Wearable basketball shooting hand shape positioning trainer

Abstract

The invention discloses a wearable basketball shooting hand shape positioning trainer which comprises a central control system and a wearable device, and the wearable device comprises a head ring, a chest ring, a glove, an upper arm sleeve and a lower arm sleeve; the finger positions of the glove, the upper arm sleeve and the lower arm sleeve are all provided with motion capture modules, and each motion capture module comprises a plurality of motion sensors and positioning sensors and is used for sensing the hand shape keeping posture in practice; the central control system is used for receiving data information transmitted by the wearable device and transmitting the information to a remote terminal, and comprises a clock module, a reminding module, a database, an action analysis and recognition module and an image acquisition module. Compared with the prior art, the shooting hand shape training system has the advantages of portability, real-time performance, accuracy, individuation, multifunctionality and the like, and a scientific and effective method can be provided for shooting hand shape training of basketball players.

Description

Technical Field

[0001] The present invention relates to the field of shooting training equipment, and specifically refers to a wearable basketball shooting hand gesture positioning trainer. Background Art

[0002] In basketball, the accuracy and stability of the shooting hand gesture play a crucial role in improving the shooting percentage. Traditional basketball shooting training mainly relies on the experience guidance of coaches and the self-perception of athletes, lacking scientific and precise training methods and tools.

[0003] On the one hand, when coaches give on-site guidance, it is often difficult to observe and correct the hand gestures of each athlete in detail and in real time. Due to the limited energy of coaches, they cannot pay attention to the training situations of all athletes simultaneously, which may lead to some subtle hand gesture problems being ignored, affecting the training effect. Moreover, the guidance of coaches is mainly based on subjective experience, lacking objective data support, and it is difficult to make precise adjustments according to the individual needs of different athletes.

[0004] On the other hand, when athletes train by themselves, they usually can only judge whether their hand gestures are correct by feeling, and this method has great uncertainty. Due to the lack of a professional feedback mechanism, it is difficult for athletes to accurately understand the problems with their hand gestures and it is also difficult to make targeted improvements.

[0005] In addition, most of the existing basketball training equipment has a single function and cannot comprehensively position and analyze the shooting hand gesture. Some equipment is bulky and complex to operate, making it inconvenient for athletes to use in daily training. There are also some equipment that can provide certain feedback, but the feedback information is not accurate and timely enough to meet the needs of athletes for efficient training.

[0006] In summary, there is an urgent need in the current market for a wearable training equipment that can accurately and real-time position the basketball shooting hand gesture and provide personalized training suggestions for athletes. Summary of the Invention

[0007] The present invention aims to solve the above technical problems and provides a wearable basketball shooting hand gesture positioning trainer.

[0008] To solve the above technical problems, the technical solution provided by the present invention is: a wearable basketball shooting hand gesture positioning trainer, including a central control system and a wearable device. The wearable device includes a headband, a chest band, gloves, upper arm sleeves, and lower arm sleeves;

[0009] Action capture modules are provided at the finger positions of the gloves, on the upper arm sleeves, and on the lower arm sleeves. The action capture modules include multiple motion sensors and positioning sensors for sensing the postures maintained by the hand gesture during practice;

[0010] Both the chest ring and the head ring adopt an elastic band structure. A heart rate detection device is provided on the chest ring, and a positioning sensor and a micro camera are provided on the head ring.

[0011] Furthermore, the glove includes a half glove and finger sleeves. A glove controller is provided on the back of the half glove. The motion sensor is arranged on the finger sleeves and is connected to the glove controller through a wire. When the glove is worn on a user's hand, the motion sensor is used to detect and obtain gesture parameters, and the positioning sensor is used to detect and obtain and feedback the position parameters of the hand.

[0012] Furthermore, the motion sensors and positioning sensors located on the upper arm sleeve and the lower arm sleeve are arranged on a watch-shaped carrier, and the carrier is fixed on the upper arm sleeve or the lower arm sleeve through an elastic band.

[0013] Furthermore, the motion sensor includes a gesture capture sensor for detecting and obtaining the finger posture parameters of the hand, specifically a bending sensor arranged along the direction of the finger sleeve.

[0014] A gyroscope chip for detecting and obtaining the deflection angle parameters of the hand.

[0015] Furthermore, the glove further includes a limiting device, which is divided into at least one finger mechanism, a palm mechanism and a wrist mechanism, and sleeve rings are respectively provided at the bottom.

[0016] The finger mechanism specifically includes a plurality of finger joints, namely a first joint, a second joint and a third joint, which are sequentially rotationally connected.

[0017] The wrist mechanism is rotationally connected to the palm structure, and a limiting plate is provided at the bottom. The cross section of the limiting plate is in a folding fan structure.

[0018] Furthermore, the rotation angles between the first joint, the second joint and the third joint, and the rotation mechanism between the palm mechanism and the wrist mechanism can be set.

[0019] Furthermore, the central control system is used to receive the data information transmitted by the wearable device, transmit the information to the remote terminal, and includes a clock module and a reminder module.

[0020] It includes a database for storing standard hand gesture action data, historical hand gesture action data and real-time hand gesture actions.

[0021] It includes an action analysis and recognition module for comparing the real-time transmitted hand gesture actions with the hand gesture actions in the database.

[0022] The described wearable device is connected to the central control system and is used to capture training postures and then transmit the collected data information to the central control system.

[0023] It includes an image acquisition module for acquiring image information of the movement from the current position to the target position during the posture capture and extracting image features of the preset hand in the hand posture from the image information.

[0024] The advantages of the present invention compared with the prior art are as follows:

[0025] 1. Portability

[0026] The wearable basketball shooting hand type positioning trainer of the present invention is small in size and light in weight, making it convenient for athletes to carry and use. Training can be carried out anytime and anywhere, without being restricted by the venue and time.

[0027] 2. Real-time performance

[0028] The trainer can collect the hand type data and heart rate data of athletes in real time and transmit the data to the central control system for analysis and processing. Coaches can view the training situation of athletes in real time through the remote terminal, give adjustment suggestions in a timely manner, and improve the training effect.

[0029] 3. Accuracy

[0030] The trainer uses multiple motion sensors and positioning sensors, which can accurately detect the hand type and position information of athletes. At the same time, the image acquisition module can provide more image features, further improving the accuracy of hand type analysis.

[0031] 4. Personalization

[0032] The limiting device can be set according to the hand types and training needs of different athletes to achieve personalized training. At the same time, the database of the central control system can store the historical hand type action data of different athletes, providing a reference for formulating personalized training plans.

[0033] 5. Versatility

[0034] The trainer can not only be used for the positioning training of basketball shooting hand types, but also for the hand movement training of other sports events. In addition, the heart rate detection device can monitor the heart rate changes of athletes in real time, providing a reference for controlling the training intensity.

[0035] In summary, the wearable basketball shooting hand type positioning trainer of the present invention has the advantages of portability, real-time performance, accuracy, personalization and versatility, and can provide a scientific and effective method for the shooting hand type training of basketball players. Description of the Drawings

[0036] Figure 1 It is a schematic structural diagram of a wearable basketball shooting hand - shape positioning trainer of the present invention.

[0037] Figure 2 It is a schematic structural diagram of a wearable basketball shooting hand - shape positioning trainer of the present invention.

[0038] Figure 3 It is a system diagram of a wearable basketball shooting hand - shape positioning trainer of the present invention.

[0039] Figure 4 It is a working flowchart of a wearable basketball shooting hand - shape positioning trainer of the present invention.

[0040] Figure 5 It is a central system setting flowchart of a wearable basketball shooting hand - shape positioning trainer of the present invention.

[0041] Figure 6 It is a data transmission and analysis flowchart of a wearable basketball shooting hand - shape positioning trainer of the present invention.

[0042] As shown in the figure: 1. Wearable device; 101. Head ring; 102. Chest ring; 103. Glove; 1031. Half - glove; 1032. Finger sleeve; 1033. Glove controller; 104. Upper - arm sleeve; 1041. Carrier; 1042. Elastic band; 105. Lower - arm sleeve; 107. Limiting device; 1071. Finger mechanism; 1072. Palm mechanism; 1073. Wrist mechanism; 1074. Limiting plate; 108. Sleeve ring. Specific embodiments

[0043] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, the term "connection" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; for those of ordinary skill in the art, the specific meaning of the above - mentioned terms in the present invention can be understood according to specific situations.

[0045] I. Working principle of the present invention:

[0046] 1. Overall structure

[0047] The wearable basketball shooting hand - shape positioning trainer of the present invention includes a central control system and a wearable device. The wearable device is composed of a head ring, a chest ring, a glove, an upper - arm sleeve and a lower - arm sleeve.

[0048] 2. Details of Wearable Devices

[0049] The headband adopts an elastic band structure, on which a positioning sensor and a micro camera are provided. The positioning sensor can monitor the position and movement state of the head in real time, and the micro camera can capture videos during the training process to provide more information for subsequent analysis.

[0050] The chest band also adopts an elastic band structure, on which a heart rate detection device is provided, which can monitor the heart rate changes of the athlete in real time and provide a reference for controlling the training intensity.

[0051] The glove includes a half glove and finger sleeves. A glove controller is provided on the back of the half glove. Motion sensors are provided on the finger sleeves to detect the posture parameters of the fingers. The motion sensors are connected to the glove controller through wires, and the glove controller can process and transmit the data collected by the motion sensors.

[0052] The motion sensors and positioning sensors on the upper arm sleeve and lower arm sleeve are arranged on a watch-shaped carrier, and the carrier is fixed on the upper arm sleeve or lower arm sleeve through an elastic band. Such a design can ensure that the sensors are closely attached to the arm and improve the accuracy of data collection.

[0053] The positioning sensors on the headband and glove can determine the position information of the head and hand by receiving satellite signals or other positioning signals. The positioning sensors usually adopt technologies such as the Global Positioning System (GPS) and the Beidou Satellite Navigation System; the heart rate detection device on the chest band usually uses a photoelectric sensor or an electrode sensor to detect the heart rate. The photoelectric sensor determines the heart rate by detecting the degree of light absorption by the blood, and the electrode sensor determines the heart rate by detecting the cardiac electrical signal.

[0054] 3. Motion Sensors

[0055] The motion sensor includes a gesture capture sensor and a gyroscope chip. The gesture capture sensor is specifically a bending sensor, which is arranged along the direction of the finger sleeve and obtains the finger posture parameters by detecting the bending degree of the finger sleeve. When the finger bends, the resistance value of the bending sensor changes, and the bending degree of the finger can be determined by measuring the change in the resistance value. The gyroscope chip can detect the deflection angle parameter of the hand and provide more dimensions for the analysis of the hand shape. The gyroscope chip uses the gyroscopic effect, that is, the principle of conservation of angular momentum of a rotating object, to measure the rotation angle of the hand.

[0056] 4. Limiting Device

[0057] The glove further includes a limiting device, which is divided into a finger mechanism, a palm mechanism and a wrist mechanism, and sleeve rings are respectively provided at the bottom. The finger mechanism includes a plurality of finger joints, such as a first joint, a second joint and a third joint, which are sequentially rotatably connected. The wrist mechanism is rotatably connected to the palm structure, and a limiting plate is provided at the bottom. The cross section of the limiting plate is in a folding fan structure.

[0058] The rotation angles between the first joint, the second joint and the third joint, and the rotation mechanism between the palm mechanism and the wrist mechanism can be set to adapt to the hand shapes and training needs of different athletes.

[0059] A motion sensor is provided on the limiting device, which can further improve the accuracy of hand shape detection.

[0060] 5. Central control system

[0061] The central control system is used to receive the data information transmitted by the wearable device and transmit the information to the remote terminal. The data collected by the sensors on the wearable device is transmitted to the central control system through wireless transmission technology. Common wireless transmission technologies include Bluetooth, Wi-Fi, ZigBee, etc. These technologies have the characteristics of low power consumption, high reliability and high-speed transmission, and can meet the data transmission requirements of the trainer.

[0062] After receiving the data transmitted by the wearable device, the central control system first preprocesses and extracts features from the data by the action analysis and recognition module. The preprocessing includes operations such as data filtering and noise reduction to improve the quality of the data. Feature extraction is to extract the features related to the hand shape from the original data, such as the bending angle of the finger, the deflection angle of the hand, the position of the hand, etc.

[0063] The central control system includes a clock module and a reminder module, which can set the training time and reminder method to improve the training efficiency and standardization.

[0064] The central control system also includes a database for storing standard hand shape action data, historical hand shape action data and real-time hand shape actions. The action analysis and recognition module can compare the real-time transmitted hand shape actions with the hand shape actions in the database, so as to judge whether the athlete's hand shape is correct and give corresponding adjustment suggestions.

[0065] The image acquisition module can acquire the image information of moving from the current position to the target position during pose capture, and extract the image features of the preset hand in the hand pose from the image information, providing more references for the analysis of the hand shape. II. Specific implementation manners:

[0067] 1. Wearable device wearing and central control system startup setting

[0068] The athlete adjusts the elastic band of the head ring, wears the head ring, and ensures the normal operation of the positioning sensor and the micro camera; adjusts the elastic band of the chest ring, wears the chest ring, and ensures the normal operation of the heart rate detection device; puts on the gloves, first puts on the half gloves on the hands, and then puts on the finger covers on the fingers, adjusts until the motion sensors are in close contact with the fingers, and adjusts the limit device according to requirements; puts on the upper arm sleeve and the lower arm sleeve on the upper arm and the lower arm respectively, and fixes the watch-shaped carrier through the elastic band, ensuring that the motion sensors and the positioning sensors are in close fit with the arms.

[0069] Connect the power supply and turn on the central control system. Enter the system settings interface, calibrate the time of the clock module, set the parameters of the reminder module (reminder time, reminder method), and confirm the integrity of the database (standard hand gesture action data, historical hand gesture action data, real-time hand gesture action).

[0070] 2. Basketball shooting training actions and data collection

[0071] The athlete performs basketball shooting actions, and the action capture module of the wearable device collects data in real time. At this time, the bending sensor on the finger cover measures the degree of finger bending, and calculates the finger bending angle according to "bending angle = k * (R - R0)"; the gyroscope chip outputs the angular velocity value, and calculates the deflection angle of the hand through the numerical integration method; the positioning sensor monitors the position information of the hand in real time. At the same time, the positioning sensor and the micro camera on the head ring and the heart rate detection device on the chest ring are also working.

[0072] 3. Data transmission and analysis

[0073] The wearable device transmits the collected data to the central control system. The action analysis and recognition module of the central control system preprocesses the data and extracts features.

[0074] For the hand gesture action data, obtain the data vector A = (a1, a2,..., an), where a1 to an respectively represent different hand gesture parameters. Extract the standard hand gesture action data vector B = (b1, b2,..., bn) from the database. Use the Euclidean distance formula "D = √((a1 - b1)^2 + (a2 - b2)^2 +... + (an - bn)^2)" to calculate the difference D between the two, and judge whether the hand gesture meets the standard.

[0075] The image acquisition module obtains the image information during pose capture, extracts image features through steps such as constructing a Gaussian difference pyramid, key point positioning, direction determination, and key point description, and assists in analyzing the hand gesture;

[0076] 4. Judgment and adjustment

[0077] Judge whether it is necessary to adjust the hand shape or device parameters according to the analysis results. If D is greater than a certain threshold, it indicates that the hand shape does not meet the standard, and parameters such as the limit device need to be adjusted, and then return to perform the basketball shooting training action; if D is less than the threshold, continue the training.

[0078] 5. Heart rate monitoring and data transmission

[0079] The heart rate detection device monitors the heart rate in real time and transmits the data to the central control system. The central control system transmits the heart rate data and the hand shape action data to the remote terminal together.

[0080] 6. Viewing at the remote terminal and formulating a training plan

[0081] The coach views the athlete's training data through the remote terminal, including the hand shape action data and the heart rate data. The coach analyzes the data and formulates a personalized training plan, and then transmits the training plan to the central control system. The central control system can set the parameters of the reminder module according to the training plan to remind the athlete to perform the corresponding training.

[0082] The above describes the present invention and its implementation manners. Such description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. All in all, if those of ordinary skill in the art are inspired by it and design similar structural manners and embodiments to this technical solution without creative efforts without departing from the gist of the present invention, they shall fall within the protection scope of the present invention.

Claims

1. A wearable basketball shooting hand gesture positioning trainer, comprising a central control system and a wearable device (1), characterized in that: The described wearable device (1) includes a headband (101), a chest band (102), gloves (103), upper arm sleeves (104), and lower arm sleeves (105); Motion capture modules are provided at the finger positions of the gloves (103), on the upper arm sleeves (104), and on the lower arm sleeves (105). The motion capture modules include multiple motion sensors and positioning sensors for sensing the postures maintained by the hand shape during practice; Both the chest band (102) and the headband (101) adopt an elastic band structure, and a heart rate detection device (1021) is provided on the chest band (102), and a positioning sensor (1012) and a micro camera (1011) are provided on the headband (101).

2. The wearable basketball shooting hand gesture positioning trainer according to claim 1, wherein: The gloves (103) include half gloves (1031) and finger sleeves (1032). A glove controller (1033) is provided on the back of the half gloves (1031). The motion sensors are arranged on the finger sleeves (1032) and are connected to the glove controller (1033) through wires. When the gloves (103) are worn on a user's hand, the motion sensors are used to detect and obtain gesture parameters, and the positioning sensors are used to detect and obtain and feedback the position parameters of the hand.

3. The wearable basketball shooting hand gesture positioning trainer according to claim 2, wherein: The motion sensors and positioning sensors on the upper arm sleeves (104) and the lower arm sleeves (105) are arranged on a watch-shaped carrier (1041), and the carrier (1041) is fixed on the upper arm sleeves (104) or the lower arm sleeves (105) through an elastic band (1042).

4. The wearable basketball shooting hand gesture positioning trainer according to claim 3, characterized in that: The motion sensors include gesture capture sensors for detecting and obtaining the finger posture parameters of the hand, specifically bending sensors arranged along the direction of the finger sleeves (1032) Gyroscope chips for detecting and obtaining the deflection angle parameters of the hand.

5. The wearable basketball shooting hand gesture positioning trainer according to claim 4, characterized in that: The gloves (103) further include a limiting device (107), which is divided into at least one finger mechanism (1071), a palm mechanism (1072), and a wrist mechanism (1073), and sleeve rings (108) are respectively provided at the bottom; The finger mechanism (1071) specifically includes multiple finger joints, namely a first joint, a second joint, and a third joint, which are sequentially rotationally connected; The wrist mechanism (1073) is rotationally connected to the palm structure (1072), and a limiting plate (1074) is provided at the bottom. The cross-section of the limiting plate (1074) is a folding fan structure.

6. A wearable basketball shooting hand gesture positioning trainer according to claim 5, characterized in that: The rotation angles between the first joint, the second joint, and the third joint, and the rotation mechanism between the palm mechanism and the wrist mechanism can be set.

7. The wearable basketball shooting hand gesture positioning trainer according to claim 6, characterized in that: Motion sensors are provided on the limiting device (107).

8. A wearable basketball shooting hand gesture positioning trainer according to any one of claims 1-7, characterized in that: The central control system is used to receive the data information transmitted by the wearable device, transmit the information to the remote terminal, and includes a clock module and a reminder module; It includes a database for storing standard hand shape action data, historical hand shape action data, and real-time hand shape actions; It includes an action analysis and recognition module for comparing the real-time transmitted hand shape actions with the hand shape actions in the database; The described wearable device is connected to the central control system, and is used to capture the training posture and then transmit the collected data information to the central control system. It includes an image acquisition module, which is used to acquire the image information of the movement from the current position to the target position during the posture capture, and extract the image features of the preset hand in the hand posture from the image information.

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