Measuring device for riding power and state of riding device and cloud system

Abstract

The invention relates to a device for measuring the riding power and state of a riding device, and the device comprises a sensor assembly which is disposed at the foot part of a user, comprises a pressure sensing device and an inertia sensing module, and is configured to collect the motion related data of the user when the riding device with a pedal carries out the riding motion; and a computing electronic device communicatively coupled to the sensor assembly, the computing electronic device receiving the motion-related data when the user performs the riding motion and executing an algorithm related to estimating the riding power according to the motion-related data to estimate the riding power when the user performs the riding motion.

Description

Technical Field

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

[0002] Cycling is a very common sport. With the development of cycling, more and more professional road cycling activities are taking place. In order to measure the pressure of bicycle pedals, a pressure measuring device is needed to measure the pressure of bicycle pedals and ultimately measure the athlete's force characteristics to achieve the optimal force mode.

[0003] During cycling, the cyclist performs an alternating pedaling motion on the bicycle with their legs, which generates an alternating rotational motion of the two cranks operated by the pedals about an axis.

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

[0005] Cycling performance metrics include cycling power, which is the time spent independently cycling a given route. Cycling power is a measure of the power applied by the cyclist to the bicycle. Cycling power measures the force applied by the rider to the bicycle's pedals and cranks over a period of time. Cycling power is a measure that is somewhat independent of road conditions, weather conditions, and altitude variations, making it a useful statistic for optimizing and comparing both amateur and professional riders.

[0006] Because cycling power is a measure of the force applied to the pedals and cranks, power is conventionally measured either at the pedals or at the cranks.

[0007] A bicycle power meter is an instrument that measures a cyclist's cycling power output (in watts). As a training aid, such a power meter can provide the rider with feedback about their exertion. If the power is lower than this value, the rider can increase the power by speeding up the pedaling or shifting to a higher gear. The power is usually displayed on a main control unit mounted on the handlebars of the bicycle. There must be a wireless connection between the power meter and the device that calculates and displays the power.

[0008] However, due to the aforementioned measurement methods, current cycling power measurements mostly rely on collecting data from the chainring, pedals, hubs, and other locations to calculate power. However, these instruments are somewhat difficult to install, often requiring additional tools to disassemble the chainring or pedals for measurement, making them quite inconvenient. Summary of the Invention

[0009] In order to improve the above-mentioned deficiencies, according to one aspect of the present invention, a device for measuring the cycling power and status of a cycling device is proposed. The device includes: a sensor component, disposed on the foot of a user, comprising a pressure sensing device and an inertial sensing module, configured to collect motion-related data of the user when performing a cycling motion on a cycling device having pedals, for obtaining the user's cycling status; and a computing electronic device, communicatively coupled to the sensor component, which receives the motion-related data of the user when performing the above-mentioned cycling motion and executes an algorithm related to estimating cycling power based on the data to estimate the user's cycling power when performing the cycling motion.

[0010] In one embodiment, the riding device with pedals includes a bicycle.

[0011] In one embodiment, the riding motion includes performing alternating pedaling motions on the pedal device, and the user's foot maintains consistent movement with the pedal device.

[0012] In one embodiment, the pressure sensing device includes a plurality of pressure sensing devices for sensing the force applied by the user's foot to the pedal device; the inertial sensing module includes a composite sensor combining an accelerometer and a gyroscope; and the inertial sensing module further includes a GPS sensor.

[0013] In one embodiment, the sensor assembly further includes: a microprocessor for collecting and analyzing electronic signals detected by the pressure sensing device, the inertial sensing module, and the GPS sensor, and converting the electronic signals 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 for storing the pressure data, the acceleration information, and the GPS information; a wireless transceiver coupled to the microprocessor for wirelessly transmitting the pressure data, the acceleration information, and the GPS information to an external electronic device; and a power supply device for supplying power to the pressure sensing device, the inertial sensing module, the GPS sensor, the microprocessor, the memory, and the wireless data transmission / reception device.

[0014] In one embodiment, the wireless transceiver is a Bluetooth or WiFi device.

[0015] In one embodiment, the data sensed by the GPS sensor can provide the user's riding distance.

[0016] In one embodiment, the aforementioned exercise-related data during cycling includes: determining the force applied to the pedals via the values ​​received by each of the multiple pressure sensors in the pressure sensing device; and determining the user's cycling cadence, the speed of the user's foot, and the angle of the user's foot via the sensor readings of the inertial sensing module.

[0017] According to another aspect of the present invention, a cloud-based system for measuring the cycling power and status of a cycling device is provided. The cloud-based system includes: a device for measuring the cycling power and status of the cycling device; a cloud-based server communicatively coupled to the computing electronic device for receiving exercise-related data and the cycling power of the user when performing a cycling exercise, uploaded by the computing electronic device; the exercise-related data and the cycling power can be shared with a third-party connected fitness application via the cloud-based server. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The system architecture of a device for measuring cycling power and status of a cycling device is shown.

[0019] Figure 2 A schematic diagram showing the distribution and wiring of the pressure sensors according to the present invention.

[0020] Figure 3 FIG. 1 is a functional block diagram of a sensor component according to an embodiment of the present invention.

[0021] Figure 4 A system block diagram showing communication between a sensor module and an externally coupled computing electronic device.

[0022] Figure 5 A diagram showing the path that a bicycle's pedals can travel.

[0023] Figure 6 An example graph showing how a signal received from a pressure sensing device, indicating the force of a foot pressing a bicycle pedal, varies over time.

[0024] Figure 7 A diagram showing an example of the z-component of the acceleration signal received from an inertial sensing module.

[0025]

Explanation of symbols

[0026] 100: System Architecture

[0027] 101: Bicycle

[0028] 102: Sensor component

[0029] (102a, 102b): Sensor module

[0030] 104: Electronic computing device

[0031] 106: Cloud Server

[0032] 108: User

[0033] 210: Insole

[0034] 213a: Pressure sensor

[0035] 215: Near the toe area

[0036] 216: Inertial sensing module

[0037] 216-1: Composite Sensor

[0038] 216-2: GPS sensor

[0039] (216a, 216b): Inertial sensing module

[0040] 219: Lateral arch area

[0041] 220: Heel area

[0042] 222: Wire

[0043] 224: Wiring

[0044] 232: Wireless transceiver

[0045] (232a, 232b): Wireless transceiver

[0046] 234: Microprocessor

[0047] 235: Memory

[0048] 237: Power supply device

[0049] 238: Pressure sensing device

[0050] (238a, 238b): Pressure sensing device

[0051] 342: Computing Core

[0052] 342a: Processor

[0053] 342b: Other computing core components

[0054] 343: User Interface

[0055] 344: Internet Interface

[0056] 345: Wireless communication transceiver

[0057] 346: Storage device

[0058] 347: AI device

[0059] 470: Path

[0060] 471: Pedal

[0061] 473: Crank

[0062] 475: Rotation axis

[0063] 480: Strength

[0064] 600: Example graph showing how the force signal from a bicycle pedal changes over time

[0065] 700: Example diagram of the z-direction component of the acceleration signal

[0066] 610,710: rotation period DETAILED DESCRIPTION

[0067] The present invention will be described in detail herein with respect to specific embodiments of the invention and its viewpoints. Such description is for explaining the structure or step flow of the present invention, which is for illustrative purposes only and is not intended to limit the scope of the patent application of the present invention. Therefore, in addition to the specific embodiments and preferred embodiments in the specification, the present invention can also be widely implemented in other different embodiments. The following describes the implementation of the present invention by means of specific specific embodiments, and people familiar with this technology can easily understand the efficacy and advantages of the present invention through the contents disclosed in this specification. The present invention can also be used and implemented through other specific embodiments, and the various details described in this specification can also be applied based on different needs, and various modifications or changes can be made without departing from the spirit of the present invention.

[0068] The present invention provides a cycling power and status measuring device for a cycling device, particularly for measuring the power consumption of a cyclist during cycling, and providing feedback information about the cyclist's exercise volume for training effect evaluation.

[0069] Determining a user's cycling power can provide important motion and activity data. Knowledge of cycling power can be very useful for various cycling-related applications, such as sports training, professional training, and recreational cycling.

[0070] For example, an athlete cycling uphill may want to cycle at a speed that maintains the same power they would on flat ground. If the user cycles uphill at a speed that exceeds their flat ground power, they may fatigue faster and may not be able to perform at their maximum capacity for the same extended period of time.

[0071] Feedback on the user's cycling power can allow the user to optimize their training to achieve the maximum training effect. For example, cycling power provides the user with an instant quantification of work efficiency, which can be used for specific training techniques, such as interval training.

[0072] The user's cycling power feedback can also be integrated and shared with third-party connected fitness applications through a cloud system, such as a cloud server, to allow users to interact with these systems.

[0073] The systems and devices described herein can determine a user's mechanical cycling power using multiple sensors located on the user's feet. The systems and devices can use sensors attached to or located within a wearable device or cycling equipment to measure and monitor data related to the user's movements or activities. The measurement data from the sensors can be used to calculate mechanical cycling power and to determine the user's cycling status.

[0074] Based on the above concepts, reference Figure 1 , which shows a system architecture 100 for a device for measuring cycling power and status of the aforementioned cycling device, including a sensor assembly 102, a computing electronic device 104, and a cloud server 106. The sensor assembly 102 is communicatively connected to the computing electronic device 104, which can receive data collected by the sensor assembly 102. The computing electronic device 104 is communicatively connected to the cloud server 106 via the Internet, for uploading the user's cycling exercise-related data and the cycling power to the cloud server 106.

[0075] According to an embodiment of the present invention, sensor assembly 102 includes a wireless transceiver configured to wirelessly transmit data collected by sensor assembly 102 regarding the force, acceleration, and motion of user 108's foot applied to bicycle pedals while riding bicycle 101 to a signal receiver of an externally coupled computing electronic device 104. As discussed in more detail below, sensor assembly 102 can be worn on user 108's foot, such as on a shoe or sole of user 108, and includes a plurality of pressure sensors and an inertial sensor module (including a wireless transceiver). According to an embodiment of the present invention, the plurality of pressure sensors and (including the wireless transceiver) can be separate or integrated.

[0076] According to an embodiment of the present invention, the sensor assembly 102 can be worn on both feet of a user. Signals generated by the sensor assembly 102 and transmitted by the wireless transceiver therein (including the aforementioned data related to the force applied by the user 108's foot to the bicycle pedals and the cranks and movement) can be received by a radio receiver (not shown) disposed on an externally coupled computing electronic device 104, which can include a computing device such as a smartphone, laptop, tablet, or personal computer.

[0077] According to an embodiment of the present invention, the sensor assembly 102 may include a plurality of pressure sensors, which may be configured to collect force data from the user's feet, such as the force exerted by the user's feet on a bicycle pedal.

[0078] According to an embodiment of the present invention, the sensor assembly 102 further includes an inertial sensing module, which may include one or more sensors for measuring the position and / or movement of the user's foot. For example, the inertial sensing module may include a gyroscope, an accelerometer (e.g., a three-axis accelerometer), a magnetometer, an orientation sensor (for measuring orientation and / or changes in orientation), an angular velocity sensor, or a tilt sensor.

[0079] According to an embodiment of the present invention, the aforementioned data related to user 108's cycling performance, such as data related to the force, speed, and acceleration of the user's foot on the bicycle pedals, can be wirelessly received by computing device 104 to estimate the user's cycling power. This data can then be uploaded to cloud server 106 via a network for subsequent training and evaluation. The system also includes an application installed on computing device 104, which includes instructions for sending and receiving data between sensor assembly 102, computing device 104 (e.g., a mobile device such as a smartphone or tablet), and cloud server 106. The application can be based on Android, Windows, or iOS platforms, and can also upload signals to cloud server 106 for storage and / or computational processing. The system architecture 100 can continuously collect data related to user 108's cycling performance via computing device 104, and execute executable algorithms on computing device 104 to, for example, execute algorithms related to estimating cycling power and estimate cycling power / energy expenditure based on the received data related to the user's cycling performance.

[0080] To describe the sensor assembly 102 in detail, Figure 2 As shown, the sensor assembly 102 includes a plurality of pressure sensors and an inertial sensing module, which can be installed on the sole of the user 108. The plurality of pressure sensors and the inertial sensing module can be integrated or separated. Figure 2 Only an example of integrating multiple pressure sensors and inertial sensing modules in the sensor assembly 102 is shown, such as integration into the insole 210. Other examples of the sensor assembly 102 that do not depart from the spirit of the present invention, such as integration into shoes or soles, also fall within the scope of protection of the present invention. Figure 2Multiple pressure sensors 213a can be installed only in the toe area 215, the lateral arch area 219, and the heel area 220 of the entire insole. The toe area 215 corresponds to the toe area and the forefoot area. Each of the above areas has multiple pressure sensors 213a, and each pressure sensor is electrically connected to the inertial sensing module 216 via a wire 222. In one embodiment, the pressure sensors 213a are capacitive pressure sensors, wherein different numbers of multiple capacitive pressure sensors and corresponding wiring 224 form a flexible pressure sensing device, which is installed in different parts of the insole 210 to sense the foot pressure distribution in different areas of the user's foot (for example, the aforementioned toe area 215, the lateral arch area 219, and the heel area 220). However, according to alternative embodiments, the pressure sensors can also be resistive pressure sensors. The inertial sensing module 216, including a wireless transceiver such as a Bluetooth chip, and other electronic components (including an inertial measurement unit and a GPS sensor), is entirely embedded within the arch support 214 located in the arch portion of the insole 210. In one embodiment, the inertial sensing module 216 can be an electronic sensing module integrated on a printed circuit board (PCB) having connection terminals electrically connected to the multiple pressure sensing devices.

[0081] According to an embodiment of the present invention, the sensor assembly 102 can provide relevant data / information about the user's cycling. In some embodiments, the inertial sensing module 216 in the sensor assembly 102 can include (1) a wearable wireless real-time motion sensing device or an IMU (inertial measurement unit), or (2) a wearable wireless real-time combined multi-zone plantar pressure / six-dimensional motion capture (IMU) device.

[0082] According to an embodiment of the present invention, the inertial sensing module 216 includes at least an accelerometer, a gyroscope, a GPS sensor, and other devices. The accelerometer and gyroscope can be sensors manufactured using micro-electro-mechanical systems (MEMS) technology. The accelerometer and gyroscope can be integrated into a composite sensor comprising a six-axis accelerometer and gyroscope with six degrees of freedom.

[0083] Therefore, the exemplary sensor assembly 102 can be a combined multi-zone plantar pressure / six-degree-of-freedom motion detection device. When a user is riding a bicycle, the sensor assembly 102 records the user's foot force data (via multiple pressure sensors) and six-degree-of-freedom motion data (via inertial sensing module 216).

[0084] The sensor assembly 102 may include an inertial sensing module 216, which uses a composite sensor consisting of a six-axis accelerometer and a gyroscope with six degrees of freedom as a six-dimensional motion detection device (or a six-axis inertial measurement device). The device is based on a six-degree-of-freedom micro-electro-mechanical system (MEMS) sensor to detect motion changes and can be used to detect the user's foot force data as well as motion-related data such as linear acceleration and angular velocity.

[0085] Figure 3 The functional block diagram of the sensor assembly 102 is shown, which includes an inertial sensing module 216 capable of data transmission / reception via a wireless transceiver (TX / RX) 232. Figure 2 The wireless transceiver (TX / RX) 232 is shown as being integrated into the inertial sensing module 216, but those skilled in the art will appreciate that the wireless transceiver (TX / RX) 232 may also be used as a separate component for data transmission / reception purposes. Figure 3In an example, the inertial sensing module 216 may include a wireless transceiver (TX / RX) 232 for transmitting data to one or more remote systems 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 networking device such as a Bluetooth chip, WiFi, RF, Zigbee, narrow channel IOT (NB-IOT), ANT+ (adaptive network technology), or a wireless transceiver with similar functions. ANT+ is a common transmission protocol for sports tracking devices. The inertial sensing module 216 can be electrically connected to multiple pressure sensors (pressure sensing device 238) provided on the insole via a connection terminal. The inertial sensing module 216 also includes a processing device (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 device 237. The power supply 237 can power the pressure sensing device 238 and / or other devices of the sensor assembly 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 includes a rechargeable solid-state battery, an inductive coil (for coupling with an external wireless charging system to wirelessly charge the battery), and a USB charging port. It should be understood that the sensor assembly 102 can provide computer programs / algorithms to collect and store data related to the user's bicycle riding (e.g., data on the user's foot force on the bicycle pedals and cranks (via the pressure sensor), the user's riding distance (via the GPS sensor), speed / distance, acceleration, angular velocity data, and angular orientation changes (via the composite sensor)), and these programs / algorithms can be stored and / or executed.

[0086] The wireless transceiver 232 can connect to one or more sensors and provide additional composite sensors 216-1, GPS sensors 216-2, etc. for detecting or providing data or information related to various parameters. Such data or information includes physiological data related to the user, including pressure data of the user's foot interacting with the bicycle pedals while riding a bicycle (obtained by the pressure sensor), the movement trajectory of the user's foot, acceleration, GPS data, angular velocity data, and angular orientation changes (obtained by the gyroscope sensor). Such data can be stored in a memory or transmitted to a remote computing device or server via the wireless transceiver 232.

[0087] The inertial sensing module 216 may also be configured to communicate with an externally coupled computing electronic device 104 , which may include a computing device such as a smartphone, laptop, tablet, or personal computer.

[0088] From a system perspective, Figure 4 As shown, a single user 108 uses two foot sensor assemblies 102, one for each foot, such as sensor modules (102a, 102b) disposed on the left and right insoles, respectively.

[0089] Figure 4 A system block diagram showing the communication between the sensor modules (102a, 102b) and the externally coupled computing electronic device 104. The sensor modules (102a, 102b) provided on the foot of the user 108 (e.g., the left and right insoles) each include an inertial sensing module (216a, 216b) embedded in the arch of the insole and electrically connected to a pressure sensing device (238a, 238b) for receiving and analyzing the force data, acceleration and angular velocity data of the user's foot on the bicycle pedal when riding a bicycle, and transmitting the above data to a remote computing device or server via a wireless transceiver (232a, 232b) located in the sensing module. The above inertial sensing modules (216a, 216b) each include a processing device (e.g., one or more microprocessors), a memory, additional sensors, and a power supply device (see Figure 3 ).

[0090] The externally coupled computing electronic device 104 is any electronic device capable of transmitting, processing, and / or storing data. In one embodiment, the externally coupled computing electronic device 104 is 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, a tablet computer, a video game console, and / or any other portable device that includes a computing core.

[0091] The externally coupled computing electronics 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., a keyboard, a touch screen, a voice input device, etc.), one or more audio output devices (e.g., a speaker, a headphone jack, etc.), and / or one or more visual output devices (e.g., a video graphics display, a touch screen, etc.). The internet interface 344 includes one or more networking devices (e.g., a wireless local area network (WLAN) device, a wired LAN device, a 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.

[0092] The computing core 342 includes a processor 342a and other computing core components 342b. Other computing core components 342b include a video graphics processing unit, a memory controller, main memory (e.g., RAM), one or more input / output (I / O) device interface modules, an input / output (I / O) interface, an input / output (I / O) controller, a peripheral device interface, one or more USB interface modules, one or more network interface modules, one or more memory interface modules, and / or one or more peripheral device interface modules.

[0093] The wireless communication transceiver 345 of the computing electronic device 104 and the wireless transceivers (232a, 232b) of the sensor modules (102a, 102b) 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 by their respective sensor modules (102a, 102b) and / or receive instructions from the externally coupled computing device 104. In addition or as an alternative, the wireless transceivers (232a, 232b) communicate the collected data between them and one of them. The wireless transceivers (232a, 232b) transmit the collective data to the wireless communication transceiver 345 of the externally coupled computing electronic device 104.

[0094] refer to Figure 5 , which shows a schematic diagram of a path 470 that a pedal 471 of a bicycle can travel, which can be a circular path around the rotation axis 475 of a crank 473 or an eccentric path around the rotation axis 475 of the crank 473. A user's foot applying a force 480 against the pedal can cause the pedal to move along the path 470. The magnitude and direction of the force 480 against the pedal 471 at any location along the path 470 can determine the speed and direction of the pedal 471. To keep the pedal 471 rotating in the same direction, the direction of the force 480 can change along the path.

[0095] According to an embodiment of the present invention, the bicycle pedals 471 move in unison with the user's feet / shoes during riding. For example, a locking / fixing structure is provided between the professional bicycle shoes and the bicycle pedals 471 to prevent relative movement between the two.

[0096] Figure 6 Displays the data from the pressure sensing device (e.g. Figure 2 An example graph 600 is shown showing how signals representing the force of a foot pressing a bicycle pedal, received by multiple pressure sensors 213a located near the toe area 215, vary over time. From this graph of signal variations over time, a revolution period 610 can be determined as the duration (e.g., the time difference) between times corresponding to signal minimums. Furthermore, since pressure sensors 213a located in other areas of the insole, such as the heel area 220 or the lateral arch area 219, are generally unable to measure significant pressure signal changes during a user's bicycle riding, a pressure signal change threshold can be set to effectively filter out pressure signals outside of the toe area 215.

[0097] Figure 7 An example graph 700 shows the z-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. According to an embodiment of the present invention, a revolution period (T rev )710 is directly linked to the pedaling rhythm by calculating the inverse of the period of the z-direction component of the acceleration signal and multiplying it by 2π, i.e. (2π / T rev ), the angular velocity of the bicycle pedals can be estimated.

[0098] According to an embodiment of the present invention, the force signal of the foot stepping on the bicycle pedal ( Figure 6 ) and acceleration signal ( Figure 7 ) and the angular velocity of the pedals can be cross-validated with, for example, the angular velocity data of the bicycle crank measured directly by a composite sensor.

[0099] Cycling power is a measure of the force a rider applies to the pedals and cranks of a bicycle over a portion of the pedal's rotation over a time interval. Many existing methods can calculate cycling power using simple motion equations, such as:

[0100] P=T×ω=F×sinθ×r×ω

[0101] Mathematical formula 1

[0102]

[0103] Where W is work done, P is power, T is torque, ω is angular velocity, F is the force applied to the pedal, θ is the angle of the foot (the angle of the foot relative to the horizontal axis of the bicycle), r is the length of the crank arm, d is the distance, t is time, and v is velocity.

[0104] For example, if one wishes to calculate cycling power using Equation 1 or 2, the force F applied to the pedals can be determined by the values ​​received from each of the multiple pressure sensors. The cycling cadence, foot velocity v, and foot angle θ can be determined using sensor readings from the inertial sensing module (gyroscope), where the angular velocity ω can be calculated from the cycling cadence.

[0105] In addition, the data sensed by the GPS sensor can provide the user's riding distance.

[0106] In another embodiment, in addition to all of the above features, the following additional features are included: This embodiment expands the aforementioned cycling power measurement technology from calculating power during the first half of a lap to measuring power during the entire cycling cycle. While the aforementioned technical features successfully implement power calculations for the first half of a lap (the Push Phase), this embodiment further expands the power estimation method to include the second half of a lap (the Pull Phase), thereby providing more complete cycling power data.

[0107] This embodiment addresses the inability of traditional methods to directly measure the pulling force in the second half of a lap, enabling power measurement throughout the entire cycling cycle. This implementation, based on strict physical laws, utilizes verified data from the first half of a lap, and incorporates advanced AI technology, resulting in superior reliability. In terms of application value, it provides more complete cycling performance analysis, helps riders optimize their training, and enhances product competitiveness.

[0108] According to the law of conservation of energy, the total power of cycling can be expressed as:

[0109] P total =P push +P pull

[0110] in:

[0111] P total : Total power for a complete cycling cycle

[0112] P push : Power in the first half of the cycle (measured by the above embodiment)

[0113] P pull : Power in the second half of the cycle (measured in this embodiment)

[0114] In terms of environmental parameter stability, the resistance coefficient (including air resistance and rolling resistance) can be regarded as a constant in a short period of time during the same riding cycle, environmental conditions (such as slope and road friction) remain relatively stable, and system parameters (such as bicycle mass and rider posture) change slightly.

[0115] This embodiment includes an AI device 347, which is connected to the computing core 342 and provides an artificial intelligence expansion application, so as to learn and establish a correlation model of the power of the front and rear half circles, adapt to different riding conditions and environmental changes, so as to provide stable and reliable power estimation results. The method of this embodiment can be implemented based on the following core principles: riding regularity: the pedaling action of a bicycle is highly regular, so that there is a stable correlation between the front and rear half circles; physical stability: within the same pedaling cycle, environmental conditions (such as wind resistance, road conditions) and riding status are maintained; energy continuity: based on the principle of conservation of energy, the power conversion between the front and rear half circles must satisfy the laws of physics. Based on the above principles, the principle of the power prediction method for the second half circle is explained as follows:

[0116] The core of this embodiment's prediction method lies in accurately estimating the power of the second half of a lap using known measured data from the first half of a lap, combined with the physical characteristics of cycling and analysis of environmental resistance. During cycling, power data from the first half of a lap (the Push Phase) not only captures the rider's applied force but also captures the power characteristics required to overcome various resistances. By analyzing how the power of the first half of a lap overcomes environmental factors such as air resistance, rolling resistance, and gravity, we can accurately calculate these resistance parameters.

[0117] Because these resistances are highly stable and predictable over a short period of time (approximately 0.5-1 second per pedaling cycle), they can be directly applied to power estimation for the second half of the cycle. Furthermore, the power outputs of the first and second half of the cycle are not independent but closely correlated. This correlation is reflected in the continuity of movement and the energy conversion process: when the rider completes the first half of the cycle, their muscle tissue, joint angles, and pedal position are all in a known state. Combined with the calculated environmental resistance parameters, we can effectively predict the motion characteristics and power requirements of the second half of the cycle.

[0118] Because cycling is a continuous motion, the power conversion between the first and second half of a lap must adhere to the laws of physics and avoid sudden changes. This provides a reliable basis for prediction. By analyzing extensive cycling data, we've discovered that the power ratio between the first and second half of a lap for the same rider, under similar conditions and overcoming the same resistance, exhibits a stable pattern. This pattern can be learned and predicted using AI technology, dynamically adjusted based on real-time environmental parameters, and thus achieve highly accurate power prediction for the second half of a lap.

[0119] The system uses sensor data (pressure sensor, IMU, GPS) on the bicycle as input. After processing and analysis, it outputs complete cycling power data, including the measured power in the first half of the lap and the predicted power in the second half. By integrating data from multiple sensors, combining physical models and AI technology, it can accurately estimate the power of the entire pedaling cycle. The specific implementation process includes three main stages:

[0120] (1) Data collection for the first half of the lap: Input data includes: pedaling force data from the pressure sensor, angle and motion data from the IMU, GPS position and speed information, and environmental sensor parameters. Output results include: calibrated pedaling force data, accurate pedaling angle information, and a complete set of environmental parameters.

[0121] (2) Data analysis and processing: Input data includes: sensor data processed in the previous stage, historical riding records, and environmental condition information. Output results include: riding mode characteristics, environmental impact factors, and resistance parameter estimates.

[0122] (3) Second half cycle prediction: Input data includes: analyzed characteristic data, real-time environmental parameters, and physical model constraints. Output results include: second half cycle power prediction value, reliability assessment indicator, and complete power output curve.

[0123] This method ensures the reliability of prediction results through multiple mechanisms: such as (1) physical constraints: ensuring that the prediction results comply with energy conservation, maintain the continuity of the power curve, and comply with physiological limitations; (2) data verification: comparing with historical data to check the rationality of the prediction results and automatically correct outliers; (3) real-time optimization: continuously updating the prediction model, adapting to different riding situations, and providing stable and reliable results.

[0124] This prediction method offers unexpected benefits and the following advantages: it provides complete cycling power data, enabling second-half lap power estimation without the need for additional hardware, and possesses self-learning and optimization capabilities, making it applicable to a variety of riding scenarios. The anticipated benefits of this invention lie in its ability to fully record power output throughout the entire pedaling cycle, providing more accurate cycling data. In sports science, it can help understand a rider's complete pedaling pattern, optimize training plans, and offer a uniquely complete power measurement solution on the market.

[0125] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment, it is not intended to limit the present invention. Any technician familiar with the present profession can make some changes or modifications to equivalent embodiments of the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A device for measuring the riding power and state of a riding device, characterized in that: include: a sensor assembly, disposed on a user's foot, comprising a pressure sensing device and an inertial sensing module, configured to collect motion-related data of the user while performing a cycling motion on a cycling device having pedals, for obtaining the user's cycling status; A computing electronic device is communicatively coupled to the sensor assembly. The computing electronic device receives the motion-related data and calculates the cycling power accordingly to obtain the cycling power during the cycling motion.

2. The device for measuring the riding power and state of a riding device according to claim 1, characterized in that: The parameters of the second half of the lap are estimated based on the first half of the lap to accurately estimate the power of the complete pedaling cycle. This includes data collection, data analysis and processing for the first half of the lap; and prediction for the second half of the lap.

3. The device for measuring riding power and state of a riding device according to claim 2, characterized in that: The AI ​​device provides artificial intelligence applications to learn and establish a correlation model between the power of the first half of the lap and the second half of the lap, adapting to different riding conditions and environmental changes to provide stable and reliable power estimation results.

4. The device for measuring riding power and state of a riding device according to claim 3, characterized in that: The pressure sensing device includes a plurality of pressure sensing devices for sensing the force applied by the foot of the user on the pedal.

5. The device for measuring riding power and state of a riding device according to claim 3, characterized in that: The inertial sensing module mentioned above includes an accelerometer, a gyroscope, a GPS sensor or a combination thereof.

6. The device for measuring riding power and state of a riding device according to claim 4 or 5, characterized in that: The sensor assembly further includes: a microprocessor for collecting and analyzing electronic signals detected by the pressure sensing device and the inertial sensing module, and converting the electronic signals 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, for storing the pressure data, the acceleration information, and the GPS information; and The wireless transceiver is coupled to the microprocessor and is used for wirelessly transmitting the pressure data, the acceleration information and the GPS information to an external electronic device.

7. The device for measuring riding power and state of a riding device according to claim 6, characterized in that: The wireless transceiver is a Bluetooth, WiFi or ANT+ device.

8. The device for measuring riding power and state of a riding device according to claim 6, wherein: The GPS information is used to provide the user's riding distance.

9. The device for measuring riding power and status of a riding device according to claim 1, wherein: The aforementioned exercise-related data during cycling includes: Determining the force applied by the user on the pedal via the values ​​of each pressure sensor received by the plurality of pressure sensors in the pressure sensing device; The user's riding cadence, speed and angle of the user's foot are determined by reading the sensors of the inertial sensing module.

10. A cloud system for cycling power and status of a cycling device, characterized in that: include: A device for measuring cycling power and status of a cycling device according to any one of claims 1 to 9; a cloud server communicatively coupled to the computing electronic device and configured to receive the exercise-related data and the cycling power of the user during cycling uploaded by the computing electronic device; The above-mentioned exercise-related data and cycling power can be shared with third-party connected fitness applications through the cloud server.

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