Track bicycle crank kinematics data processing method and system based on fusion calibration of imu and hall sensor

Abstract

The application discloses a kind of based on IMU and Hall sensor fusion calibration's field bicycle crank kinematics data processing method and system, comprising: S1: equipment installation: in field bicycle crank installation data acquisition equipment, the data acquisition equipment includes IMU and Hall sensor, magnet is installed on the frame;S2: time synchronization and calibration: calibration is implemented to IMU and Hall sensor, to synchronize with Beijing time;S3: data acquisition: record wheel circumference and gear ratio, start IMU and Hall data synchronous acquisition, simultaneously collect the Beijing time when athlete passes through terminal point time and cycling performance;S4: data processing and analysis: according to record cycling start and end time, the IMU and Hall sensor data in corresponding time period are intercepted, based on Hall pulse and Euler angle peak fusion data, IMU angular velocity data is segmented integral and proportion correction, calculate real-time speed, real-time cycling distance and pedaling technical index;S5: data visualization and report export.

Description

Technical Field

[0001] This disclosure relates to the field of sports training monitoring and intelligent sensing technology, specifically to a method and system for processing track bicycle crank kinematics data based on IMU and Hall sensor fusion calibration. Background Technology

[0002] In track cycling, an athlete's technical performance directly determines their competition results. This sport is characterized by the fact that athletes must complete various events at a maximum speed of 90 km / h on a 200-meter wooden circular track. Their pedaling efficiency, rhythmic stability, and left-right leg symmetry are the core factors influencing their performance.

[0003] However, existing technologies struggle to meet the demands for high-precision kinematic parameter acquisition: traditional wheel speed sensors, cadence meters, or GPS devices can only acquire basic motion data, failing to accurately capture key dynamic parameters such as the crank's instantaneous angular velocity, angular acceleration, and pedaling phase; while inertial measurement units (IMUs) can monitor crank motion, the inherent zero-bias drift characteristic of their gyroscopes causes angular errors to accumulate over time, severely impacting data reliability; and although Hall effect sensors can provide absolute position references for each lap through magnetic triggering, they only output discrete event signals, unable to fully reflect continuous motion details. This technological bottleneck contradicts the unique environment of track cycling: as a device with a fixed gear ratio and no braking system, the crank rotation direction directly determines the wheel's trajectory, requiring athletes to ride along the inner markings of the bowl-shaped elliptical track to optimize their route. Even small fluctuations in real-time speed and differences in accumulated distance can affect the final result.

[0004] Existing data collection methods suffer from three major technical challenges: First, conventional equipment lacks sufficient accuracy. For high-speed cycling at 20m / s, a one-second error can lead to a 20-meter distance deviation, severely interfering with the assessment of athletic performance. Second, modern track bikes use enclosed wheel designs, making it impractical to add equipment to traditional wheels. Third, high-speed camera methods are susceptible to obstruction and cannot accurately calculate the actual driving distance.

[0005] Therefore, there is an urgent need to develop a new monitoring system that can overcome the limitations of existing technologies. Through innovative integration of hardware and algorithms, it can achieve high-precision, low-drift, and automatic periodic segmentation acquisition of crank kinematic parameters, providing reliable data support for athlete technical movement analysis, training status monitoring, and cycling strategy optimization. Summary of the Invention

[0006] According to the present invention, a method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration is proposed, characterized in that the method includes: S1: Equipment Installation A data acquisition device is installed on the crank of a track bicycle. The data acquisition device includes an IMU and a Hall sensor, and a magnet corresponding to the Hall sensor is installed on the frame. S2: Time Synchronization and Calibration The IMU and Hall sensor are calibrated to synchronize with Beijing time; S3: Data Acquisition Record the wheel circumference and gear ratio, begin synchronous acquisition of IMU and Hall data, and simultaneously acquire the Beijing time of the athlete's crossing the finish line and the cycling time; S4: Data Processing and Analysis Based on the recorded start and end times of the ride, IMU and Hall sensor data within the corresponding time period are extracted. Based on the fusion data of Hall pulse and Euler angle peak, the IMU angular velocity data is integrated in segments and proportionally corrected to calculate real-time speed, real-time riding distance and pedaling technical indicators. S5: Data Visualization and Report Export Export the calculated data from S4, automatically segment the pedaling cycle according to the fusion data of Hall pulse and Euler angle peak, and generate a single-lap pedaling cycle report for export.

[0007] In one embodiment, the Y-axis of the IMU is parallel to the long axis of the crankshaft, the X-axis of the IMU is perpendicular to the long axis of the crankshaft, and the Z-axis of the IMU is perpendicular to the attachment surface between the IMU and the crankshaft.

[0008] In one embodiment, the data acquisition device further includes a microcontroller unit, a wireless communication module, and a host computer. The IMU synchronously acquires the angular velocity of the three-axis gyroscope, the data from the three-axis accelerometer, and the three-dimensional Euler angle attitude information and transmits the data with the microcontroller unit. The Hall sensor outputs periodic pulse signals to the microcontroller unit. The host computer completes the precise alignment of the local clock with the Beijing time source. The microcontroller unit coordinates the real-time acquisition, timestamp marking, and preprocessing tasks of the data streams from the IMU and the Hall sensor, and transmits the data uplink to the cloud platform through the wireless communication module.

[0009] In one embodiment, the data processing and analysis includes the following steps: Read the collected data; Enter the wheel circumference, gear ratio, start time (Beijing time), end time (Beijing time), or performance information; The data is effectively segmented based on the input time information, and interval data is automatically extracted. Hall pulses are used to periodically correct the angular displacement obtained from the integration of the IMU gyroscope, constructing a "piecewise integration-Hall correction" model to suppress angle drift. The Hall pulse time series is extracted. Euler Y-axis peak time series ; Combine the two sets of data for each segment The IMU angular velocity integral is corrected to 2π for single-circle angular velocity integral. calculate Total cycling distance The pedaling technique smoothness indicators are SSP, SLP, SRP, and PBI.

[0010] In one embodiment, the "piecewise integration-Hall calibration" model includes: Between the i-th Hall pulse and the (i+1)-th Hall pulse, the gyroscope output is... Integrating yields the angular displacement. The second step is to adjust the gyroscope output between the e-th Euler peak and the (e+1)-th Euler peak. integral The cycle order is as follows: the crank rotation first reaches the Euler Y peak period, and after rotating a certain angle, the Hall pulse period is obtained; if And simultaneously satisfy , If the tolerance threshold is used, the angular velocity data within this interval will be scaled proportionally: .

[0011] In one embodiment, the data processing flow includes calculating the real-time vehicle speed based on the calibrated crank angular velocity ω(t), combined with a preset gear ratio R and tire circumference C: .

[0012] In one embodiment, the data processing flow includes calculating the cumulative cycling distance using integration plus pedaling cycles, which includes the following steps: determining the complete pedaling cycles within the start and end points of the ride; calculating the cycling distance for the complete pedaling cycles; integrating the angular velocity for the portions of the start and end phases of the ride that are less than one cycle to form three data segments; and calculating the cycling distance again by gradually accumulating these segments; the times of the four marker points of the ride are defined as the start time of the ride. The moment when the complete pedaling cycle begins The moment when the complete pedaling cycle ends End of the ride ; ; ; In the above formula and Simultaneously satisfy and ,Depend on The period calculation formula can be derived Number of cycles after fusion calibration ,and for Positive integer multiples; The final cycling distance can be obtained by resolving the above formulas. : .

[0013] In one embodiment, each complete pedaling cycle is automatically segmented using adjacent Euler Y peak values ​​as boundaries. ,right Each complete cycle generates a single-lap pedaling data report, including the following: SSP: In the above formula, This represents the real-time angular velocity of the crank angle during one cycle of bicycle pedaling, as collected by the sensor. This represents the average angular velocity of the crank during one pedaling cycle. The standard deviation of the pedal crank angular velocity during a single pedaling cycle; SLP: In the above formula This represents the real-time angular velocity of the left crank angle collected by the sensor during one pedaling cycle. This represents the average angular velocity of the left foot pressing the crank during one pedal cycle. The standard deviation of the left foot's pedal crank angular velocity during a single pedaling cycle; SRP: In the above formula This represents the real-time angular velocity of the right crank angle collected by the sensor during one pedaling cycle. This represents the average angular velocity of the right foot pressing the bicycle crank during one pedaling cycle. Standard deviation of the right foot pedal crank angular velocity during a single pedal cycle; PBI: The above formula represents the total number of crank angular velocity data collected by the IMU within one cycle of cycling. The following relationship must be satisfied: .

[0014] and The data represent the angular velocity data for the left and right half-cycles of the crank during one pedaling cycle, respectively.

[0015] This invention provides a track cycling crank kinematics data processing system based on IMU and Hall sensor fusion calibration, characterized in that: it includes... The data acquisition module is configured to acquire crank kinematics data during track cycling. The data analysis module is configured to enable time synchronization of the equipment and accurate processing and analysis of the data collected by the equipment.

[0016] In one embodiment, the processing and analysis of the collected data includes using the athlete's start time, end time, gear ratio, and wheel circumference as inputs to perform precise data segmentation and IMU-Hall fusion calibration, using the calibrated data to calculate the athlete's real-time speed, pedaling frequency, and cumulative cycling distance during the cycling process, and generating a single-lap pedaling report and exporting various data.

[0017] This invention significantly improves the accuracy and reliability of crank kinematics data acquisition for track cycling by integrating a high-precision inertial measurement unit (IMU) with a Hall sensor. Traditional single IMU systems are susceptible to zero-bias drift during prolonged high-speed riding, leading to cumulative errors in angular velocity and angle data. This invention utilizes discrete phase reference points provided by the Hall sensor to periodically and dynamically correct IMU data, effectively suppressing drift and achieving high-precision acquisition of key kinematic parameters such as crank angular displacement, cadence, real-time riding speed, and Euler angles. At the algorithm level, the system constructs an adaptive data segmentation model that intelligently identifies and accurately extracts effective pedaling cycles. Combined with parameters such as fixed gear ratio and tire circumference, the system can accurately calculate real-time riding speed and cumulative mileage, and automatically generate a detailed single-lap kinematic analysis report. This report includes crank angular displacement-time curves, instantaneous angular velocity and angular acceleration waveforms, and cumulative pedaling cycle statistics, comprehensively evaluating the planarity, stability, and periodic consistency of the pedaling action, significantly improving the automation and intelligence of data processing. Furthermore, the system supports both wired and wireless dual-mode data transmission and employs a high-precision time synchronization mechanism, allowing it to flexibly adapt to complex application scenarios such as laboratory environments and long-distance race tracks, significantly enhancing the device's environmental adaptability and user-friendly operation. In summary, this invention not only effectively solves the problem of insufficient accuracy in traditional equipment during high-speed, long-duration cycling, but also provides a scientific and reliable quantitative analysis tool for diagnosing athletes' technical movements, evaluating training effectiveness, and optimizing competitive performance, possessing outstanding technical advantages and broad application value. Attached Figure Description

[0018] Figure 1 A flowchart of a track bicycle crank kinematics data processing system based on IMU and Hall sensor fusion calibration is shown according to an embodiment of the present disclosure.

[0019] Figure 2 This diagram illustrates a flowchart of data acquisition and timestamp synchronization of a data acquisition device according to an embodiment of the present disclosure.

[0020] Figure 3 A flowchart of the host computer data processing and single-loop segmentation algorithm according to an embodiment of the present disclosure is shown.

[0021] Figure 4 A flowchart is shown for a method for processing track bicycle crank kinematics data based on IMU and Hall sensor fusion calibration according to an embodiment of the present disclosure. Detailed Implementation

[0022] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings.

[0023] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0024] The various exemplary embodiments, features, and aspects of this disclosure will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions.

[0025] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0026] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0027] Furthermore, to better illustrate this disclosure, numerous specific details are set forth in the following detailed description. Those skilled in the art will understand that this disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art have not been described in detail in order to highlight the main points of this disclosure.

[0028] Reference manual attached Figure 1 and 4The document illustrates a flowchart of a track bicycle crank kinematics data processing system and method based on IMU and Hall sensor fusion calibration, according to an embodiment of this disclosure. The method includes: S1: Equipment Installation A data acquisition device is installed on the crank of a track bicycle. The data acquisition device includes an IMU and a Hall sensor. A magnet corresponding to the Hall sensor is installed on the frame. The data is fused with the Hall sensor and Euler angles to provide an absolute reference, effectively suppressing IMU gyroscope drift and achieving long-term stable high-precision angle measurement. S2: Time Synchronization and Calibration The IMU and Hall sensor are calibrated to synchronize with Beijing time; S3: Data Acquisition Record the wheel circumference and gear ratio, begin synchronous acquisition of IMU and Hall data, and simultaneously acquire the Beijing time of the athlete's crossing the finish line and the cycling time; S4: Data Processing and Analysis Based on the recorded start and end times of the ride, IMU and Hall sensor data within the corresponding time period are extracted. Based on the fusion data of Hall pulse and Euler angle peak, the IMU angular velocity data is integrated in segments and proportionally corrected to calculate real-time speed, real-time riding distance and pedaling technical indicators. S5: Data Visualization and Report Export Export the calculated data from S4, automatically segment the pedaling cycle according to the fusion data of Hall pulse and Euler angle peak, and generate a single-lap pedaling cycle report for export.

[0029] In one embodiment, the data acquisition device is fixed to the inside of the left crank of the bicycle near the bottom bracket. This area is a non-stressed region, avoiding motion interference and ensuring data acquisition stability. The IMU is built into the data acquisition device. The Y-axis of the IMU is parallel to the long axis of the crank, the X-axis is perpendicular to the long axis of the crank, and the Z-axis is perpendicular to the attachment surface between the IMU and the crank, to reduce the impact of installation deviation on the data. A Hall sensor is integrated into the data acquisition device. Rotating the crank ensures that a pulse signal is generated for each revolution of the crank. In this embodiment, the IMU is an inertial measurement unit, which is existing technology and will not be described in detail here. The IMU uses a high-precision sensor of model JY901B, which has a sampling frequency of ≥200Hz and can simultaneously acquire triaxial gyroscope angular velocity, triaxial accelerometer data, and three-dimensional Euler angle attitude information. It achieves high-speed data transmission with the microcontroller unit (MCU) through a serial transceiver interface (RX / TX). The Hall sensor uses a digital switch type device and outputs periodic pulse signals to the microcontroller unit (MCU) through an external interrupt pin.

[0030] In one embodiment, see Appendix Figure 2 The data acquisition equipment also includes a microcontroller unit, a wireless communication module, and a host computer. The IMU uses a high-precision sensor of model JY901B, which has a sampling frequency of ≥200Hz. It synchronously acquires the angular velocity of the three-axis gyroscope, the data of the three-axis accelerometer, and the three-dimensional Euler angle attitude information and transmits the data with the microcontroller unit (MCU).

[0031] Hall sensors output periodic pulse signals to microcontroller units (MCUs). Specifically, Hall sensors use digital switching devices and output periodic pulse signals to the microcontroller unit (MCU) through an external interrupt pin.

[0032] The host computer completes the precise alignment of the local clock with the Beijing time source. Specifically, the system introduces the Network Time Protocol (NTP) time synchronization mechanism, and the host computer completes the millisecond-level precise alignment of the local clock with the Beijing time source, constructing a unified spatiotemporal coordinate system across devices, which meets the millimeter-level precision acquisition requirements of crank dynamic parameters in high-speed cycling scenarios.

[0033] The microcontroller unit (MCU) acts as a central node, coordinating the real-time acquisition, timestamping, and preprocessing of data streams from the IMU and Hall effect sensors. It then transmits the data to the cloud platform via wireless communication modules (USB or Bluetooth 5.0) and other data transmission protocols. The MCU is built on the STM32F4 series low-power microcontroller and includes a built-in RTC module to ensure strict consistency of the time base between the two sensors.

[0034] The data acquisition device features a miniaturized design and is independently powered by a built-in rechargeable lithium battery, meeting the continuous operation requirements of long-term outdoor training scenarios.

[0035] In one embodiment, the host computer runs a data processing program developed based on Python. (See attached...) Figure 3 As shown, data processing and analysis includes the following steps (host computer data processing and single-cycle segmentation algorithm): Step 1: Read the acquired data from the sensor ports (IMU and Hall sensor); Step 2: Enter the wheel circumference, gear ratio, start time (Beijing time), end time (Beijing time), or performance information; Step 3: Effectively segment the data based on the input time information (e.g., start time 10:01:35.109 and end time 10:03:15.234), automatically extract the data within this interval, and use Hall pulses to periodically correct the angular displacement obtained by integrating the IMU gyroscope, constructing a "segmented integration-Hall correction" model to suppress angle drift; extract the Hall pulse time series. Euler Y-axis peak time series ; Combine the two sets of data for each segment The IMU angular velocity integral is corrected to 2π for single-circle angular velocity integral. Step 4: Calculation Total cycling distance The pedaling technique smoothness indices are SSP, SLP, SRP, and PBI, where SSP is the smoothness of a single pedaling loop, SLP is the smoothness of the left-foot pedaling technique, SRP is the smoothness of the right-foot pedaling technique, and PBI is the pedaling balance coefficient.

[0036] Step 5: Output the collected data in the specified format file, export the angular velocity curve, statistical indicators and visualization report for each cycle, which can fully support the diagnosis of competitive performance and the optimization of training strategies.

[0037] In one embodiment, the "piecewise integration-Hall calibration" model includes: Between the i-th Hall pulse and the (i+1)-th Hall pulse, the gyroscope output is... Integrating yields the angular displacement. The second step is to adjust the gyroscope output between the e-th Euler peak and the (e+1)-th Euler peak. integral The cycle order is as follows: the crank rotation first reaches the Euler Y peak period, and after rotating a certain angle, the Hall pulse period is obtained; if And simultaneously satisfy , If the tolerance threshold is used, the angular velocity data within this interval will be scaled proportionally: .

[0038] In one embodiment, the host computer's software system executes the following data processing flow: Based on the calibrated crank angular velocity ω(t), combined with the preset gear ratio R and tire circumference C, the real-time vehicle speed is calculated: .

[0039] The cumulative cycling distance is obtained by integrating the pedaling cycles: The host computer system, Chen Xu, first determines the complete pedaling cycles within the start and end points of the ride, calculates the cycling distance for each complete cycle, and integrates the angular velocity for the portions of the start and end phases that are less than one cycle, forming three data segments. These segments are then gradually accumulated to calculate the cycling distance, further reducing the cumulative error caused by drift when using a single integral. The times of the four marker points of the ride are defined as the start time of the ride. (At the initial moment of crank rotation), the moment when the complete pedaling cycle begins. (The moment when the left crank first turns to vertical position), the moment when the complete pedaling cycle ends. (The moment when the left crank last turns to a vertical position), the end of the ride. (At the final moment of crank rotation); ; ; In the above formula and Simultaneously satisfy and ,Depend on The period calculation formula can be derived Number of cycles after fusion calibration ,and for Positive integer multiples; The final cycling distance can be obtained by resolving the above formulas. : .

[0040] In one embodiment, during data generation, each complete pedaling cycle is automatically segmented using adjacent Euler Y peak values ​​as boundaries. ,right Each complete cycle generates a single-lap pedaling data report, including the following: SSP (Single-Loop Pedaling Technique Smoothness): In the above formula, This represents the real-time angular velocity of the crank angle during one cycle of bicycle pedaling, as collected by the sensor, in rad / s. This represents the average angular velocity of the crank during one pedaling cycle, measured in rad / s. The standard deviation of the pedal crank angular velocity during a single pedaling cycle; SLP (Smoothness of Left Foot Pedaling Technique): In the above formula This represents the real-time angular velocity (in rad / s) of the left crank angle collected by the sensor during one pedaling cycle. This represents the average angular velocity of the left foot pressing the crank during one pedal cycle (unit: rad / s). The standard deviation of the left foot's pedal crank angular velocity during a single pedaling cycle; SRP (Right Foot Pedaling Smoothness): In the above formula This represents the real-time angular velocity (in rad / s) of the right crank angle collected by the sensor during one pedaling cycle. This represents the average angular velocity of the right foot pressing the bicycle crank during one pedaling cycle (unit: rad / s). Standard deviation of the right foot pedal crank angular velocity during a single pedal cycle; PBI (Pedal Balance Factor): The above formula represents the total number of crank angular velocity data collected by the IMU within one cycle of cycling. The following relationship must be satisfied: .

[0041] and The data represent the angular velocity data for the left and right half-cycles of the crank during one pedaling cycle, respectively.

[0042] As an example, the table below shows the output pedaling technique smoothness indices SSP, SLP, SRP, and PBI: Please refer to the attached instruction manual. Figure 1 and attached Figure 2 This invention illustrates a track bicycle crank kinematics data processing system based on IMU and Hall sensor fusion calibration provided in an embodiment of the present disclosure, including a data acquisition module and a data analysis module.

[0043] In one embodiment, the data acquisition module is configured to acquire crank kinematic data during track cycling. Furthermore, the data acquisition module integrates modules such as an IMU, Hall effect sensor, MCU, 5G wireless communication, and a power supply lithium battery to accurately acquire and store the crank kinematic data of the track cyclist throughout the entire riding process.

[0044] In one embodiment, the data analysis module includes a host computer configured to synchronize the device's time and accurately process and analyze the data collected by the device. It primarily relies on the host computer software system to achieve two functions: firstly, synchronizing the device's time (data acquisition module) by sending the host computer's real-time Beijing time via a wired / wireless connection to the device, with the synchronization signal indicated by the host computer interface and device indicator lights; secondly, accurately processing and analyzing the data collected by the device (data acquisition module). This involves inputting the athlete's start and end times (i.e., race time), gear ratio, and wheel circumference to perform precise data segmentation and IMU-Hall fusion calibration. The calibrated data is then used to calculate the athlete's real-time speed, pedaling frequency, and cumulative distance, and to generate a single-lap pedaling report and export various data.

[0045] In the description herein, it should be understood that the terms “up,” “down,” “front,” “back,” “left,” “right,” “vertical,” “horizontal,” “top,” “bottom,” “inner,” and “outer,” etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description.

[0046] The terminology used herein is chosen to best explain the principles, practical applications, or technological improvements to the various embodiments, or to enable those skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for processing track bicycle crank kinematics data based on IMU and Hall sensor fusion calibration, characterized in that, The method includes: S1: Equipment Installation A data acquisition device is installed on the crank of a track bicycle. The data acquisition device includes an IMU and a Hall sensor, and a magnet corresponding to the Hall sensor is installed on the frame. S2: Time Synchronization and Calibration The IMU and Hall sensor are calibrated to synchronize with Beijing time; S3: Data Acquisition Record the wheel circumference and gear ratio, begin synchronous acquisition of IMU and Hall data, and simultaneously acquire the Beijing time of the athlete's crossing the finish line and the cycling time; S4: Data Processing and Analysis Based on the recorded start and end times of the ride, IMU and Hall sensor data within the corresponding time period are extracted. Based on the fusion data of Hall pulse and Euler angle peak, the IMU angular velocity data is integrated in segments and proportionally corrected to calculate real-time speed, real-time riding distance and pedaling technical indicators. S5: Data Visualization and Report Export Export the calculated data from S4, automatically segment the pedaling cycle according to the fusion data of Hall pulse and Euler angle peak, and generate a single-lap pedaling cycle report for export.

2. The method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration according to claim 1, characterized in that: The Y-axis of the IMU is parallel to the long axis of the crankshaft, the X-axis of the IMU is perpendicular to the long axis of the crankshaft, and the Z-axis of the IMU is perpendicular to the attachment surface between the IMU and the crankshaft.

3. The method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration according to claim 1 or 2, characterized in that: The data acquisition device also includes a microcontroller unit, a wireless communication module, and a host computer. The IMU synchronously acquires the angular velocity of the three-axis gyroscope, the data from the three-axis accelerometer, and the three-dimensional Euler angle attitude information and transmits the data with the microcontroller unit. The Hall sensor outputs periodic pulse signals to the microcontroller unit. The host computer completes the precise alignment of the local clock with the Beijing time source. The microcontroller unit coordinates the real-time acquisition, timestamp marking, and preprocessing tasks of the data streams from the IMU and the Hall sensor, and transmits the data uplink to the cloud platform through the wireless communication module.

4. The method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration according to claim 1, characterized in that: The data processing and analysis includes the following steps: Read the collected data; Enter the wheel circumference, gear ratio, start time (Beijing time), end time (Beijing time), or performance information; The data is effectively segmented based on the input time information, and interval data is automatically extracted. Hall pulses are used to periodically correct the angular displacement obtained from the integration of the IMU gyroscope, constructing a "piecewise integration-Hall correction" model to suppress angular drift. The Hall pulse time series is extracted. Euler Y-axis peak time series ; Combine the two sets of data for each segment The IMU angular velocity integral is corrected to 2π for single-circle angular velocity integral. calculate Total cycling distance The pedaling technique smoothness indicators are SSP, SLP, SRP, and PBI.

5. The method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration according to claim 4, characterized in that: The "piecewise integration-Hall calibration" model includes: Between the i-th Hall pulse and the (i+1)-th Hall pulse, the gyroscope output is... Integrating yields the angular displacement. The second step is to adjust the gyroscope output between the e-th Euler peak and the (e+1)-th Euler peak. integral The cycle order is as follows: the crank rotation first reaches the Euler Y peak period, and after rotating a certain angle, the Hall pulse period is obtained; if And simultaneously satisfy , If the tolerance threshold is used, the angular velocity data within this interval will be scaled proportionally: 。 6. The method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration according to claim 5, characterized in that: The data processing flow includes calculating the real-time vehicle speed based on the calibrated crank angular velocity ω(t), combined with the preset gear ratio R and tire circumference C: 。 7. The method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration according to claim 6, characterized in that: The data processing flow includes using integration and pedaling cycles to obtain the cumulative cycling distance: determining the complete pedaling cycles within the start and end points of the ride, calculating the cycling distance for each complete pedaling cycle, integrating the angular velocity for the portions of the ride that are less than one cycle at the beginning and end, forming three data segments, and then calculating the cycling distance again by progressively accumulating these segments; the times of the four marker points of the ride are defined as the start time of the ride. The moment when the complete pedaling cycle begins The moment when the complete pedaling cycle ends End of the ride ; ； ； In the above formula and Simultaneously satisfy and ,Depend on The period calculation formula can be derived ; Number of cycles after fusion calibration ,and for Positive integer multiples; The final cycling distance can be obtained by resolving the above formulas. : 。 8. The method for processing track cycling crank kinematics data based on IMU and Hall sensor fusion calibration according to claim 4, characterized in that: Data generation includes: automatically segmenting each complete pedaling cycle using adjacent Euler Y peak values ​​as boundaries. ,right Each complete cycle generates a single-lap pedaling data report, including the following: SSP: In the above formula, This represents the real-time angular velocity of the crank angle during one cycle of bicycle pedaling, as collected by the sensor. This represents the average angular velocity of the crank during one pedaling cycle. The standard deviation of the pedal crank angular velocity during a single pedaling cycle; SLP: In the above formula This represents the real-time angular velocity of the left crank angle collected by the sensor during one pedaling cycle. This represents the average angular velocity of the left foot pressing the crank during one pedal cycle. The standard deviation of the left foot's pedal crank angular velocity during a single pedaling cycle; SRP: In the above formula This represents the real-time angular velocity of the right crank angle collected by the sensor during one pedaling cycle. This represents the average angular velocity of the right foot pressing the bicycle crank during one pedaling cycle. Standard deviation of the right foot pedal crank angular velocity during a single pedal cycle; PBI: The above formula represents the total number of crank angular velocity data collected by the IMU within one cycle of cycling. The following relationship must be satisfied: ， and The data represent the angular velocity data for the left and right half-cycles of the crank during one pedaling cycle, respectively.

9. A system for processing kinematic data of a track bicycle crank based on IMU and Hall sensor fusion calibration, characterized in that: include The data acquisition module is configured to acquire crank kinematics data during track cycling. The data analysis module is configured to enable time synchronization of the equipment and accurate processing and analysis of the data collected by the equipment.

10. The track cycling crank kinematics data processing system based on IMU and Hall sensor fusion calibration according to claim 9, characterized in that: The processing and analysis of the collected data includes using the athlete's start time, end time, gear ratio, and wheel circumference as inputs to perform precise data segmentation and IMU-Hall fusion calibration. The calibrated data is then used to calculate the athlete's real-time speed, pedaling frequency, and cumulative cycling distance during the cycling process. Additionally, a single-lap pedaling report can be generated, and various data can be exported.

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