[0124] Of course, it should be understood that in the actual use of this solution, only the IMU device can be installed to detect the pedaling smoothness (such as the preferred real-time method of the present invention). The following describes the two phases of the experiment respectively.

[0125] (1) Data collection during model verification

[0126] In this embodiment, taking a series of track cycling experiments with specific settings as an example, it should be understood that the riding duration, number of laps, distance, personnel, etc. set in the experiment can all be adjusted and should not be regarded as limiting the scope of protection of the present invention.

[0127] In the model verification experiment, four 125m middle-distance cycling experiments and four 250m long-distance cycling experiments were conducted. The experimenters were two male short-distance track cyclists.

[0128] Experiment naming rules: The four middle-distance cycling experiments are named 125m-01 to 125m-04; the four long-distance cycling experiments are named 250m-01 to 250m-04. The experimental site can be a regular on-site cycling site. Figure 3 As shown, two fixed cameras are respectively set in the middle of the long edge of the track, and multiple electronic timing systems (i.e., training timing modules, which have the same meaning in this embodiment) can be evenly set on the inner edge of the track. In this embodiment, the training timing modules are set to 7, recorded as M1, M2, ..., M7. Preferably, the fixed camera position can be used as the timing point. Experimental equipment parameter setting: the front and rear gear ratio of the experimental bicycle is 52:13, and the circumference of the rear wheel is 2.105m; the shooting frame rate of the first fixed camera is 240hz, and the shooting frequency of the second fixed camera is 240hz; the refresh rate of the display is 60hz; the acquisition frequency of the IMU is set to 120hz; the acquisition frequency of the SRM module is 1hz. The experiment is expected to obtain 8 segments of IMU experimental data and 8 segments of SRM experimental data. The two fixed cameras shoot a total of 8 segments of video, and the electronic timing system records 8 groups of experimental time.

[0129] Experimental equipment installation and debugging and data recording methods. Before starting the experiment, arrange and debug the experimental site and experimental equipment, and configure the timing rules of the electronic timing system in advance. In the experiment, the track marking distance between the M1-M3 timing points is 125m, and the standard measurement distance of one lap of the field track is 250m. Experimental exercise plan: The 125m cycling experiment starts with the M1 timing point. M1 can be set at one of the fixed camera positions to Figure 3 The M3 timing point in the test is the end point; the 250m cycling test is based on Figure 3The M1 timing point in the experiment is used as the starting and ending point; the riding direction is counterclockwise, and the starting position of a single ride is fixed. The experimental riding route and direction are referenced Figure 3 The dashed line with an arrow in the .

[0130] Model validation experiments are performed as needed. Figure 3 The cameras at the M1 and M3 timing points are arranged at the first fixed position (1) and the second fixed position (2) respectively. The camera image must be parallel to the track, and ensure that the camera image is kept horizontal and contains the Beijing time display screen. The criterion for determining the start time of the experiment is the Beijing time display screen time (i.e. the display time) at the moment when the front wheel of the experimental vehicle touches the starting timing point. The experimental time uses the time recorded by the electronic timing system; the experimental distance uses the distance between the venue timing points. The SRM equipment, IMU and two fixed-position cameras are turned on 1 minute before the experiment and record the entire process of the experiment without interruption until the end of the entire experiment.

[0131] (2) Data collection during application verification

[0132] In the application verification experiment, the experiment planned to conduct two short-distance 42.5m sprint cycling experiments and two long-distance 250m sprint cycling experiments. The experimenters selected women's short-distance track cycling A athletes from Jiangsu Province, and the experimental cycling content was to simulate the high-intensity steep slope sprint cycling in the competition.

[0133] Application verification experiment naming rules: two 42.5m short-distance cycling experiments are named 42.5m-01 and 42.5m-02; two 250m long-distance cycling experiments are named 250m-01 and 250m-02.

[0134] The application verification experiment does not disrupt the normal training schedule of the athletes. The training involves two athletes, A and B, to conduct cooperative training. The experimental exercise program (specific training plan formulated by the coach) has a total of 4 groups. In the first group of training, athlete A performs a 250m sprint training. The training cycling route diagram is shown in Figure 4 The dotted line with the middle arrow indicates that athlete B was the leader in the first 42.5 m of the cycling training, and athlete A followed athlete B; in the second group of training, athlete B performed a 250 m sprint training, and athlete A was the leader in the first 42.5 m of the cycling training, and athlete B followed athlete A; the third group of training was the same as the first group; the fourth group of training was the same as the second group.

[0135] Experimental equipment parameter setting and recording. The front and rear gear ratio of the bicycle ridden by the athlete is 50:13, and the circumference of the rear wheel is 2.09m; the shooting frame rate of the first fixed camera (1) is 240hz; the refresh rate of the Beijing time display is 60hz; the IMU acquisition frequency is 120hz offline acquisition. It is expected to obtain 4 segments of IMU experimental data, 4 segments of fixed camera shooting videos, and 4 sets of athlete training results recorded by the electronic timing system.

[0136] Data collection implementation process. The timing rules of the electronic timing system are configured according to the coach's training plan. In this embodiment, at the timing starting point ( Figure 4 The M4 timing point in the figure is shot with a fixed camera. The experimental equipment on site is arranged as follows: Figure 4 . Figure 4 In the embodiment, multiple experimental timing modules are still set. In this embodiment, 7 modules are set, which are recorded as M1, M2, ..., M7.

[0137] According to the training requirements, the electronic timing rules are configured in combination with the timing points of the electronic timing system. Figure 4 In the figure, the timing point at M4 is the starting and ending timing point of the 250m sprint cycling experiment; the timing point at M4 is also the starting timing point of the 42.5m sprint cycling experiment, and the end point of the 42.5m cycling experiment is at the timing point at M2. Figure 4 The distance between the M4-M2 timing points is 42.5m. In this experiment, the training results are recorded by the electronic timing system; the training prescribed distance is measured by the standard track distance between the venue timing points.

[0138] 4. Experimental Data Processing

[0139] (1) Data segmentation

[0140] Before data segmentation, the start time of a single experiment needs to be calibrated. In all experiments in this embodiment, the video captured by the fixed-position camera is used as the standard. The start time of the experiment is based on the time in the camera display, and the criterion for determining the start time of the experiment is the instant when the front wheel of the experimental vehicle presses on the electronic timing sensor. The time at the start of the experiment plus the time recorded by the electronic timing system is used to obtain the time at the end of the experiment, and the data in this interval from the start to the end of the experiment is used as the data of the experimental interval. In the experiment of this embodiment, the experimental data collected by the SRM, IMU and camera are all segmented using this method.

[0141] 1) SRM data segmentation

[0142] Export the speed and cadence data recorded by SRM (for example, in fit format) on the computer, convert the fit format file into a csv format file, and after opening the csv file, display Beijing time, speed, power, cadence, etc. from left to right.

[0143] According to the experimental time calibration principle, the corresponding experimental data collected by the SRM power meter are segmented. Since the acquisition frequency of SRM is 1HZ and the refresh rate of the Beijing time display is 60HZ, when selecting the experimental data interval, the seconds displayed in Beijing time are used as a reference to minimize the error. For example, the time when the experiment starts is 17:14:00:205, and the time when it ends is 17:14:10:805, the corresponding experimental interval of the SRM data is 17:14:01-17:14:11, that is, we can round the seconds forward.

[0144] 2) IMU data segmentation

[0145] a. Calibrate integer time lines

[0146] After exporting the experimental data in csV file format collected by IMU, the collected experimental data are displayed from left to right as follows: data packet counter, IMU internal timestamp, XYZ three-axis space Euler angle, XYZ three-axis free acceleration, XYZ three-axis gyroscope and XYZ three-axis magnetometer. In this embodiment, this data set focuses on the changes in the timestamp column inside the sensor, which is convenient for intercepting the data segments collected during the corresponding experiment.

[0147] When the IMU starts collecting data, it will create a data packet named with Beijing time. The file name of the data packet is accurate to the second. The first line in the data packet is a frame of data within that second (each frame is a line), so the integer time line at the start of the experiment can be determined by observing the data changes in the internal timestamp column. For example, if the h of a certain bit in the e-th line of the IMU timestamp column changes to h+1, and the e+120 line changes to h+2, set the e line (frame) to the 0 millisecond integer timestamp of the next second of the file package naming time.

[0148] b. Processing method for calibration experiment start and end time

[0149] Use the time calibration tool to calibrate the data set collected by the IMU. Use the time at the start of the experiment to calibrate the integer time. Keep the millisecond time difference first, convert the subtracted time to integer seconds, multiply the integer seconds by 120 to calculate the total number of rows of data recorded by the IMU during this time, and then convert the millisecond difference left by the subtraction into the number of rows (i.e., number of frames) of specific IMU collected data. This method is also applied to the time calibration at the end of the experiment. First, calibrate the number of rows in the data set corresponding to the Beijing time at the end of the experiment. The data set within the range of the number of rows at the start of the experiment and the number of rows at the end of the experiment is used as the data collected by the IMU during the experiment. Because the refresh rate of the display screen in Beijing time is 60hz and the IMU acquisition frequency is 120hz, the cumulative error of the time at the start and end of the experiment calibration is within 1 / 30 second.

[0150] (2) Principles and methods of IMU data collection and processing

[0151] 1) Noun naming

[0152] To facilitate data processing, the terms that the IMU needs to process data in this embodiment are all named with fixed indicators. The following are the professional terms that need to be used in IMU data processing.

[0153] IMU acquisition frequency k (Hz); bicycle crank real-time angle change dθ (rad / s), bicycle crank real-time angle change time dt (K); real-time space Y-axis Euler angle (rad / s); circumference of the experimental bicycle wheel C (m); riding time t (s) obtained by the electronic timing system; fixed gear ratio G of the experimental vehicle.

[0154] 2) IMU collects track cycling kinematic data calculation

[0155] a. Real-time pedaling frequency during riding

[0156] Real-time pedaling frequency CAD (rpm) indicates the speed of the athlete pedaling the bicycle crank. As one of the indicators that track cycling athletes and coaches are highly concerned about during training, by combining pedaling frequency with other evaluation indicators, it can assist coaches in evaluating and analyzing the quality of athletes' single training. The specific calculation formula is as follows:

[0157] The IMU device collects the real-time angular velocity ω of the bicycle crank:

[0158]

[0159] Cycling real-time pedaling frequency CAD:

[0160]

[0161] Among them, k represents the IMU acquisition frequency, t represents the riding time, θ represents the bicycle crank angle; dθ represents the real-time angle change of the bicycle crank rotation, in degrees (°); dt represents the time taken by the IMU to collect data each time, in seconds (s); ω is the angular velocity of the crank rotation, in radians per second (rad / s).

[0162] b. Real-time riding speed

[0163] The real-time cycling speed v (m / s) indicates the speed of the athlete during cycling, which is related to pedaling frequency, cycling technique, wheel circumference and transmission ratio. Due to the particularity of track cycling, the wheel circumference and transmission ratio remain fixed during cycling, and the cycling speed can be calculated by the pedaling frequency. The specific calculation formula is as follows. The real-time cycling speed v is:

[0164]

[0165] 3) IMU data filtering and denoising

[0166] In this embodiment, the processing of the IMU raw data also includes filtering. A Butterworth filter can be used in the filtering, and the filter cutoff frequency is set to 15 and the filter order is set to 5. The gyroscope and acceleration data are filtered. The schematic diagram of the effect before and after filtering is shown in FIG. Figure 5 .

[0167] like Figure 3 As shown in the figure, the data of the bicycle crank rotation angular velocity for 1 second (a total of 120 data) collected in a certain experiment are intercepted and filtered. Figure 5 It can be found that after the original angular velocity is filtered, the burrs and outliers in the original angular velocity are obviously removed, and the angular velocity curve after filtering is smoother, which is conducive to angular velocity observation and subsequent calculation.

[0168] 4) Calculate average angular velocity using IMU data

[0169] In this embodiment, the IMU acquisition frequency is set to 120HZ. In order to facilitate the comparative analysis with the motion data recorded by the SRM, the angular velocity collected by the IMU within one second (120 frames) is averaged once, and the calculation is gradually accumulated. The data recorded by the IMU is averaged. If the initial data collected by the IMU is averaged once every 120 frames, there will be errors. In order to reduce the error, the value of the advance frame is introduced here. This value is the number of frames before the full seconds recorded by the IMU. For example, the experimental time calibration IMU start time is 18:01:58:314. It needs to record 686ms of data from 18:01:59:000. Then 686ms is converted into the number of frames, which is the advance frame. The data processing first averages the advance frame, and the data after the advance frame is averaged every 120 frames, trying to ensure that the averaged data records the data collected within an integer second of Beijing time, in order to keep consistent with the data time recorded by the SRM device. In this study, the IMU acquisition data compared with the SRM device is all the averaged data.

[0170] It should be pointed out here that the data collected by the IMU is averaged in this step in this embodiment because it is necessary to make a comparative analysis with the SRM device. The acquisition frequency of the SRM device is only 1Hz, and the acquisition frequency of the IMU used in this embodiment is 120Hz. In order to facilitate the comparative analysis of the data of the two devices, the data collected by the IMU in this embodiment using the 120hz acquisition frequency is averaged once per second (120 items) to facilitate subsequent comparative analysis, etc. Of course, in the specific motion data detection and evaluation process, the average data can also be calculated to facilitate the calculation and analysis of the index data.

[0171] 5) IMU segmentation and calculation of left and right foot pedaling data

[0172] The IMU is fixed on the left crank of the bicycle, and the changes in the rotation of the bicycle crank can be obtained. According to the calibration of the internal coordinate system of the sensor, refer to Figure 6 In this embodiment, the bicycle crank changes from -90° to 90° as the rising posture, and changes from 90° to -90° as the descending posture. This state is the ideal state in which the bicycle crank is perpendicular to the earth coordinate system. Figure 7 and according to Figure 8The defined Y-axis Euler angle change can clearly show the change in the angular velocity of the bicycle crank corresponding to the rising and falling stages of the Y-axis Euler angle, and the angular velocity data is divided accordingly. When the left foot pedals, the left crank descends, the IMU records the Euler angle decline, and the pedaling data is a descending posture; when the right foot pedals, the left crank rises, the IMU records the Euler angle rise, and the pedaling data is an ascending posture. In this embodiment, the criterion for determining the ascending and descending postures is to use the difference between the angles of two adjacent Euler angles in the data packet. If the difference is greater than 0, it is an ascending posture, and if the difference is less than 0, it is a descending posture; repeat the calculation, and put the data of the ascending posture and the descending posture in the corresponding data sets, respectively, and the data sets record the angular velocities of the left and right foot pedaling the bicycle cranks.

[0173] against Figure 7 The angular velocity collected by the IMU within 1s is used to segment the left and right feet, thereby obtaining the segmented data, such as Figure 8 shown.

[0174] exist Figure 7 It was found that the rotation period of the Euler angle is less than 180°. According to research, athletes will sway left and right during actual riding on the field, and the change value of the Y-axis Euler angle cannot reach 90° or -90°. According to the principle of IMU Euler angle spatial attitude solution, the roll angle of the IMU installed on the bicycle crank will fluctuate, especially when riding on a curve, the bicycle will tilt more in the geodetic coordinate system. However, the minimum degree of the IMU roll angle will not be lower than 0 degrees. Therefore, it is reasonable to use the change of Euler angle as the basis for distinguishing the left and right feet of athletes when riding. Schematic diagram based on the change of Euler angle and data segmentation Figure 6 It can be clearly observed that the bicycle crank has a significant speed drop and fluctuation in the two intervals of 90°~0° (approaching 90°) and -90°~0° (approaching -90°), which is consistent with the conclusion of existing research, that is, at the top dead center and bottom dead center, the athlete's pedaling technique is hindered by the limbs, which affects the athlete's limb force and causes the bicycle crank pedaling angular velocity to drop. According to data observation, it is found that the smaller the amplitude of the bicycle crank angular velocity fluctuation caused by the dead point, the better.

[0175] 5. Pedaling technique smoothness test

[0176] (1) Comparison of IMU and SRM data

[0177] 1) Real-time pedaling frequency detection results

[0178] Table 1 shows the results of collecting cadence data from the 1st to the 4th 125m cycling experiments.

[0179] Table 1 Cadence data collected by IMU and SRM in the 125m cycling experiment

[0180]

[0181] In Table 1, the mean and standard deviation of the cadence collected by IMU and SRM in the 125m cycling test were averaged and calculated, and the calculated differences were 0.495rpm and 0.507rpm.

[0182] Table 2 shows the results of collecting cadence data from the 1st to the 4th 250m cycling experiments.

[0183] Table 2 Cadence data collected by IMU and SRM in the 250m cycling experiment

[0184]

[0185] In Table 2, the mean and standard deviation of the cadence collected by the IMU and SRM in the 250m cycling test were averaged and the calculated differences were 0.200rpm and 0.201rpm.

[0186] In the model verification experiment, the real-time pedaling frequency was calculated according to the formula based on the data collected by IMU, and the pedaling frequency was compared and analyzed with the real-time pedaling frequency output by SRM. The mean difference of the pedaling frequency collected by IMU and SRM in all test data was less than 1rpm, and the standard deviation was less than 0.88rpm, and the results showed high consistency. The experimental results show that the real-time pedaling frequency data calculated based on the angular velocity changes of the crank collected by IMU has high accuracy.

[0187] 2) Real-time cycling speed measurement data

[0188] Table 3 compares the speed data collected by IMU and SRM in the 125m cycling experiment. The mean and standard deviation of the speed collected by IMU and SRM in the 125m cycling test are averaged and calculated to be 0.145m / s and 0.158m / s, respectively.

[0189] Table 3 Speed ​​data collected by IMU and SRM in the 125m cycling experiment

[0190]

[0191] Table 4 compares the real-time speed data collected by IMU and SRM in the 250 m cycling experiment. The mean and standard deviation of the speed collected by IMU and SRM in the 250 m cycling test are averaged and calculated to be 0.028 m / s and 0.028 m / s, respectively.

[0192] Table 4 Speed ​​data collected by IMU and SRM in the 250m cycling experiment

[0193]

[0194] From the comparison of the data in Tables 3 and 4, it can be seen that the real-time speed is calculated based on the data collected by the IMU, and the real-time speed is compared and analyzed with the SRM output. The experimental results show that when the real-time angular velocity of the crank is used to calculate the speed of track cycling, it has high accuracy and meets the accuracy requirements of data collection and subsequent applications.

[0195] The above experimental data show that in actual application experiments or actual application data collection, the use of IMU devices alone to collect data, and based on the data processing and calculation provided by this solution, its accuracy can fully meet the evaluation requirements of athletes' sports data.

[0196] (2) Model verification experiment pedaling technique smoothness evaluation results

[0197] In this embodiment, the test results of smoothness are calculated based on the data obtained in the actual test process. According to the mathematical model for evaluating the smoothness of pedaling technique constructed in this study, the experimental data collected in the model verification experiment are substituted into the corresponding formulas (1)-(8) of the evaluation model for calculation. The specific calculation results are shown in Tables 5 and 6 below.

[0198] Table 5 Data table of the smoothness test results of pedaling technique in 4 experiments of 125m cycling

[0199]

[0200] Table 5 records the evaluation results of the smoothness of the pedaling technique in the 125m experiment. Analysis of the evaluation results of PBI in Table 5 shows that, based on the evaluation results of FRC, LFC, RFC and PBI absolute values ​​in Table 5, the smoothness of the pedaling technique in the 125m-01 experiment is the best.

[0201] Table 6 Data table of the smoothness test results of pedaling technique in 4 experiments of 250m cycling

[0202]

[0203] A comparative analysis was conducted on the pedaling technique smoothness evaluation results of the 250m cycling experiment in Table 6. Combined with the FRC, LFC and RFC data analysis, it was found that in the 250m cycling experiment, the FRC, LFC and RFC data of the 250m-01 experiment were significantly smaller than those of the other three experiments. After the introduction of the absolute value of PBI, the pedaling technique smoothness evaluation results in the 250m-01 experiment were still the best.

[0204] (3) Evaluation of the smoothness of pedaling technique in application verification experiments

[0205] Table 7 Sprint cycling 4 pedaling technique smoothness data table

[0206]

[0207] Substitute the data of the four sprint training tests collected in the application verification experiment into formulas (1)-(8) to obtain the pedaling technique smoothness evaluation data of the four sprint training tests, as shown in Table 7.

[0208] It can be seen from the analysis of the pedaling technique smoothness evaluation index established according to the present embodiment that the pedaling technique smoothness evaluation index can effectively evaluate the quality of the athlete's pedaling technique.

[0209] In summary, combined again Fig. 9 As shown, when this scheme is directly applied to the pedaling smoothness detection process, its main method flow is:

[0210] S1. Acquire motion data during bicycle pedaling, wherein the motion data includes: a real-time angular velocity of a crank, a real-time angular velocity of a left crank, and a real-time angular velocity of a right crank of the bicycle; the motion data is collected by an IMU device, and the IMU device also collects Euler angle data;

[0211] S2. Based on the motion data, calculate the average angular velocity of the bicycle crank, the average angular velocity of the left foot pedaling crank and the average angular velocity of the right foot pedaling crank, and count the total number of bicycle crank angular velocity data N and the total number of real-time crank angular velocity data N of the left foot pedaling bicycle L The total amount of real-time crank angular velocity data N of the right foot pedaling the bicycle R ;

[0212] S3, calculating the smoothness coefficient of the whole pedaling technique based on the coefficient of variation of the bicycle crank angular velocity; calculating the smoothness coefficient of the left pedaling technique based on the coefficient of variation of the left foot pedaling crank angular velocity; calculating the smoothness coefficient of the right pedaling technique based on the coefficient of variation of the right foot pedaling crank angular velocity; calculating the left and right pedaling balance indexes based on the left and right pedaling technique smoothness coefficients;

[0213] S4. The smoothness of bicycle pedaling technique is evaluated based on the smoothness coefficient of the whole pedaling technique, the smoothness coefficient of the left foot pedaling technique, the smoothness coefficient of the right foot pedaling technique and the left and right pedaling balance index.

[0214] In another embodiment, the solution of the present invention can also be implemented in the form of a device, which includes one or more processors, a memory, multiple timing devices and an IMU device. The timing device and the IMU device send the collected data to the processor; the processor can call the computer instructions in the memory based on the collected data to execute the bicycle pedaling smoothness detection method.

[0215] The processor may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or information execution capabilities, and may control other components in the device to perform desired functions.

[0216] The memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program information may be stored on the computer-readable storage medium, and the processor may run the program information to implement the master mode I2C / SMBUS control method or other desired functions of the various embodiments of the present invention described above.

[0217] In one example, the device may further include: an input device and an output device, and these components are interconnected via a bus system and / or other forms of connection mechanisms.

[0218] The logic and / or steps represented in the flowchart or otherwise described herein may be embodied in any readable storage medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other system that can fetch instructions from and execute instructions on an instruction execution system, apparatus, or device), or in combination with such instruction execution systems, apparatuses, or devices.

[0219] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for detecting bicycle pedaling smoothness, characterized in that: The method comprises: S1. Acquire motion data during bicycle pedaling, wherein the motion data includes: a real-time angular velocity of a crank, a real-time angular velocity of a left crank angle, and a real-time angular velocity of a right crank angle of the bicycle; the motion data is collected by an IMU device, and the IMU device also collects Euler angle data; S2. Based on the motion data, calculate the average angular velocity of the bicycle crank, the average angular velocity of the left foot pedaling crank and the average angular velocity of the right foot pedaling crank, and count the total number of bicycle crank angular velocity data N and the total number of real-time crank angular velocity data N of the left foot pedaling bicycle L The total amount of real-time crank angular velocity data N of the right foot pedaling the bicycle R ; S3, calculating the smoothness coefficient of the whole pedaling technique based on the coefficient of variation of the bicycle crank angular velocity; calculating the smoothness coefficient of the left pedaling technique based on the coefficient of variation of the left foot pedaling crank angular velocity; calculating the smoothness coefficient of the right pedaling technique based on the coefficient of variation of the right foot pedaling crank angular velocity; calculating the left and right pedaling balance indexes based on the left and right pedaling technique smoothness coefficients; S4. The smoothness of bicycle pedaling technique is evaluated based on the smoothness coefficient of the whole pedaling technique, the smoothness coefficient of the left foot pedaling technique, the smoothness coefficient of the right foot pedaling technique and the left and right pedaling balance index.

2. The method according to claim 1, characterized in that In S3, the calculation method of the smoothness coefficient FRC of the whole pedaling technique is: Among them, X i represents the real-time angular velocity of the ith crank collected, is the average angular velocity of the crank.

3. The method according to claim 1, characterized in that In S3, the calculation method of the left foot pedaling technique smoothness coefficient LFC is: in, represents the real-time angular velocity of the i-th left crank angle collected, It represents the mean angular velocity of the left foot pedaling the crank.

4. The method according to claim 1, characterized in that: In S3, the calculation method of the right foot pedaling technique smoothness coefficient RFC is: in, represents the real-time angular velocity of the i-th right crank angle collected, Represents the mean angular velocity of the right foot pedaling the bicycle crank.

5. The method according to claim 1, characterized in that In S4, the smoothness of bicycle pedaling technique is judged as follows: The closer the absolute value of the left and right pedaling balance index is to 0, the higher the similarity of the left and right pedaling techniques is, and the smoother the bicycle pedaling technique is; The smaller the smoothness coefficient of the whole pedaling technique, the smoother the bicycle pedaling technique; The smaller the smoothness coefficient of the left foot pedaling technique, the smoother the bicycle pedaling technique; The smaller the smoothness coefficient of the right foot pedaling technique, the smoother the bicycle pedaling technique.

6. The method according to claim 1, characterized in that In S1, the IMU device is fixed on the inner side of the bicycle crank and is fixed parallel to the bicycle crank, the lateral long axis of the IMU device is parallel to the long axis of the bicycle crank, and the Z axis of the IMU device is perpendicular to the inner surface of the bicycle crank.

7. The method according to claim 1, characterized in that The S2 further includes: Calculate real-time pedaling frequency CAD: Among them, k represents the acquisition frequency of the IMU device, dθ represents the real-time angle change of the bicycle crank, t represents the riding time, θ represents the bicycle crank angle; ω represents the angular velocity of the crank rotation; dt represents the time taken by the IMU device to collect data each time.

8. The method according to claim 1, characterized in that The S2 further includes: Calculate the real-time riding speed v: Among them, k represents the acquisition frequency of the IMU device, dθ represents the real-time angle change of the bicycle crank, t represents the riding time, θ represents the bicycle crank angle, C represents the circumference of the bicycle wheel, and G represents the fixed gear ratio of the bicycle; dt represents the time taken by the IMU device to collect data each time; ω represents the angular velocity of the crank rotation.

9. A bicycle pedaling smoothness detection system, characterized in that: The system comprises: Multiple training timing modules to record the time during riding; An IMU device is used to collect motion data, wherein the motion data includes: a real-time angular velocity of a bicycle crank, a real-time angular velocity of a left crank angle of a bicycle, and a real-time angular velocity of a right crank angle of a bicycle; A camera module for acquiring motion images during riding; Display, used to display time and test data information; A data processing module is used to calculate the smoothness coefficient of the whole pedaling technique, the smoothness coefficient of the left foot pedaling technique, the smoothness coefficient of the right foot pedaling technique and the left and right pedaling balance index; The system is used to execute the bicycle pedaling smoothness detection method as described in any one of claims 1-8.

10. A bicycle pedaling smoothness detection device, characterized in that: The device includes a timing device, an IMU device, a processor and a memory; The timing device and the IMU device send the collected data to the processor; The processor calls the computer instructions in the memory to execute the bicycle pedaling smoothness detection method according to any one of claims 1-8.

Images