Wearable equipment control system for knee joint injury detection and pre-protection

Abstract

The utility model relates to the technical field of intelligent health protection, in particular to a wearable equipment control system for knee joint injury detection and pre-protection, which comprises a controller, an upper computer, a data transmission module, a signal acquisition module, a wearable module and an electrical stimulation module, and is characterized in that the controller controls the wearable module; the upper computer records, checks and modifies personal information and checks the electric quantity of the wearable module; the data transmission module is used for communication between the controller and an upper computer; the signal acquisition module acquires human knee joint movement conditions; the electrical stimulation module is used for stimulating a human muscle system, the system collects knee joint movement conditions in the movement process in real time through the wearable module, judges whether injury risks exist or not based on a knee joint injury early warning algorithm of a deep learning model, and if the injury risks exceed an injury risk threshold value, gives an alarm. If yes, the electrical stimulation module can automatically apply electrical stimulation to the corresponding muscle position, muscle groups are promoted to contract, knee joint restoration is helped, and knee joint ligament injury is monitored and prevented.

Description

Technical Field

[0001] This utility model relates to the field of intelligent health protection technology, and in particular to a wearable device control system for knee joint injury detection and prevention. Background Technology

[0002] Anterior cruciate ligament (ACL) injury is one of the most common and serious injuries among athletes, with an incidence rate approaching 10% in professional athletes. Following an ACL injury, knee stability is compromised, potentially leading to meniscus tears, cartilage degeneration, and osteoarthritis. Therefore, to maintain knee function and prevent secondary injuries, ACL injury patients typically require ACL reconstruction surgery. In recent years, with the increase in the number of athletes in my country, the number of ACL reconstruction surgeries has risen dramatically, placing a significant burden not only on individual patients but also on society as a whole.

[0003] Given this situation, simply focusing on improving surgical techniques to promote postoperative recovery is far from sufficient; the focus should be shifted to preventing injury before it occurs. If effective measures can be implemented to prevent anterior cruciate ligament (ACL) injuries during exercise, a series of subsequent problems can be avoided. However, currently, apart from educating sports enthusiasts to warm up adequately before exercise, stretch properly, and wear knee braces, there are no more ideal methods or devices that can prevent ACL injuries without hindering the patient's movement. Utility Model Content

[0004] The purpose of this invention is to provide a wearable device control system for knee joint injury detection and prevention, which aims to effectively prevent anterior cruciate ligament injury without affecting normal knee joint movement.

[0005] To achieve the above objectives, this utility model provides a wearable device control system for knee joint injury detection and prevention, including a controller, a host computer, a data transmission module, a signal acquisition module, a wearable module, and an electrical stimulation module, wherein the wearable module is connected to the controller, the host computer, the data transmission module, the signal acquisition module, and the electrical stimulation module, respectively.

[0006] The controller is used to control the wearable module;

[0007] The host computer is used to record, view, and modify personal information, and to check the battery level of the wearable module;

[0008] The data transmission module is used for communication between the controller and the host computer;

[0009] The signal acquisition module is used to collect data on human knee joint movement.

[0010] The electrical stimulation module is used to stimulate the human muscular system;

[0011] The wearable module is used to collect real-time data on knee joint activity during human movement and, based on a knee joint injury early warning algorithm using a deep learning model, determine whether there is a risk of injury.

[0012] The wearable module includes a knee brace, a tension sensor, a processor, a fixator, and a flexible circuit. The knee brace is connected to the tension sensor, the processor, and the flexible circuit, respectively, and the fixator is connected to the tension sensor.

[0013] The knee brace is used to protect the human knee joint;

[0014] The tension sensor is used to measure the anterior displacement and torsion of the tibia;

[0015] The processor is used to collect and analyze data from the tension sensor, communicate with the host computer, and control the electrical stimulation module.

[0016] The retainer is used to fix both ends of the tension sensor;

[0017] The flexible circuit is used for communication and power management between the controller, the tension sensor, and the electrical stimulation module.

[0018] The tension sensor includes an elastic membrane, an elastic element, a tension sensor fixing component, and an elastic sensor circuit interface. The elastic membrane is disposed on one side of the tension sensor fixing component, the elastic element is disposed on one side of the elastic membrane, and the elastic sensor circuit interface is connected to the elastic membrane.

[0019] The controller includes a controller base, a processor mounting bracket, a power supply, a processor, and a controller top. The power supply is fixedly connected to the controller base and is located on one side of the controller base. The processor mounting bracket is fixedly connected to the controller base and is located on one side of the controller base. The processor is fixedly connected to the processor mounting bracket and is located on the side of the processor mounting bracket away from the power supply. The controller top is located on one side of the controller base.

[0020] The fixture includes a fixture base and a fixture nut. The fixture base is located on one side of the tension sensor fixing component, and the fixture nut is located on the other side of the fixture base.

[0021] This invention relates to a wearable device control system for knee joint injury detection and prevention. The controller controls the wearable module and incorporates a deep learning model algorithm, a storage module, and an electrical stimulation trigger module. The deep learning algorithm includes, but is not limited to, support vector machines, long short-term memory networks, and convolutional neural networks. During movement, the controller's control area is characterized by its small size and high processing efficiency. The controller receives real-time changes in forward displacement and torsion transmitted by the wearable module and uses the deep learning model to determine whether there is a risk of ligament injury. If a risk is identified, appropriate electrical stimulation is applied through the electrical stimulation module to promote posterior muscle contraction, thereby aiding in knee joint reduction. This provides feedback and intervention before ligament injury occurs, reducing the risk of injury. The controller integrates a storage module, which includes, but is not limited to, magnetic random access memory, static random access memory, cloud storage, and NAND flash memory. The host computer's functions include recording, viewing, and modifying personal information; checking the wearable device's battery level; viewing, but not limited to, force sensor values, relative position information of the femur and tibia, electrical stimulation intensity, and activation status; and turning the wearable device on and off. Preferably, the host computer can be a mobile electronic device such as a mobile phone or smartwatch. The data transmission module is used for communication between the processor and the host computer. The transmitted information includes, but is not limited to, force sensor values, relative position information of the femur and tibia, electrical stimulation intensity, and activation status. The data transmission module includes, but is not limited to, wireless WIFI and Bluetooth. The signal acquisition module includes, but is not limited to, a force sensor, a digital-to-analog converter, and a signal adjustment unit. It acquires information about human knee joint activity. The electrical stimulation module includes, but is not limited to, a digital-to-analog converter and a drive module. The electrical stimulation module is used to stimulate the human muscular system. The electrical stimulation patch is placed on the posterior muscle position and in contact with the skin. The electrical stimulation module is thin and small.The electrical stimulation is a low-frequency pulsed current that can induce muscle movement or simulate voluntary movement. The intensity, frequency, and mode of the electrical stimulation can be individually adjusted, with an intensity range between 0mA and 60mA and a stimulation frequency range of 1–200Hz. Electrical stimulation modes include, but are not limited to, bidirectional symmetrical square waves and bidirectional asymmetrical square waves. The electrical stimulation module is controlled by the controller and adheres well to the skin. When needed, it releases electrical signals to stimulate the contraction of the posterior thigh muscles to counteract anterior tibial displacement and prevent anterior cruciate ligament injury. The released electrical signal intensity is just enough to stimulate muscle contraction without causing physical damage to the tissue. The controller monitors and controls in real time, effectively detecting and intervening in abnormal anterior tibial displacement during knee joint movement. The system achieves millisecond-level control over the time from signal reception and data analysis to command release and intervention application, effectively preventing ligament injuries. It features rapid processing, low latency, and excellent parallel processing capabilities. During operation, the wearable module collects real-time data on knee joint activity. A deep learning-based knee injury early warning algorithm assesses the risk of injury. If the risk exceeds a threshold, the electrical stimulation module automatically applies electrical stimulation to the corresponding muscle location, inducing muscle contraction to aid knee joint repositioning. This system enables the monitoring and prevention of knee ligament injuries for sports professionals and enthusiasts, reducing the risk of knee injuries. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of this utility model or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this utility model. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a front view of a wearable device for knee joint injury detection and prevention provided by this utility model.

[0024] Figure 2 This is a side view of a wearable device for knee joint injury detection and prevention provided by this utility model.

[0025] Figure 3 This is an exploded view of the controller of a wearable device system for knee joint injury detection and prevention provided by this utility model.

[0026] Figure 4 This is an exploded schematic diagram of the electrical stimulation module of a wearable device system for knee joint injury detection and prevention provided by this utility model.

[0027] Figure 5 This is an exploded view of the fixation device of a wearable device system for knee joint injury detection and prevention provided by this utility model.

[0028] Figure 6 This is an exploded view of the tension sensor in a wearable device system for knee joint injury detection and prevention provided by this utility model.

[0029] Figure 7 This is a connection diagram of a wearable device system for knee joint injury detection and prevention provided by this utility model.

[0030] In the diagram: 1-Electrical stimulation module, 2-Flexible circuit, 3-Controller, 4-Tension sensor data transmission line, 5-Suction cup, 6-Fixer, 7-Tension sensor, 8-Knee pad, 31-Controller base, 32-Charging interface, 33-Tension sensor data transmission line port, 34-Power supply, 35-Processor fixing device, 36-Processor, 37-Controller top, 311-Controller surface and bottom connection device, 312-Power supply recess, 313-Controller base inner wall protrusion, 351-Processor recess, 352- Charging port, 353-Power supply and processor connection hole, 371-Controller face-to-bottom bonding device groove, 81-Outer layer of knee brace, 11-Electrode sheet, 12-Electrode sheet gel, 82-Inner layer of knee brace, 61-Immobilizer lower support, 62-Immobilizer nut, 71-Tension sensor sensing device, 72-Tension sensor fixing piece, 711-Elastic membrane, 712-Elastic element, 713-Elastic sensor circuit interface, 9-Host computer, 91-Data transmission module, 92-Signal acquisition module, 93-Wearable module. Detailed Implementation

[0031] The embodiments of this utility model are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this utility model, and should not be construed as limiting this utility model.

[0032] Please see Figures 1 to 7 This utility model provides a wearable device control system for knee joint injury detection and prevention, including a controller 3, a host computer 9, a data transmission module 91, a signal acquisition module 92, a wearable module 93, and an electrical stimulation module 1. The wearable module 93 is connected to the controller 3, the host computer 9, the data transmission module 91, the signal acquisition module 92, and the electrical stimulation module 1, respectively.

[0033] The controller 3 is used to control the wearable module 93;

[0034] The host computer 9 is used to record, view, and modify personal information, and to check the battery level of the wearable module 93;

[0035] The data transmission module 91 is used for communication between the controller 3 and the host computer 9;

[0036] The signal acquisition module 92 is used to acquire information about human knee joint activity.

[0037] The electrical stimulation module 1 is used to stimulate the human muscular system;

[0038] The wearable module 93 is used to collect real-time data on knee joint activity during human movement and to determine whether there is a risk of injury based on a knee joint injury early warning algorithm using a deep learning model.

[0039] In this embodiment of the invention, the controller 3 is used to control the wearable module 93. It incorporates a deep learning model algorithm, a storage module, and an electrical stimulation trigger module. The deep learning algorithm includes, but is not limited to, support vector machines, long short-term memory networks, and convolutional neural networks. During exercise, the controller 3 receives real-time changes in forward movement and torsion transmitted by the wearable module 93. It uses the deep learning model to determine if there is a risk of ligament injury. If a risk is identified, appropriate electrical stimulation is applied through the electrical stimulation module 1 to promote posterior muscle contraction, thereby aiding in knee joint reduction. This provides feedback and intervention before ligament injury, reducing the risk of damage. The controller 3 integrates a storage module, which includes, but is not limited to, magnetic random access memory, static random access memory, cloud storage, and NAND flash memory. The host computer 9 has the following functions: recording, viewing, and modifying personal information; viewing the battery level of the wearable device; viewing, but not limited to, the values ​​of the tension sensor 7, the relative position information of the femur and tibia, the intensity of electrical stimulation, and the activation status; and turning the wearable device on and off. Preferably, the host computer 9 can be a mobile electronic device such as a mobile phone or smartwatch. The data transmission module 91 is used for communication between the processor 36 and the host computer 9. The transmitted information includes, but is not limited to, the values ​​of the tension sensor 7, the relative position information of the femur and tibia, the intensity of electrical stimulation, and the activation status. The data transmission module 91 includes, but is not limited to, wireless WIFI and Bluetooth. The signal acquisition module 92 includes, but is not limited to, the tension sensor 7, a digital-to-analog converter, and a signal adjustment unit. The signal acquisition module 92 collects information on the human knee joint activity. The electrical stimulation module 1 includes, but is not limited to, a digital-to-analog converter and a drive module. The electrical stimulation module 1 is used to stimulate the human muscular system. The electrical stimulation module 1 is controlled by the controller 3 and adheres well to the skin, releasing power as needed. The electrical signal stimulates the contraction of the posterior thigh muscles to counteract anterior tibial displacement and prevent anterior cruciate ligament injury. The intensity of the released electrical signal is just enough to stimulate muscle contraction without causing physical damage to the tissue. The controller 3 monitors and controls in real time, effectively detecting and intervening in abnormal anterior tibial displacement during knee joint movement. It can control the time from receiving the signal to analyzing the data, releasing the command, and applying the intervention within milliseconds, effectively preventing ligament injury. The system features fast processing capability, low latency, and excellent parallel processing capability. In working mode, the wearable module 93 collects real-time data on knee joint activity during movement. Based on a deep learning model-based knee joint injury early warning algorithm, it determines whether there is an injury risk. If the injury risk threshold is exceeded, the electrical stimulation module 1 automatically applies electrical stimulation to the corresponding muscle position to induce muscle contraction and help the knee joint return to its normal position. This achieves the monitoring and prevention of knee ligament injuries for sports professionals and enthusiasts, reducing the risk of knee joint injury.

[0040] Furthermore, the wearable module 93 includes a knee brace 8, a tension sensor 7, a processor 36, a fixator 6, and a flexible circuit 2. The knee brace 8 is connected to the tension sensor 7, the processor 36, and the flexible circuit 2, respectively, and the fixator 6 is connected to the tension sensor 7.

[0041] The knee brace 8 is used to protect the human knee joint;

[0042] The tension sensor 7 is used to measure the anterior displacement and torsion of the tibia;

[0043] The processor 36 is used to collect and analyze the data from the tension sensor 7, communicate with the host computer 9, and control the electrical stimulation module 1.

[0044] The fixture 6 is used to fix both ends of the tension sensor 7;

[0045] The flexible circuit 2 is used for communication and power management between the controller 3, the tension sensor 7 and the electrical stimulation module 1.

[0046] In this embodiment of the invention, the knee brace 8 serves as a carrier for the intelligent device. To avoid affecting the range of motion of the knee joint, the material at the front of the knee joint is removed from the knee brace 8. The knee brace 8 is made of a highly elastic and lightweight material to protect the human knee joint. The tension sensor 7 is used to measure the anterior displacement and torsion of the tibia. The tension sensor 7 can monitor the changes in the magnitude of anterior displacement during knee joint movement in real time. Through real-time monitoring and feedback, it can effectively identify the occurrence of excessive anterior displacement of the tibia at an early stage and apply appropriate electrical stimulation to provide feedback and intervention before anterior cruciate ligament injury, thereby preventing the occurrence of anterior cruciate ligament rupture. There are a total of 3 sensors. The first sensor basically corresponds to the projection of the anterior cruciate ligament on the body surface, originating from the lateral femoral condyle and inserting into the Gerdy's tubercle or the center of the tibial tuberosity; the second... Two sensors are located on the lateral side of the knee joint, originating from the lateral femoral condyle and ending at the center of the fibular head, to simulate the position of the lateral collateral ligament on the body surface; a third sensor is located on the medial side of the knee joint, originating from the medial femoral condyle and ending at the medial tibial condyle, to simulate the position of the medial collateral ligament on the body surface. The processor 36 collects and analyzes the data from the tension sensor 7, communicates with the host computer 9, and controls the electrical stimulation module 1; the fixator 6 is used to fix both ends of the tension sensor 7. The fixator 6 has the characteristics of small size, stable fixation performance, and can be combined with the knee brace 8 fabric. The flexible circuit 2 is used for communication and power management between the controller 3, the tension sensor 7, and the electrical stimulation module 1. The flexible circuit 2 has the characteristics of high flexibility, softness, and high durability.

[0047] Furthermore, the tension sensor 7 includes an elastic membrane 711, an elastic element 712, a tension sensor fixing member 72, and an elastic sensor circuit interface 713. The elastic membrane 711 is disposed on one side of the tension sensor fixing member 72, the elastic element 712 is disposed on one side of the elastic membrane 711, and the elastic sensor circuit interface 713 is connected to the elastic membrane 711.

[0048] In this embodiment of the invention, to improve the durability of the tensile sensor 7, the sensor has a sandwich structure. Elastic membranes 711 are attached to the top and bottom of the elastic element 712. The elastic sensor circuit interface 713 is located at one end of the elastic membrane 711, and connects the elastic element 712 and the data cable, allowing tensile data to be smoothly transmitted to the processor 36. The type of elastic element 712 includes, but is not limited to, a resistance strain gauge tensile sensor 7, a piezoelectric tensile sensor 7, and a magnetoelastic tensile sensor 7. The elastic membrane 711 has good flexibility, ductility, and chemical stability.

[0049] Furthermore, the controller 3 includes a controller base 31, a processor mounting bracket 35, a power supply 34, a processor 36, and a controller top 37. The power supply 34 is fixedly connected to the controller base 31 and is located on one side of the controller base 31. The processor mounting bracket 35 is fixedly connected to the controller base 31 and is located on one side of the controller base 31. The processor 36 is fixedly connected to the processor mounting bracket 35 and is located on the side of the processor mounting bracket 35 away from the power supply 34. The controller top 37 is located on one side of the controller base 31.

[0050] In this embodiment of the utility model, the controller base 31 has a groove inside, which can accommodate the power supply 34 to be fixed in the controller base 31; the controller base 31 has a protrusion inside, which is used to combine with the processor fixing member 35 to fix the processor fixing member 35; the processor fixing member 35 has a groove to fix the processor 36; the controller base 31 has a protrusion on the outside, and the controller top 37 has a groove to combine the controller base 31 and the controller top 37.

[0051] Furthermore, the fixture 6 includes a fixture base 61 and a fixture nut 62. The fixture base 61 is disposed on one side of the tension sensor fixture 72, and the fixture nut 62 is disposed on one side of the fixture base 61.

[0052] In this embodiment of the utility model, the retainer lower support 61 and the retainer nut 62 are used together to fix the two ends of the tension sensor 7.

[0053] To better understand this technical solution, the following embodiments are provided for further explanation:

[0054] Example 1

[0055] Figure 1 This is a front view structural diagram of a smart wearable device for knee joint injury detection and prevention provided in an embodiment of this application. Figure 2 This is a side view structural diagram of a smart wearable device for knee joint injury detection and prevention provided in an embodiment of this application, as shown below. Figure 1-2 As shown, this embodiment includes an electrical stimulation module 1; a flexible circuit 2; a controller 3; a tension sensing data transmission line 4; a suction cup 5; a fixator 6; a tension sensor 7; and a knee brace 8. The knee brace 8 in this embodiment has two layers of material, with the smart wearable device placed between the two layers to form a sandwich structure. The inner layer of the knee brace 8 has good sweat absorption and wicking capabilities, while the outer layer is a stain-resistant material, giving the knee brace 8 good thermal and moisture comfort and easy cleaning. The upper end of the knee brace 8 is located in the middle of the thigh, and the lower end is located at the lower edge of the tibial tuberosity. The material at the front of the knee joint is removed, so that the knee brace 8 has good coverage without affecting the range of motion of the knee joint. Preferably, the knee brace 8 is made of a highly elastic, thin, and sweat-absorbing material. In this embodiment, three tension sensors 7 are used to measure the anterior displacement and torsion of the tibia. The first sensor corresponds to the projection of the anterior cruciate ligament on the body surface, originating from the lateral femoral condyle and inserting into the Gerdy's tubercle or the center of the tibial tuberosity. The second sensor is located on the lateral side of the knee joint, originating from the lateral femoral condyle and inserting into the center of the fibular head, to simulate the position of the lateral collateral ligament on the body surface. The third sensor is located on the medial side of the knee joint, originating from the medial femoral condyle and inserting into the medial tibial condyle, to simulate the position of the medial collateral ligament on the body surface. The origin and insertion points of each tension sensor 7 are fixed to the corresponding bony landmarks using the fixator 6.

[0056] Example 2

[0057] like Figure 1 and Figure 5As shown, this embodiment contains five fixators 6. Three fixators 6 are located in the lower leg segment, which are attached to the knee brace 8 fabric via suturing or adhesion, serving as the insertion points for the tension sensors 7. The fixators 6 located in the thigh segment, where no fabric is attached to the bony landmarks, are fixed to the bony landmarks on the body surface using suction cups 5 or adhesive, serving as the starting points for the tension sensors 7. From top to bottom, from lateral to medial, the first fixator 6 is located at the lateral femoral condyle, the second fixator 6 is located at the lateral tibial condyle, used to fix the tension sensor corresponding to the lateral collateral ligament; the third sensor is located at the center of the tibial tuberosity, and together with the first sensor, is used to fix the tension sensor corresponding to the anterior cruciate ligament; the fourth and fifth sensors are located at the medial femoral condyle and the medial tibial condyle, respectively, used to fix the tension sensor corresponding to the medial collateral ligament. The fixation device 6, which is combined with the fabric of the knee brace 8, includes a fixation lower support 61 and a fixation nut 62, with the tension sensor fixing member 72 embedded between the two. The fixation lower support 61 is combined with the fabric by stitching or adhesive, and the fixation nut 62 is combined with the fixation lower support 61 by a knob or slot.

[0058] Example 3

[0059] like Figure 1 and Figure 5 As shown, the tensile sensor in this embodiment includes: an elastic membrane 711; an elastic element 712; a tensile sensor fixing component 72; and an elastic sensor circuit interface 713. To improve the durability of the tensile sensor, the sensor as a whole has a sandwich structure, with the elastic element attached to the upper and lower ends of the elastic membrane 711, and the elastic sensor circuit interface 713 located at one end of the elastic membrane 711. The elastic sensor circuit interface 713 and the data transmission line 4 connecting the elastic element 712 and the tensile sensor data enable smooth transmission of tensile data to the processor. The type of elastic element 712 includes, but is not limited to, resistance strain gauge tensile sensors, piezoelectric tensile sensors, and magnetoelastic tensile sensors. The elastic membrane has good flexibility, ductility, and chemical stability. Figure 1 and Figure 4As shown, the electrical stimulation module of this embodiment is placed on the hamstring muscle on the back of the thigh, including an electrode pad 11, an electrode pad gel 12, and the flexible circuit 2. When a risk of damage is detected, the electrode pad discharges. The electrode pad 11 and the flexible circuit 2 are embedded between the inner layer 82 and the outer layer 81 of the knee brace. The inner layer 82 of the knee brace has holes at the corresponding positions of the electrode pad 11 to allow the electrode pad 11 and the electrode pad gel 12 to combine, improve charge injection efficiency, and enhance the electrical stimulation effect of the patch. Preferably, the electrical stimulation module 1 is thin and small; the electrical stimulation is a low-frequency pulsed current that can induce muscle movement or simulate voluntary movement. The intensity, frequency, and mode of the electrical stimulation can be adjusted individually. The released electrical stimulation intensity is just enough to stimulate muscle contraction but will not cause physical damage to the tissue. The intensity range is between 0mA and 60mA, the stimulation frequency range is 1 to 200Hz, and the electrical stimulation mode includes, but is not limited to, bidirectional symmetrical square wave and bidirectional asymmetrical square wave.

[0060] Example 4

[0061] like Figure 1 and Figure 4 As shown, the controller used in this embodiment is sewn or glued to the outer side of the upper part of the knee brace to reduce the impact on movement. It includes: a controller base 31, a charging port 32, a tension sensor data transmission line port 33, a power supply 34, a processor fixing device 35, a processor 36, a controller top 37, a controller surface-to-bottom bonding device 311, a power supply groove 312, an inner wall protrusion 313 of the controller base, a processor groove 351, a charging port 352, and a power supply and processor connection hole 353. The controller base 31 has a power supply groove 312 inside for fixing the power supply 34; the controller base 31 has an inner wall protrusion 313 for fixing the processor fixing device 35. The processor fixing device 35 has a processor groove 351 to fix the processor 36; simultaneously, a charging port 352 and a power supply and processor connection hole 353 are provided at the lower end of the groove 351, wherein the charging port 352 is used for connecting an external power source to the smart wearable device for charging. The controller base 31 has a protrusion on its exterior, and the controller top 37 has a groove to accommodate the controller base 31 and the controller top 37. The controller base 31 and controller top 37 are joined by the controller surface-to-bottom coupling device protrusion 311 screwing into the groove 371. The lower ends of the controller base 31 and controller top 37 are provided with a charging interface 32 and a tension sensor data transmission line port 33 to allow connection to an external power supply 34 and a tension sensor 7. This structure integrates the power supply 34 and the processor 36 to prevent the power supply 34 and processor 36 from shaking during operation.

[0062] The above-disclosed embodiments are merely preferred embodiments of the wearable device control system for knee joint injury detection and prevention of this utility model. Of course, they should not be construed as limiting the scope of this utility model. Those skilled in the art can understand that implementing all or part of the above embodiments and making equivalent changes according to the claims of this utility model still fall within the scope of this utility model.

Claims

1. A wearable device control system for knee joint injury detection and prevention, characterized in that... ； It includes a controller, a host computer, a data transmission module, a signal acquisition module, a wearable module, and an electrical stimulation module, wherein the wearable module is connected to the controller, the host computer, the data transmission module, the signal acquisition module, and the electrical stimulation module, respectively. The controller is used to control the wearable module; The host computer is used to record, view, and modify personal information, and to check the battery level of the wearable module; The data transmission module is used for communication between the controller and the host computer; The signal acquisition module is used to collect data on human knee joint movement. The electrical stimulation module is used to stimulate the human muscular system; The wearable module is used to collect real-time data on knee joint activity during human movement and, based on a knee joint injury early warning algorithm using a deep learning model, determine whether there is a risk of injury.

2. The wearable device control system for knee joint injury detection and prevention as described in claim 1, characterized in that... ； The wearable module includes a knee brace, a tension sensor, a processor, a fixator, and a flexible circuit. The knee brace is connected to the tension sensor, the processor, and the flexible circuit, respectively, and the fixator is connected to the tension sensor. The knee brace is used to protect the human knee joint; The tension sensor is used to measure the anterior displacement and torsion of the tibia; The processor is used to collect and analyze data from the tension sensor, communicate with the host computer, and control the electrical stimulation module. The retainer is used to fix both ends of the tension sensor; The flexible circuit is used for communication and power management between the controller, the tension sensor, and the electrical stimulation module.

3. The wearable device control system for knee joint injury detection and prevention as described in claim 2, characterized in that; The tension sensor includes an elastic membrane, an elastic element, a tension sensor fixing component, and an elastic sensor circuit interface. The elastic membrane is disposed on one side of the tension sensor fixing component, the elastic element is disposed on one side of the elastic membrane, and the elastic sensor circuit interface is connected to the elastic membrane.

4. The wearable device control system for knee joint injury detection and prevention as described in claim 2, characterized in that... ； The controller includes a controller base, a processor mounting bracket, a power supply, a processor, and a controller top. The power supply is fixedly connected to the controller base and is located on one side of the controller base. The processor mounting bracket is fixedly connected to the controller base and is located on one side of the controller base. The processor is fixedly connected to the processor mounting bracket and is located on the side of the processor mounting bracket away from the power supply. The controller top is located on one side of the controller base.

5. The wearable device control system for knee joint injury detection and prevention as described in claim 3, characterized in that... ； The fixture includes a fixture base and a fixture nut. The fixture base is located on one side of the tension sensor fixing component, and the fixture nut is located on the same side as the fixture base.

Images