Apparatus for measuring cycling power and state of saddle-riding device, and cloud system

Abstract

To provide an apparatus for measuring cycling power and a state of a saddle-riding device, which assists understanding of the entire pedaling pattern of a cyclist, optimizes a training plan, and provides a complete power measurement solution unique to a market, and a cloud system.SOLUTION: A system configuration 100 for implementing an apparatus for measuring cycling power and a state of a saddle-riding device has: a sensor member 102 which is installed on a foot of a user 108, includes a pressure sensing device and an inertial sensing module, and collects motion-related data when the user performs a cycling motion on a bicycle 101 having pedals; and a computing electronic device 104 which is communicatively coupled to the sensor member, receives the motion-related data when the user performs the cycling motion, executes and estimates a cycling power-related algorithm, and estimates cycling power when the user performs the cycling motion.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to the related technical field of cycling power measurement, and in particular to a riding equipment cycling power and status measurement device and cloud system. [Background technology]

[0002] Cycling is one of the most popular sports, and with the development of cycling, more and more cycling sports are being held on dedicated roads. In order to measure the pressure of the bicycle pedal, it is necessary to use a pressure measuring device, and then it is possible to measure the force characteristics of the athlete to achieve the optimal force generation mode.

[0003] During cycling, a cyclist uses their feet to alternately pedal the bicycle, which causes two cranks operated by the pedals to alternately rotate about their axes.

[0004] In order to better manage the training effect of a cyclist, it is necessary to provide the cyclist with useful power during the pedaling process when riding a bicycle. This information can be used to better manage the pedaling assistance of the bicycle, monitor the change in the training effect of the cyclist, or calculate the total cycling power of the cyclist.

[0005] Indicators used by cyclists to measure cycling performance include cycling power, which is the time it takes to ride a specific route alone. Cycling power is a measure of the force a cyclist exerts on a bicycle. Cycling power measures the force a cyclist exerts on the pedals and cranks of a bicycle during the rotation of the pedals over a set time interval. Because cycling power is, to a certain extent, unaffected by changes in road conditions, weather conditions, and altitude, it is a useful statistic for training and comparison for both amateur and professional cyclists.

[0006] Cycling power is typically measured at the pedals or cranks, as it is a measure of the force applied to the pedals and cranks.

[0007] A bicycle power meter is an instrument that measures a cyclist's cycling power output (in watts). As a training aid, this type of power meter can provide cyclists with feedback information about their effort; if their power is lower than this value, the cyclist can increase their power by pedaling faster or shifting to a higher gear. Power is usually displayed on a main control unit attached to the bicycle's handlebars, and a wireless connection is required between the power meter and the device that calculates and displays power.

[0008] However, with the above measurement methods, most current bicycle cycling power measurements require data to be collected from the main plate, pedals, hub, etc., and the above instruments are somewhat difficult to install and often require separate tools to disassemble the main plate or pedals for measurement, which can be very inconvenient. Summary of the Invention [Problem to be solved by the invention]

[0009] In view of this, the present invention provides a riding equipment cycling power and condition measurement device. [Means for solving the problem]

[0010] In order to improve the above-mentioned deficiencies, according to one aspect of the present invention, there is provided a cycling power and state measurement device for a riding device, which is installed on a user's foot and includes a pressure sensing device and an inertial sensing module, wherein the measurement device comprises a sensor element configured to collect motion-related data when the riding device having the user's pedals performs a cycling motion and to obtain the user's riding state, and is communicatively coupled to the sensor element to receive the motion-related data when the user performs the cycling motion, perform and estimate a cycling power-related calculation method, and estimate the cycling power when the user performs the cycling motion.

[0011] In one embodiment, the pedal riding device comprises a bicycle.

[0012] In one embodiment, the cycling motion includes performing an alternating pedaling motion on the pedal device, and the user's feet maintaining a consistent motion on the pedal device.

[0013] In one embodiment, the pressure sensing device includes a plurality of pressure sensing devices for sensing a force applied to the pedal device by the user's foot, the inertial sensing module includes a hybrid sensor combining an accelerometer and a gyroscope, and the inertial sensing module further includes a GPS sensor.

[0014] In one embodiment, the sensor member includes a microprocessor that collects and analyzes electronic signals detected by the pressure sensing device, the inertial sensing module, and the GPS sensor and converts them into corresponding pressure data, acceleration information, and GPS information of the interaction between the foot and the pedal device; a memory coupled to the microprocessor that stores the pressure data, acceleration information, and GPS information; a wireless transceiver coupled to the microprocessor that wirelessly transmits the pressure data, acceleration information, and GPS information to an external electronic device; and a power supply that provides power to the pressure sensing device, the inertial sensing module, the GPS sensor, the microprocessor, the memory, and the wireless data transceiver.

[0015] In one embodiment, the wireless transceiver is a Bluetooth or WiFi device.

[0016] In one embodiment, the data sensed by the GPS sensor can provide the user's cycling distance.

[0017] In one embodiment, the motion-related data when performing the cycling motion includes pressure sensor readings received from multiple pressure sensors in the pressure sensing device to determine the force applied to the pedals, and sensor readings from the inertial sensing module to determine the user's cycling cadence, and the speed and angle of the user's feet.

[0018] In accordance with another aspect of the present invention, there is provided a cloud system for measuring cycling power and status of a riding device, the cloud system including: a cycling power and status measurement device for a riding device; and a cloud server communicatively coupled to the computing electronic device, the cloud server receiving performance-related data and the cycling power uploaded by the computing electronic device when the user performs a cycling motion, wherein the performance-related data and the cycling power can be shared with third-party connected fitness applications via the cloud server. [Effects of the Invention]

[0019] The present invention has the following advantages: it provides complete cycling power data, estimates power in the second half of the cycle without additional hardware, has self-learning and optimization capabilities, and can be applied to various riding scenarios. The expected application benefits of the present invention lie in the technical aspect, which is that it can completely record power output throughout the entire pedaling cycle and provide more accurate cycling data. From a sports science perspective, it can help cyclists understand their overall pedaling pattern, optimize training plans, and provide a unique and complete power measurement solution on the market. [Brief explanation of the drawings]

[0020] [Figure 1] FIG. 1 illustrates a system configuration for implementing a cycling power and condition measurement device for a riding device. [Figure 2] FIG. 2 is an explanatory diagram showing the arrangement and wiring of pressure sensors according to the present invention. [Figure 3] FIG. 2 is a functional block diagram of a sensor member according to an embodiment of the present invention. [Figure 4] FIG. 1 is a system block diagram illustrating communication between the sensor module and externally connected computing electronics. [Figure 5] FIG. 1 is an explanatory diagram showing the path that a bicycle pedal can travel. [Figure 6]1 is an exemplary diagram showing the change over time in the force signal of a foot pressing down on a bicycle pedal as received from a pressure sensing device; [Figure 7] 10 is an exemplary diagram showing a z-direction component of an acceleration signal received from a pressure sensing device. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0021] Here, the present invention will be described in detail with respect to specific embodiments and aspects thereof. This description is intended to explain the structure and step flow of the present invention and is not intended to limit the scope of the claims of the present invention, but is for illustrative purposes. Therefore, in addition to the specific embodiments and comparative embodiments described in the specification, the present invention can be broadly implemented in other different embodiments. In the following, the implementation manner of the present invention will be described using certain specific embodiments, so that those skilled in the art can easily understand the effectiveness and advantages of the present invention through the contents disclosed herein. Furthermore, the present invention can be operated and implemented through other specific embodiments, and each detail described in this specification can be adapted based on different requirements, and various modifications and changes can be made without departing from the spirit of the present invention.

[0022] The present invention provides a riding equipment cycling power and condition measurement device, in particular, to measure a cyclist's power consumption while cycling, and provide the cyclist with feedback data on their exercise volume and to evaluate their training effect.

[0023] Determining a user's cycling power can provide important exercise and activity data. Knowledge of cycling power can be highly useful in various cycling-related applications, such as sports training, professional training, and recreational cycling.

[0024] For example, an athlete cycling uphill may want to maintain a cycling speed that is in line with their cycling power on the flat. If the user rides uphill at a speed that exceeds their power on the flat, they may tire more quickly and not be able to perform at their maximum potential for the same extended period of time.

[0025] Feedback on a user's cycling power allows the user to optimize their training and maximize their training effectiveness. For example, cycling power provides the user with a real-time quantification of their work efficiency and can be used for specific training techniques such as interval training.

[0026] The user's cycling power feedback can also be integrated and shared with third-party fitness applications via cloud systems such as cloud servers, allowing the user to interact with these systems.

[0027] The systems and devices described in this invention can determine a user's mechanical cycling power using multiple sensors on the user's feet. The systems and devices can measure and monitor data related to the user's movements and activities using sensors attached or installed on wearable devices or cycling equipment. The sensor measurement data can be used to calculate mechanical cycling power and obtain the user's cycling status (user).

[0028] Based on the above concept, referring to FIG. 1, FIG. 1 shows a system configuration 100 for realizing the cycling power and state measurement device of the riding device, the system configuration 100 including a sensor member 102, a computing electronic device 104, and a cloud server 106. The sensor member 102 is communicatively connected to the computing electronic device 104, and the computing electronic device 104 can receive data collected by the sensor member 102. The computing electronic device 104 is connected to the cloud server 106 via the Internet, and can upload the motion-related data and the cycling power when a user performs a cycling motion to the cloud server 106.

[0029] According to an embodiment of the present invention, the sensor element 102 includes a wireless transceiver configured to wirelessly transmit to a signal receiver of an externally connected computing electronic device 104 data collected by the sensor element 102, the force exerted by the user's foot on the bicycle pedals, acceleration, and motion-related data collected by the sensor element 102 when the user 108 is riding on the bicycle 101 and performing an activity. As will be explained in more detail below, the sensor element 102 may be attached to the user's 108's foot, for example, in the shoe or sole of the user 108, and may include a plurality of pressure sensors and an inertial sensing module (including a wireless transceiver). According to an embodiment of the present invention, the plurality of pressure sensors and the inertial sensing module (including a wireless transceiver) may be separate or integrated.

[0030] In accordance with an embodiment of the present invention, sensor members 102 may be attached to the legs (feet) of a user. Signals generated by the sensor members 102 and transmitted by a wireless transceiver included therein (including the aforementioned force and motion-related data applied by the feet of the user 108 to the bicycle pedals and cranks) may be received by a wireless receiver (not shown) located on an externally connected computing electronic device 104, which may include a computing device such as a smartphone, laptop, tablet computer, or desktop personal computer.

[0031] In accordance with an embodiment of the present invention, the sensor member 102 includes a plurality of pressure sensors that may be configured to collect force data from the user's feet, such as, for example, the force exerted by the soles of the user's feet against bicycle pedals.

[0032] According to an embodiment of the present invention, the sensor member 102 further includes an inertial sensing module, which is one or more sensors that can be used to measure the position and / or movement of the user's feet. For example, the inertial sensing module may include a gyroscope, an accelerometer (such as a three-axis accelerometer), a magnetometer, an orientation sensor (measuring changes in orientation and / or heading), an angular rate sensor, or a tilt sensor.

[0033] According to an embodiment of the present invention, data related to the cycling behavior of the user 108, such as data related to the force, speed, and acceleration of the user's feet acting on the bicycle pedals, is received by the computing electronic device 104 via wireless transmission to estimate the user's cycling power, which is then uploaded to the cloud server 106 via the Internet for subsequent training and evaluation. The system further includes an application installed on the computing electronic device 104, the application including instructions for transmitting and receiving data between the sensor member 102, the computing electronic device 104 (e.g., a mobile device such as a smartphone or tablet computer), and the cloud server 106. The application may be based on an Android, Windows, or iOS platform, and may upload signals to the cloud server 106 for storage and / or computational processing. The system configuration 100 continuously collects data related to the cycling behavior of the user 108 via the computing electronic device 104 and executes an executable computing program via the computing electronic device 104 to perform, for example, an algorithm for estimating cycling power and / or estimating cycling power / energy expenditure based on the received data related to the user's cycling behavior.

[0034] To explain the sensor member 102 in more detail, as shown in FIG. 2, the sensor member 102 includes multiple pressure sensors and an inertial sensing module and can be installed on the sole of the user's 108. Here, the multiple pressure sensors and the inertial sensing module can be integrated or separated. For convenience of explanation, FIG. 2 illustrates integration of the multiple pressure sensors and the inertial sensing module into an insole 210 as an example of integration of the sensor member 102. Other examples of the sensor member 102 that do not deviate from the spirit of the present invention, such as integration into a shoe or shoe sole, are also within the scope of protection of the present invention. Referring to FIG. 2, the multiple pressure sensors 213a can be installed only in the toe vicinity region 215, the lateral arch region 219, and the heel region 220 of the entire insole. The toe vicinity region 215 corresponds to the toe region and the front sole region. Each of the above regions has multiple pressure sensors 213a, and each pressure sensor is electrically connected to the inertial sensing module 216 using wires 222. In one embodiment, the pressure sensor 213a is a capacitive pressure sensor, and different numbers of multiple capacitive pressure sensors and corresponding wiring 224 form a flexible pressure sensing device that is installed at different locations on the insole 210 to sense foot pressure distribution in different regions of the user's foot (e.g., the aforementioned near-toe region 215, lateral arch region 219, and heel region 220). However, in alternative embodiments, the pressure sensor may be a resistive pressure sensor. Here, the inertial sensing module 216 includes, for example, a wireless transceiver such as a Bluetooth chip, and other electronic components (including an inertial measurement unit and a GPS sensor), all of which are built into the arch pad 214 of the insole 210. In one embodiment, the inertial sensing module 216 may be an electronic sensing module integrated on a printed circuit board with connection terminals electrically connected to the multiple pressure sensing devices.

[0035] According to an embodiment of the present invention, the sensor member 102 can provide relevant data / information during a user's bicycle cycling exercise. In some embodiments, the inertial sensing module 216 of the sensor member 102 can include: (1) a wearable wireless instant motion sensing device or IMU (inertial measurement units); (2) a wearable wireless instant combined multi-region plantar pressure / 6-dimensional motion capture (IMU) device.

[0036] According to an embodiment of the present invention, the inertial sensing module 216 includes at least an accelerometer, a gyroscope, a GPS sensor, etc. Here, the accelerometer and the gyroscope can be sensors manufactured based on Micro-Electro-Mechanical Systems (MEMS) technology, and the accelerometer and the gyroscope can be integrated into a 6-axis accelerometer and gyroscope combined sensor having six degrees of freedom.

[0037] Thus, the exemplary sensor member 102 may be a combined multi-area plantar pressure and six-degree-of-freedom motion detection device. While the user rides the bicycle, the sensor member 102 records the user's foot force data (via multiple pressure sensors) and six-degree-of-freedom motion data (via the inertial sensing module 216).

[0038] The sensor member 102 may include an inertial sensing module 216 that uses a combined sensor of a 6-axis accelerometer and a gyroscope with six degrees of freedom as a six-dimensional motion detection device (also called a six-axis inertial measurement unit), which can be used to detect changes in motion based on a six-degrees-of-freedom Micro-Electro-Mechanical Systems (MEMS) sensor and detect motion-related data such as force data of the user's feet and linear acceleration, angular velocity, etc.

[0039] FIG. 3 illustrates a functional block diagram of the sensor member 102, including an inertial sensing module 216 capable of transmitting and receiving data via a wireless transceiver (TX / RX) 232. While FIG. 2 depicts the wireless transceiver (TX / RX) 232 as integrated into the inertial sensing module 216, those skilled in the art will appreciate that the wireless transceiver (TX / RX) 232 may be a separate, discrete component for transmitting and receiving data. In the example of FIG. 3, the inertial sensing module 216 may include the wireless transceiver (TX / RX) 232 for transmitting data to and / or receiving data from one or more remote systems. In one embodiment, the wireless transceiver 232 may be a low-power, medium- to long-range network device such as a Bluetooth chip, WiFi, RF, Zigbee, narrow-channel IoT (NB-IoT), adaptive network technology (ANT+), or a wireless transceiver with similar functionality, where ANT+ is a transmission protocol common to sports tracking devices. The inertial sensing module 216 can be electrically connected to multiple pressure sensors (pressure sensing device 238) disposed in the insole via connection terminals. The inertial sensing module 216 further includes a processing unit (e.g., one or more microprocessors 234), a memory 235, a composite sensor 216-1 (including an accelerometer and a gyroscope (G-sensor)), a GPS sensor 216-2, and a power supply 237. The power supply 237 can supply power to the pressure sensing device 238 and / or other devices of the sensor member 102 (e.g., the microprocessor 234, the memory 235, the composite sensor 216-1, the GPS sensor 216-2, etc.). In a preferred embodiment, the power supply 237 may include a rechargeable solid-state battery, an induction coil (coupled with an external wireless charging system to wirelessly charge the battery), and a USB charging port.In addition, the sensor member 102 can provide computer programs / algorithms for collecting and storing relevant data during the user's cycling activity (e.g., force data of the user's feet against the bicycle pedals and cranks (via pressure sensors), the user's cycling distance (via GPS sensors), speed / distance, acceleration, angular velocity related data and changes in angular direction (via composite sensors)), and these programs / algorithms can be stored and / or executed.

[0040] Through the wireless transceiver 232, a connection to one or more sensors can be completed, providing additional composite sensors 216-1, GPS sensors 216-2, etc., to detect or provide data or information related to various different parameters. These data or information include physiological data related to the user, such as pressure data (obtained from pressure sensors) of the interaction of the user's feet with the bicycle pedals as the user rides the bicycle, the movement trajectory of the user's feet, acceleration, GPS data, angular velocity-related data and changes in angular orientation (obtained from gyroscope sensors). These data can be stored in memory or transmitted via the wireless transceiver 232 to a remote computing electronic device or server.

[0041] The inertial sensing module 216 may further be configured to communicate with an externally connected computing electronic device 104, which may include a computing device such as a smartphone, laptop, tablet, or desktop computer.

[0042] From the system's perspective, as shown in FIG. 4, a single user 108 uses sensor elements 102 on both legs (feet), one on each leg, e.g., sensor modules (102a, 102b) placed in the left and right insoles, respectively.

[0043] 4 shows a system block diagram in which sensor modules (102a, 102b) communicate with an externally connected computing electronics device 104. Here, the sensor modules (102a, 102b) installed on the feet (e.g., left and right insoles) of a user 108 each include an inertial sensing module (216a, 216b) embedded in the arch of the insole, electrically connected to a pressure sensing device (238a, 238b) to receive and analyze force data, acceleration data, and angular velocity data related to the user's foot acting on a bicycle pedal when riding a bicycle, and transmit the data to a remote computing device or server via a wireless transceiver (232a, 232b) located within the sensing module. Each of the inertial sensing modules (216a, 216b) includes a processing unit (e.g., one or more microprocessors), memory, additional sensors, and a power supply (see FIG. 3).

[0044] The externally coupled computing electronic device 104 may be any electronic device that transmits, processes, and / or stores data. In one embodiment, the externally coupled computing electronic device 104 may be a portable computing device. The portable computing device may be a social networking device, a gaming device, a mobile phone, a smartphone, a personal digital assistant, a digital audio / video player, a laptop computer, a tablet computer, a video game controller, and / or other portable device containing a computing core.

[0045] The externally coupled computing electronics device 104 includes a computing core 342, a user interface 343, an Internet interface 344, a wireless communication transceiver 345, and a storage device 346. The user interface 343 includes one or more input devices (e.g., keyboard, touch screen, voice input device, etc.), one or more audio output devices (e.g., speakers, headphone jack, etc.), and / or one or more visual output devices (e.g., video graphic display, touch screen, etc.). The Internet interface 344 includes one or more network devices (e.g., wireless local area network (WLAN) device, wired LAN device, wireless wide area network (WWAN) device, etc.). The storage device 346 includes a flash memory device, one or more hard disk drives, one or more solid-state (SS) storage devices, and / or cloud storage.

[0046] Computing core 342 includes a processor 342a and other computing core components 342b, which may include a video graphics processing unit, a memory controller, main memory (such as RAM), one or more input / output (I / O) device interface modules, input / output (I / O) interfaces, input / output (I / O) controllers, one or more USB interface modules, one or more network interface modules, one or more memory interface modules, and / or one or more peripheral interface modules.

[0047] The wireless communication transceiver 345 and the wireless transceivers (232a, 232b) of the computing electronic device 104 have similar transceiver types (e.g., Bluetooth, WLAN, Wi-Fi, etc.). The wireless transceivers (232a, 232b) communicate directly with the wireless communication transceiver 345 to share data collected through their respective sensor modules (102a, 102b) and / or receive instructions from the externally connected computing electronic device 104. Additionally or alternatively, the wireless transceivers (232a, 232b) communicate collected data between themselves and one another. The wireless transceivers (232a, 232b) transmit aggregate data to the wireless communication transceiver 345 of the externally coupled computing electronic device 104.

[0048] 5 is an illustration of a path 470 that a bicycle pedal 471 may travel, which may be a circular path about the axis of rotation 475 of a crank 473, or an eccentric path about the axis of rotation 475 of the crank 473. A user's foot exerts a force 480 on the pedal, causing the pedal to move along the path 470. The magnitude and direction of the force 480 on the pedal 471 at any point along the path 470 determines the speed and direction of the pedal 471. The direction of the force 480 can be changed along the path to keep the pedal 471 rotating in the same direction.

[0049] According to an embodiment of the present invention, the bicycle pedal 471 operates in conjunction with the user's foot / shoe when riding, for example, a snap-fit / fixing structure is provided between the dedicated bicycle shoe and the bicycle pedal 471 to prevent relative movement between the two.

[0050] 6 shows an example graph 600 of the change over time of a signal of foot force when pedaling a bicycle received from a pressure sensing device (e.g., multiple pressure sensors 213a installed in the toe vicinity region 215 as shown in FIG. 2). From the graph of the change over time of the signal, a revolution period 610 can be determined as the time length (e.g., time difference) between times corresponding to minimum values ​​of the signal. Furthermore, multiple pressure sensors 213a installed in other regions of the insole, such as the heel region 220 or the lateral arch region 219, generally cannot measure significant changes in the pressure signal while the user is riding a bicycle. Therefore, a threshold value for the change in the pressure signal can be set to effectively filter out pressure signals from other regions than the toe vicinity region 215.

[0051] FIG. 7 illustrates an example graph 700 of the z-direction component of an acceleration signal received from an inertial sensing module. A revolution period 710 can be determined as the length of time (e.g., the time difference) between times corresponding to signal minima. In accordance with an embodiment of the present invention, the revolution period (T rev ) 710 is directly connected to the pedaling rhythm of the pedals, and by calculating the inverse of the period of the z-component of the acceleration signal and multiplying it by 2π, i.e., (2π / Trev), the angular velocity of the bicycle pedal can be estimated.

[0052] According to an embodiment of the present invention, the revolution period and pedal angular velocity obtained via the pedaling force signal (FIG. 6) and acceleration signal (FIG. 7) of a bicycle pedal can be cross-validated with angular velocity data of the bicycle crank measured directly, for example, via a composite sensor.

[0053] Cycling power measures the force a cyclist applies to the pedals and cranks of a bicycle over a portion of a pedal revolution over a given period of time. Many conventional methods can calculate cycling power using simple equations of motion, such as:

number

number

[0054] where W is the work done, P is power, T is torque, ω is angular velocity, F is the force applied to the pedal, θ is the foot angle (the angle of the foot relative to the horizontal axis of the bicycle), r is the length of the crank arm, d is distance, t is time, and v is velocity.

[0055] For example, when calculating cycling power using Equation 1 or Equation 2, the force F applied to the pedals can be determined through the values ​​received from multiple pressure sensors. Using sensor readings from the inertial sensing module (gyroscope), cycling cadence, foot velocity v, and foot angle θ can be determined, and angular velocity ω can be calculated from the cycling cadence.

[0056] In addition, the user's running distance can be provided from data sensed by the GPS sensor.

[0057] Another embodiment, in addition to all of the above features, further includes the following feature, which extends the bicycle cycling power measurement technique described above from calculating power in the first half of a cycle to measuring power over a complete cycling cycle: While the technical features of the above embodiment enable calculation of power in the first half of a cycle (push phase), this embodiment extends the power estimation method to cover the second half of a cycle (pull phase), providing more complete cycling power data.

[0058] This embodiment solves the problem that traditional methods cannot directly measure the tension in the second half of the cycle, and realizes power measurement for the entire cycling cycle. Based on strict physical laws, this embodiment uses verified data from the first half of the cycle and combines it with advanced AI technology, making this embodiment highly reliable. In terms of application value, it provides a more complete cycling performance analysis, helps cyclists optimize their training effect, and improves the competitiveness of the product.

[0059] According to the law of conservation of energy, the total cycling power can be expressed as: P total =P push +P pull where P total is the total power for a complete cycling period, and P push is the first half cycle power (measured in the above embodiment), and P pull is the rear half frequency power (measured in this embodiment).

[0060] Regarding environmental parameter stability, the drag coefficient (including air resistance and rolling resistance) within the same cycling cycle can be considered a constant value within a short period of time, the environmental conditions (such as slope and road friction) are relatively stable, and the changes in system parameters (such as bicycle quality and cyclist posture) are minimal.

[0061] This embodiment includes an AI device 347, which is connected to the computing core 342 to provide an artificial intelligence extension application. This device learns and establishes a correlation model between the power of the first and second laps, adapting to different riding conditions and environmental changes to provide stable and reliable power estimation results. The method of this embodiment can be realized based on the following core principles: Cycling regularity: Because bicycle pedaling motion is highly regular, there is a stable correlation between the first and second laps. Physical stability: Within the same pedaling cycle, the environmental conditions (wind resistance, road conditions, etc.) and riding status remain the same. Energy continuity: Based on the principle of energy conservation, the power conversion between the first and second laps must satisfy the laws of physics. Based on the above principles, the principle of the method for predicting power in the second lap is explained as follows:

[0062] The core of this prediction method is to use known measured data from the first half of the cycle and combine it with an analysis of the physical characteristics of cycling and environmental resistance to accurately estimate power output in the second half of the cycle. In a bicycle pedaling motion, power data from the first half of the cycle (push phase) not only records information about the force exerted by the cyclist, but also the characteristics of the power required to overcome various resistances. By analyzing how power output in the first half of the cycle overcomes environmental factors such as air resistance, rolling resistance, and gravity, these resistance parameters can be accurately calculated.

[0063] These resistances are highly stable and predictable over a short period (approximately 0.5 to 1 second per pedaling cycle), so they can be directly applied to power estimation in the second half of the cycle. At the same time, the power output in the first and second half of the cycle is not independent but closely related. This relationship embodies the continuity of movement and the energy conversion process. When a cyclist completes the first half of the cycle, the musculature, joint angles, and pedal position are all known, and by combining the calculated environmental resistance parameters, the movement characteristics and required power in the second half of the cycle can be effectively predicted.

[0064] Because cycling is a continuous movement, the power conversion between the front and back halves must follow the laws of physics and cannot vary. This provides a basis for reliable prediction. By analyzing large amounts of cycling data, we have discovered that the power ratio between the front and back halves of a cycle when the same cyclist overcomes the same resistance under similar conditions has a stable pattern. Such patterns can be learned and predicted using AI technology, and dynamically adjusted in combination with real-time environmental parameters to achieve highly accurate prediction of back halve power.

[0065] The system takes bicycle sensor data (pressure sensor, IMU, GPS) as input, processes and analyzes it, and then outputs complete cycling power data, including measured power for the first half of the cycle and predicted power for the second half. By integrating multiple sensor data and combining physical models and AI technology, it can accurately estimate the power of the complete pedaling cycle. The specific implementation process involves the following three major steps:

[0066] (1) Data collection for the first half of the cycle: Input data includes pedaling force data from the pressure sensor, angle and motion data from the IMU, position and speed information from the GPS, and environmental sensor parameters. The output results include calibrated pedaling force data, accurate pedaling angle information, and a complete set of environmental parameters. (2) Data analysis and processing: Input data includes pre-processed sensor data, past riding records, and environmental condition information. Output results include cycling pattern characteristics, environmental influence factors, and estimated resistance parameters. (3) Late-cycle prediction: The input data includes the analyzed feature data, real-time environment parameters, and constraints of the physical model. The output results include late-cycle power prediction values, reliability evaluation indexes, and the complete power output curve.

[0067] This method ensures the reliability of prediction results through multiple mechanisms: (1) Physical constraints: Ensures that prediction results comply with the law of conservation of energy, maintains the continuity of the power curve, and complies with physiological limits; (2) Data validation: Compares prediction results with past data to check their rationality and automatically corrects outliers; (3) Real-time optimization: Continuously updates the prediction model to adapt to different riding situations and provide stable and reliable results.

[0068] This prediction method has unexpected benefits and the following advantages: it provides complete cycling power data, estimates power in the second half of the cycle without additional hardware, has the ability to self-learn and optimize, and can be applied to various riding scenarios. The expected application benefits of this invention lie in the technical aspect, which is that it can completely record power output throughout the entire pedaling cycle and provide more accurate cycling data. From a sports science perspective, it can help cyclists understand their overall pedaling pattern, optimize training plans, and provide a unique and complete power measurement solution on the market.

[0069] The above is a preferred embodiment of the present invention. Those skilled in the art should understand that this is used to illustrate the present invention and does not limit the scope of the patent rights claimed by the present invention. The scope of patent protection shall be determined by the appended claims and their equivalent fields. Any changes or modifications made by those skilled in the art without departing from the spirit or scope of this patent shall be considered equivalent changes or designs completed based on the spirit disclosed in the present invention and shall be included in the scope of the following claims. [Explanation of symbols]

[0070] 100 System Configuration 101 Bicycle 102 Sensor member 102a Sensor Module 102b Sensor Module 104 Computing electronic equipment 106 Cloud Server 108 users 210 Insole 213a Pressure Sensor 215 Toe area 216 Inertial Sensing Module 216-1 Composite Sensor 216-2 GPS sensor 216a Inertial Sensing Module 216b Inertial Sensing Module 219 Lateral arch area 220 Heel area 222 Wire 224 Wiring 232 Radio Transceiver 232a radio transceiver 232b radio transceiver 234 microprocessor 235 memory 237 Power supply equipment 238 Pressure Sensing Device 238a Pressure Sensing Device 238b Pressure sensing device 342 computing cores 342a processor 342b Other computing core components 343 User Interface 344 Internet Interface 345 Wireless Communication Transceiver 346 Storage Devices 347 AI device 470 routes 471 Pedals 473 Crank 475 Rotational Axis 480 power 600 Example graph of bicycle pedal force signal change over time 700 Example graph of z-component of acceleration signal 610 rotation period 710 rotation period

Claims

1. a sensor member disposed on a user's foot, the sensor member including a pressure sensing device and an inertial sensing module, configured to collect motion-related data when the user's riding device with pedals performs a cycling motion and to acquire the riding state of the user; computing electronics communicatively coupled to the sensor element to receive the performance-related data, calculate cycling power, and obtain cycling power during the cycling performance; 1. A riding equipment cycling power and state measurement device, comprising:

2. 2. The cycling power and state measurement device for a riding device as described in claim 1, wherein the parameters of the second half of the cycle are estimated from the first half of the cycle, and the power of a complete pedaling cycle is accurately estimated, and the estimation includes data collection and data analysis of the first half of the cycle and prediction of the second half of the cycle.

3. 3. The cycling power and status measuring device for riding equipment as described in claim 2, further comprising an AI device that provides an artificial intelligence application that learns and establishes a correlation model of the power of the first and second laps, adapts to different riding conditions and environmental changes, and provides stable and reliable power estimation results.

4. 2. The cycling power and state measurement device for a riding device of claim 1, wherein the pressure sensing device includes a plurality of pressure sensing devices for sensing the force applied to the pedals from the user's feet, and the inertial sensing module includes an accelerometer, a gyroscope, a GPS sensor, or a combination thereof.

5. 5. The riding cycling power and state measurement device of claim 4, wherein said sensor member further comprises a wireless transceiver used to wirelessly transmit pressure data, acceleration information and GPS information to an external electronic device.

Images