Intelligent sports shoes

Abstract

The invention relates to the technical field of sporting goods, and discloses an intelligent sneaker, comprising: a vamp, the bottom of which is provided with a cushion layer used for placing a device; the net surface is arranged on one side of the vamp and is used for improving the air permeability of the shoe; the sole is installed at the bottom of the cushion layer and used for bearing friction generated when the shoe is used; the sensor is embedded in the cushion layer and used for monitoring the running state of a user; the PLC module is embedded in the shoe sole and used for interacting with the APP; the PLC module comprises a sensor module which is used for receiving key motion data of a user monitored by a sensor in real time. Through connection with the mobile phone APP, the exercise data of the user is synchronized to the mobile phone in real time, and the health data management function enables the user to check and analyze the personal exercise data at any time, make a reasonable training plan and carry out timely adjustment according to health changes, so that health management and exercise performance improvement of the user are comprehensively promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of sports goods, in particular to smart sports shoes. Background Art

[0002] Sports shoes are a type of footwear designed for sports activities and casual wear. They are usually lightweight, comfortable and wear-resistant, and are suitable for various sports such as running, basketball, football, fitness, etc. The design of sports shoes includes cushioning functions, support structures and breathable materials to provide good foot protection and comfort. Now, with the increasing attention paid to health and fitness, the use of smart devices has become increasingly popular. Many sports enthusiasts hope to be able to track and analyze their sports data in real time in order to develop a more reasonable training plan, so smart sports shoes have begun to appear.

[0003] However, traditional sports shoe monitoring devices can only provide basic functions and lack effective connection and data synchronization with devices such as smartphones. With the development of mobile application technology, users have an increasing demand for smart devices that can seamlessly connect and synchronize sports data.

[0004] Secondly, during fitness and running, the need for personalized training suggestions is becoming more and more obvious. Different users have different physical conditions, exercise habits and goals, so simple training instructions cannot meet the needs of everyone. Traditional training methods often rely on the coach's experience and lack real-time sports data analysis, resulting in poor training results and even possible sports injuries. Therefore, it is particularly important for smart sports equipment combined with real-time data analysis to provide users with personalized training suggestions;

[0005] Finally, traditional sports monitoring equipment often has too single detection indicators and cannot fully capture the user's sports information. Modern sports equipment has begun to integrate multiple sensors, such as accelerometers, gyroscopes and pressure sensors, in order to accurately monitor key data such as cadence, stride, running efficiency, etc. This precise data tracking can not only help users gain an in-depth understanding of their own exercise status, but also identify unreasonable exercise habits in a timely manner, thereby achieving more effective training optimization. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides smart sports shoes, which solve the problem that traditional smart sports shoes can only provide basic functions and lack effective connection and data synchronization functions with devices such as smart phones.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: smart sports shoes, including:

[0008] The upper has a cushion layer installed at the bottom thereof, and the cushion layer is used to place equipment;

[0009] A mesh surface, which is arranged on one side of the upper and is used to increase the breathability of the shoe;

[0010] The sole is installed at the bottom of the cushion layer and is used to bear the friction when the shoe is in use;

[0011] A sensor embedded in the cushion layer for monitoring the running status of the user;

[0012] The PLC module is embedded inside the sole and is used to interact with the APP.

[0013] Preferably, the PLC module comprises:

[0014] A sensor module, which is used to receive key motion data of the user monitored by the sensor in real time;

[0015] A microprocessing module for analyzing the user's exercise data and generating personalized training suggestions;

[0016] A feedback module, which is used to analyze the user's running posture in real time and provide instant feedback;

[0017] Wireless connection module, which is used to synchronize sports data to the mobile phone.

[0018] Preferably, the key motion data include cadence, stride and running efficiency.

[0019] Preferably, the microprocessing module includes:

[0020] A data storage unit, which is used to cache and store the user's historical motion data and current data;

[0021] Algorithm unit, which is used to implement motion pattern recognition, feature extraction and machine learning models, perform data analysis and generate training suggestions;

[0022] A power management unit, which is used to ensure that the microprocessor maintains a stable power supply during operation;

[0023] The historical motion data and the current data are different sensor data transmitted by the sensor module.

[0024] Preferably, the algorithm unit operation includes the following steps:

[0025] S1. Motion pattern recognition: Receive real-time data from the sensor module, build a standard motion pattern library based on historical motion data, mark the collected data, distinguish different motion patterns, and then use random forest to train the motion pattern;

[0026] S2, Feature extraction: Extract key features from sensor data, divide motion data into multiple time windows, calculate statistical features of each window and transmit them to the APP;

[0027] S3. Machine learning model: The APP uses a regression model to predict continuous variables, such as heart rate and speed. If it recognizes that the user's gait is incorrect or the heart rate is too high, the APP generates corresponding training suggestions, including the following forms:

[0028] Stride length is too short: the APP voice prompts you to increase your stride length to improve efficiency;

[0029] Heart rate exceeds the safe range: APP recommends slowing down and performing appropriate recovery;

[0030] In step S1, the standard motion pattern library is constructed based on the running data of normal running, improper gait, and running under different speeds and terrain conditions. In step S2, the key features include cadence, stride, heart rate, ground contact time, acceleration and gyroscope data, and the statistical features include mean, standard deviation and maximum value.

[0031] Preferably, the feedback module includes:

[0032] A real-time analysis unit, which is used to receive sensor data and analyze the user's running posture;

[0033] A sound feedback unit, which is used to transmit a signal to the APP to issue a prompt;

[0034] The vibration feedback unit is used to provide vibration feedback to remind the user to correct the posture in time.

[0035] Preferably, the vibration feedback may be performed at a frequency and amplitude according to the dangerousness of the posture, specifically:

[0036] Normal posture: no vibration, prompting that no adjustment is required;

[0037] Short and unstable steps: 1Hz to 2Hz low-frequency vibration, prompting you to slightly adjust your steps;

[0038] Improper running: 3Hz~4Hz medium frequency vibration, reminding you to maintain your stride and reduce your speed;

[0039] Danger of running away: 5Hz~6Hz high-frequency vibration, prompting you to slow down immediately, adjust your posture, and take a proper rest.

[0040] Preferably, the wireless connection module includes:

[0041] Bluetooth unit, which is used for short-range wireless communication with the mobile phone APP and real-time transmission of sports data;

[0042] Antenna unit, which is used to enhance the reception and transmission capabilities of wireless signals and ensure the stability of data transmission;

[0043] The data transmission protocol unit is used for data encryption and secure transmission to protect the user's motion data.

[0044] The present invention provides intelligent sports shoes, which have the following beneficial effects:

[0045] 1. The present invention connects with a mobile phone APP to synchronize the user's sports data to the mobile phone in real time. This health data management function enables the user to view and analyze personal sports data at any time, formulate a reasonable training plan, and make timely adjustments based on health changes, thereby comprehensively promoting the user's health management and sports performance improvement.

[0046] 2. Through the built-in microprocessor performance, the smart sports shoes of the present invention can provide personalized training suggestions based on real-time sports data and scientifically improve running performance. In addition, the system instantly analyzes the user's running posture and provides real-time feedback to help the user correct improper movements, effectively reduce the risk of sports injuries, and ensure the safety of training.

[0047] 3. The present invention uses built-in high-precision sensors to monitor key data such as the user's cadence, stride, and running efficiency in real time. This precise data tracking enables the user to have an in-depth understanding of their own exercise status, identify and adjust unreasonable exercise habits in a timely manner, and thus optimize the training effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A perspective view of the present invention;

[0049] Figure 2 It is a structural explosion diagram of the present invention;

[0050] Figure 3 It is a schematic diagram of a PLC module of the present invention;

[0051] Figure 4 is a schematic diagram of a microprocessing module of the present invention;

[0052] Figure 5 It is a schematic diagram of the feedback module of the present invention;

[0053] Figure 6 It is a schematic diagram of the wireless connection module of the present invention.

[0054] Among them, 1. Upper; 2. Cushion; 3. Mesh; 4. Sole; 5. Sensor; 6. PLC module. DETAILED DESCRIPTION

[0055] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] Please see attached Figure 1 -Attached Figure 3 , an embodiment of the present invention provides a smart sports shoe, comprising:

[0057] The upper 1 has a cushion layer 2 installed at the bottom thereof, and the cushion layer 2 is used to place equipment;

[0058] A mesh surface 3, which is arranged on one side of the upper 1 and is used to increase the air permeability of the shoe;

[0059] The sole 4 is mounted on the bottom of the cushion layer 2 and is used to bear the friction when the shoe is in use;

[0060] A sensor 5, which is embedded in the cushion layer 2 and is used to monitor the running status of the user;

[0061] A PLC module 6, which is embedded in the sole 4 and is used to interact with the APP;

[0062] PLC module 6 includes:

[0063] A sensor module, which is used to receive key motion data of the user monitored in real time by the sensor 5;

[0064] A microprocessing module for analyzing the user's exercise data and generating personalized training suggestions;

[0065] A feedback module, which is used to analyze the user's running posture in real time and provide instant feedback;

[0066] Wireless connection module, which is used to synchronize sports data to the mobile phone.

[0067] Specifically, the user first puts on the shoes and downloads and installs the corresponding APP on the mobile phone to complete the initial settings, including registering user information and setting exercise goals. When starting to run, the sensor module in the shoe monitors key exercise data in real time, such as cadence, stride, ground contact time and heart rate, and transmits these data to the PLC module embedded in the sole. Under the action of the microprocessor module, these data are analyzed to identify the user's movement pattern and stride characteristics, thereby generating personalized training suggestions. For example, if it is detected that the user's stride is too short, the system will suggest "increasing the stride to improve efficiency". At the same time, the feedback module analyzes the user's running posture in real time. If an improper posture is found, it will provide sound suggestions. The PLC module synchronizes the processed data and suggestions to the user's mobile phone APP through the wireless connection module. The user can view detailed real-time data and historical records. After running, the APP will generate a training report including the total number of steps, total distance, average step frequency and heart rate, as well as a summary and improvement suggestions based on the user's performance to help users adjust their future training plans. Users can also record their personal training experience and feedback in the APP. This information will be used to optimize subsequent training suggestions to make them more personalized. Through this modular design, smart sports shoes not only enhance the user's sports experience, but also provide them with scientific and effective training guidance and feedback.

[0068] Please see attached Figure 4 , key sports data include cadence, stride length and running efficiency;

[0069] The microprocessor module includes:

[0070] A data storage unit, which is used to cache and store the user's historical motion data and current data;

[0071] Algorithm unit, which is used to implement motion pattern recognition, feature extraction and machine learning models, perform data analysis and generate training suggestions;

[0072] A power management unit, which is used to ensure that the microprocessor maintains a stable power supply during operation;

[0073] Both historical motion data and current data are different sensor data transmitted by the sensor module;

[0074] The algorithm unit operation includes the following steps:

[0075] S1. Motion pattern recognition: Receive real-time data from the sensor module, build a standard motion pattern library based on historical motion data, mark the collected data, distinguish different motion patterns, and then use random forest to train the motion pattern;

[0076] S2, Feature extraction: Extract key features from sensor data, divide motion data into multiple time windows, calculate statistical features of each window and transmit them to the APP;

[0077] S3. Machine learning model: The APP uses a regression model to predict continuous variables, such as heart rate and speed. If it recognizes that the user's gait is incorrect or the heart rate is too high, the APP generates corresponding training suggestions, including the following forms:

[0078] Stride length is too short: the APP voice prompts you to increase your stride length to improve efficiency;

[0079] Heart rate exceeds the safe range: APP recommends slowing down and performing appropriate recovery;

[0080] In step S1, the standard motion pattern library is constructed based on the running data of normal running, improper gait, and running under different speeds and terrain conditions. In step S2, the key features include cadence, stride, heart rate, ground contact time, acceleration and gyroscope data, and the statistical features include mean, standard deviation and maximum value.

[0081] Specifically, in the microprocessor module of the smart sports shoes, the operation and coordination process between each unit is realized through efficient data flow and analysis. First, the data storage unit caches the motion data from the sensor module in real time to ensure fast access and processing. When the user starts exercising, the algorithm unit receives these real-time data, starts motion pattern recognition, compares the data with historical records, builds a standard motion pattern library, and trains the model through the random forest algorithm to identify different motion patterns; then, it enters the feature extraction step, the algorithm unit extracts key features from the sensor data, divides the motion data into multiple time windows, calculates statistical features and transmits them to the APP, these features provide a basis for subsequent data analysis; during the operation of the machine learning model, the algorithm unit uses the extracted features for regression analysis to predict heart rate and speed. If it detects that the user's gait is incorrect or the heart rate is abnormal, the APP will generate corresponding training suggestions and directly feedback to the user. This series of steps ensures seamless connection between the data storage unit, the algorithm unit and the APP, thereby realizing real-time feedback and personalized training guidance, and improving the user's sports performance and safety.

[0082] Please see attached Figure 5 -Attached Figure 6 , the feedback module includes:

[0083] A real-time analysis unit, which is used to receive sensor data and analyze the user's running posture;

[0084] A sound feedback unit, which is used to transmit a signal to the APP to issue a prompt;

[0085] A vibration feedback unit, which is used to provide vibration feedback to remind the user to correct the posture in time;

[0086] The vibration feedback can be adjusted according to the frequency of the amplitude based on the dangerousness of the posture, specifically:

[0087] Normal posture: no vibration, prompting that no adjustment is required;

[0088] Short and unstable steps: 1Hz to 2Hz low-frequency vibration, prompting you to slightly adjust your steps;

[0089] Improper running: 3Hz~4Hz medium frequency vibration, reminding you to maintain your stride and reduce your speed;

[0090] Danger of running: 5Hz~6Hz high-frequency vibration, prompting you to slow down immediately, adjust your posture, and take a proper rest;

[0091] The wireless connection module includes:

[0092] Bluetooth unit, which is used for short-range wireless communication with the mobile phone APP and real-time transmission of sports data;

[0093] Antenna unit, which is used to enhance the reception and transmission capabilities of wireless signals and ensure the stability of data transmission;

[0094] The data transmission protocol unit is used for data encryption and secure transmission to protect the user's motion data.

[0095] Specifically, the real-time analysis unit receives data from sensors, which include the user's gait, posture and movement status. The unit analyzes this data in real time to identify the user's running posture and determine whether it is normal according to the set standards. Specifically, the system evaluates the extracted key features (such as cadence, stride, ground contact time and center of gravity change) through the trained machine learning model. If the stride is lower than the set value (such as 30 cm), it is marked as "too short stride"; if the ankle rotation angle exceeds the normal range (such as more than 15 degrees), it is evaluated as "improper posture". When it is identified that the user's running posture is abnormal, the feedback module will activate the corresponding feedback mechanism according to the analysis results; if the user's running posture is normal, the system will not issue any vibration or sound prompts. If it is detected that the user's steps are short and unstable, the sound feedback unit will emit low-frequency vibrations (1Hz~2Hz) through the APP and prompt the user to "slightly adjust the pace." ", if the analysis results show that the user's running posture is improper, the feedback module will provide medium-frequency vibration (3Hz~4Hz) and issue a prompt through the APP, suggesting that the user "pay attention to maintaining the stride and reduce the speed". In the most serious case, if the user's running posture is judged to be dangerous, the vibration feedback unit will generate high-frequency vibration (5Hz~6Hz) and issue a warning, prompting the user to "slow down immediately, adjust the posture, and take a proper rest"; in order to achieve these feedbacks, the Bluetooth unit of the wireless connection module is responsible for short-range wireless communication with the mobile phone APP, real-time transmission of motion data and feedback information, the antenna unit ensures the stability of the wireless signal, so that the data can be transmitted in a timely and reliable manner, at the same time, the data transmission protocol is responsible for encrypting and securely transmitting the motion data to protect the user's personal privacy. Through the cooperation of this series of units, the feedback module of the smart sports shoes can effectively monitor and correct the user's running posture and improve the safety and effectiveness of exercise.

[0096] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. Smart sports shoes, characterized in that: include: A shoe upper (1), the bottom of which is provided with a cushion layer (2), wherein the cushion layer (2) is used for placing equipment; A mesh surface (3) is arranged on one side of the upper (1) and is used to increase the air permeability of the shoe; A sole (4) mounted on the bottom of the cushion layer (2) and used to bear the friction when the shoe is in use; A sensor (5) is embedded in the cushion layer (2) and is used to monitor the running status of the user; The PLC module (6) is embedded in the sole (4) and is used for interacting with the APP.

2. The smart sports shoes according to claim 1, characterized in that: The PLC module (6) comprises: A sensor module, which is used to receive key motion data of a user monitored in real time by a sensor (5); A microprocessing module for analyzing the user's exercise data and generating personalized training suggestions; A feedback module, which is used to analyze the user's running posture in real time and provide instant feedback; Wireless connection module, which is used to synchronize sports data to the mobile phone.

3. The smart sports shoes according to claim 2, characterized in that: The key sports data include cadence, stride length and running efficiency.

4. The smart sports shoes according to claim 2, characterized in that: The microprocessing module comprises: A data storage unit, which is used to cache and store the user's historical motion data and current data; Algorithm unit, which is used to implement motion pattern recognition, feature extraction and machine learning models, perform data analysis and generate training suggestions; A power management unit, which is used to ensure that the microprocessor maintains a stable power supply during operation; The historical motion data and the current data are different sensor data transmitted by the sensor module.

5. The smart sports shoes according to claim 4, characterized in that: The operation of the algorithm unit includes the following steps: S1. Motion pattern recognition: Receive real-time data from the sensor module, build a standard motion pattern library based on historical motion data, mark the collected data, distinguish different motion patterns, and then use random forest to train the motion pattern; S2, Feature extraction: Extract key features from sensor data, divide motion data into multiple time windows, calculate statistical features of each window and transmit them to the APP; S3. Machine learning model: The APP uses a regression model to predict continuous variables, such as heart rate and speed. If it recognizes that the user's gait is incorrect or the heart rate is too high, the APP generates corresponding training suggestions, including the following forms: Stride length is too short: the APP voice prompts you to increase your stride length to improve efficiency; Heart rate exceeds the safe range: APP recommends slowing down and performing appropriate recovery; In step S1, the standard motion pattern library is constructed based on the running data of normal running, improper gait, and running under different speeds and terrain conditions. In step S2, the key features include cadence, stride, heart rate, ground contact time, acceleration and gyroscope data, and the statistical features include mean, standard deviation and maximum value.

6. The smart sports shoes according to claim 2, characterized in that: The feedback module comprises: A real-time analysis unit, which is used to receive sensor data and analyze the user's running posture; A sound feedback unit, which is used to transmit a signal to the APP to issue a prompt; The vibration feedback unit is used to provide vibration feedback to remind the user to correct the posture in time.

7. The smart sports shoes according to claim 6, characterized in that: The vibration feedback can be performed at an amplitude and frequency according to the dangerousness of the posture, specifically: Normal posture: no vibration, prompting that no adjustment is required; Short and unstable steps: 1Hz to 2Hz low-frequency vibration, prompting you to slightly adjust your steps; Improper running: 3Hz~4Hz medium frequency vibration, reminding you to maintain your stride and reduce your speed; Danger of running away: 5Hz~6Hz high-frequency vibration prompts you to slow down immediately, adjust your posture, and take a proper rest.

8. The smart sports shoes according to claim 2, characterized in that: The wireless connection module comprises: Bluetooth unit, which is used for short-range wireless communication with the mobile phone APP and real-time transmission of sports data; Antenna unit, which is used to enhance the reception and transmission capabilities of wireless signals and ensure the stability of data transmission; The data transmission protocol unit is used for data encryption and secure transmission to protect the user's motion data.

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