A wearable device control system for knee injury detection and prevention

Abstract

The present invention relates to the technical field of intelligent health protection, and specifically to a wearable device control system for knee joint injury detection and prevention, comprising a controller, a host computer, a data transmission module, a signal acquisition module, a wearable module and an electrical stimulation module, wherein the controller controls the wearable module; the host computer records, checks and modifies personal information, and checks the power level of the wearable module; the data transmission module is used for communication between the controller and the host computer; the signal acquisition module collects the activity of the human knee joint; the electrical stimulation module is used to stimulate the human muscle system, and the system collects the activity of the knee joint in real time during exercise through the wearable module, and judges whether there is an injury risk based on a knee joint injury early warning algorithm of a deep learning model. If the injury risk threshold is exceeded, the electrical stimulation module will automatically apply electrical stimulation to the corresponding muscle position to prompt the muscle group to contract, so as to help the knee joint be repositioned, thereby realizing the monitoring and prevention of knee joint ligament injuries.

Description

Technical Field

[0001] The present invention 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 Art

[0002] Anterior cruciate ligament injury of the knee is one of the most common and serious injuries among athletes, with an incidence rate of nearly 10% among professional athletes. After anterior cruciate ligament injury, the stability of the patient's knee joint is difficult to maintain, which will then cause problems such as meniscus injury, cartilage degeneration and osteoarthritis. Therefore, in order to maintain the patient's knee function and prevent secondary injuries, patients with anterior cruciate ligament injury currently need to undergo anterior cruciate ligament reconstruction surgery. In recent years, with the increase in the number of athletes in my country, the number of anterior cruciate ligament reconstruction surgeries has increased dramatically, which has brought great burdens not only to individual patients but also to the entire society.

[0003] In the face of this situation, it is far from enough to focus only on improving surgical techniques to promote the recovery of postoperative efficacy. The focus should be shifted to before the patient is injured. If there are good measures to prevent patients from suffering anterior cruciate ligament injuries during exercise, a series of subsequent problems can be avoided. However, at present, in addition to educating sports enthusiasts to fully warm up, stretch well, and wear knee braces before exercise, there is no more ideal means or device to prevent anterior cruciate ligament injuries of the knee joint without affecting the patient's exercise. Summary of the invention

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

[0005] To achieve the above-mentioned object, the present invention provides a wearable device control system for knee joint injury detection and prevention, comprising 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 view the power 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 the activity of the human knee joint;

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

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

[0012] Wherein, the wearable module includes a knee pad, a tension sensor, a processor, a fixator and a flexible circuit, the knee pad 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 pad 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 fixer is used to fix the two ends of the tension sensor;

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

[0018] Among them, the tension sensor includes an elastic membrane, an elastic element, a tension sensor fixing part and an elastic sensor circuit interface, the elastic membrane is arranged on one side of the tension sensor fixing part, the elastic element is arranged on one side of the elastic membrane, and the elastic sensor circuit interface is connected to the elastic membrane.

[0019] Wherein, the controller includes a controller base, a processor fixing, 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 fixing 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 fixing and is located on a side of the processor fixing away from the power supply, and the controller top is on one side of the controller base.

[0020] Wherein, the fixer comprises a fixer low support and a fixer nut, the fixer low support is arranged on one side of the tension sensor fixing part, and the fixer nut is arranged on one side of the fixer low support.

[0021] The present invention discloses a wearable device control system for knee joint injury detection and prevention, wherein the controller is used to control the wearable module, and has a built-in deep learning model algorithm, a storage module and an electrical stimulation trigger module, wherein the deep learning algorithm includes but is not limited to a support vector machine, a long short-term memory network, a convolutional neural network, etc.; during exercise, the controller control area has the characteristics of small size and high processing efficiency, the controller receives the changes in forward movement and torsion transmitted by the wearable module in real time, and determines whether there is a risk of ligament injury through a deep learning model. If it is determined that there is a risk, appropriate electrical stimulation is applied through the electrical stimulation module to promote contraction of the posterior group muscles to help reposition the knee joint, provide feedback and intervention before ligament injury, and reduce the risk of injury; the controller integrates a storage module, and the storage module includes but is not limited to a magnetic random access memory, a static random access memory, a cloud storage, a NAND memory, etc. The functions of the host computer include recording, viewing and modifying personal information, viewing the battery power of the wearable device, viewing including but not limited to the value of the tension sensor, the relative position information of the femur and tibia, the intensity of electrical stimulation and the activation status, turning on and off the wearable device, preferably, the host computer can be a mobile electronic device such as a mobile phone and a smart watch; the data transmission module is used for the communication between the processor and the host computer, and the transmitted information includes but is not limited to the value of the tension sensor, the relative position information of the femur and tibia, the intensity of electrical stimulation and the activation status, and 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 tension sensor, a digital / analog converter, and a signal adjustment unit, and the human knee joint activity is collected through the signal acquisition module; the electrical stimulation module includes but is not limited to a digital / analog converter, a driving module, and the electrical stimulation module is used to stimulate the human muscle system, and the electrical stimulation patch is placed in the rear muscle position and contacts the skin. The electrical stimulation module has the characteristics of being thin and small.Electrical stimulation is a low-frequency pulse current that can induce muscle movement or simulate autonomous movement. The intensity, frequency and mode of electrical stimulation can be adjusted individually. The intensity range is between 0mA and 60mA, and the stimulation frequency range is 1-200Hz. The electrical stimulation mode includes but is not limited to bidirectional symmetrical square wave and bidirectional asymmetrical square wave. The electrical stimulation module is controlled by the controller. The electrical stimulation module adheres well to the skin and releases electrical signals in time when needed to stimulate the contraction of the posterior thigh muscles to counteract tibial anterior displacement and prevent anterior cruciate ligament injury. The intensity of the released electrical signal can just stimulate muscle contraction but will not cause physical damage to the tissue. The controller monitors and controls in real time, and can effectively monitor the occurrence of abnormal tibial anterior displacement during knee joint movement and intervene, and can The time for receiving signals-analyzing data-releasing instructions-applying intervention is controlled in milliseconds, which effectively prevents the occurrence of ligament injuries. The system has the characteristics of fast processing capability, low latency and excellent parallel processing capability. The time for receiving signals-analyzing data-releasing instructions-applying intervention is controlled in milliseconds. In the working state, the wearable module can collect the knee joint activity during exercise in real time, and the knee joint injury early warning algorithm based on the deep learning model can be used to determine whether there is an injury risk. If the injury risk threshold is exceeded, the electrical stimulation module will automatically apply electrical stimulation to the corresponding muscle position to prompt the muscle group to contract to help reposition the knee joint, thereby realizing the monitoring and prevention of knee ligament injuries for sports practitioners and enthusiasts and reducing the risk of knee injuries. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 This is a front view of a wearable device for detecting and preventing knee joint injuries provided by the present invention.

[0024] Figure 2 This is a side view of a wearable device for detecting and preventing knee joint injuries provided by the present invention.

[0025] Figure 3 The present invention is a schematic diagram of a controller decomposition of a wearable device system for knee injury detection and prevention provided by the present invention.

[0026] Figure 4 This is a schematic diagram of the decomposition of an electrical stimulation module of a wearable device system for knee injury detection and prevention provided by the present invention.

[0027] Figure 5The present invention is a schematic diagram of a fixator decomposition of a wearable device system for knee injury detection and prevention provided by the present invention.

[0028] Figure 6 It is a schematic diagram of the decomposition of a tension sensor of a wearable device system for knee injury detection and prevention provided by the present invention.

[0029] Figure 7 This is a connection diagram of a wearable device system for knee injury detection and prevention provided by the present invention.

[0030] In the figure: 1-electric stimulation module, 2-flexible circuit, 3-controller, 4-tension sensor data transmission line, 5-suction cup, 6-fixator, 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 combination device, 312-power supply groove, 313-controller base inner wall protrusion, 351-processor groove, 352- Charging port, 353-power supply and processor connection hole, 371-controller surface and bottom combination device groove, 81-knee pad outer layer, 11-electrode sheet, 12-electrode sheet gel, 82-knee pad inner layer, 61-fixer low support, 62-fixer nut, 71-tension sensor sensing device, 72-tension sensor fixing part, 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 DESCRIPTION

[0031] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0032] See also Figures 1 to 7 The present invention provides a wearable device control system for knee joint injury detection and prevention, comprising 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, wherein the wearable module 93 is respectively 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;

[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 view the power 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 collect the activity of the human knee joint;

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

[0038] The wearable module 93 is used to collect the knee joint activity status during human movement in real time, and determine whether there is an injury risk based on the knee joint injury early warning algorithm of the deep learning model.

[0039] In an embodiment of the present invention, the controller 3 is used to control the wearable module 93, and has a built-in deep learning model algorithm, a storage module and an electrical stimulation trigger module, wherein the deep learning algorithm includes but is not limited to a support vector machine, a long short-term memory network, a convolutional neural network, etc.; during exercise, the controller 3 receives the changes in forward movement and torsion transmitted by the wearable module 93 in real time, and determines whether there is a risk of ligament injury through a deep learning model. If it is determined that there is a risk, appropriate electrical stimulation is applied through the electrical stimulation module 1 to promote contraction of the posterior group muscles to help reposition the knee joint, provide feedback and intervention before ligament injury, and reduce the risk of injury; the controller 3 integrates a storage module, and the storage module includes but is not limited to a magnetic random access memory, a static random access memory, a cloud storage, a NAND memory, etc. The functions of the host computer 9 include recording, viewing and modifying personal information, viewing the battery level of the wearable device, viewing including but not limited to the value 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 on and off the wearable device. Preferably, the host computer 9 can be a mobile electronic device such as a mobile phone and a smart watch; the data transmission module 91 is used for communication between the processor 36 and the host computer 9, and the transmitted information includes but is not limited to the value 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 is not limited to wireless WIFI and Bluetooth; the signal acquisition module 92 is not limited to the tension sensor 7, the digital / analog converter, and the signal adjustment unit, and the human knee joint activity is collected through the signal acquisition module 92; the electrical stimulation module 1 includes but is not limited to the digital / analog converter, the driving module, and the electrical stimulation module 1 is used to stimulate the human muscle system. The electrical stimulation module 1 is controlled by the controller 3 and is well attached to the skin, and is released in time when needed. The discharge signal stimulates the contraction of the posterior thigh muscles to counteract the anterior displacement of the tibia and prevent anterior cruciate ligament injury. The intensity of the released electrical signal can just stimulate muscle contraction, but will not cause physical damage to the tissue. The controller 3 monitors and controls in real time, can effectively monitor the occurrence of abnormal anterior displacement of the tibia during knee joint movement and impose intervention, and can control the time of receiving signals-analyzing data-releasing instructions-imposing intervention to milliseconds, effectively preventing the occurrence of ligament injury results. The system has the characteristics of fast processing capability, low latency and excellent parallel processing capability. The time of receiving signals-analyzing data-releasing instructions-imposing intervention is controlled to milliseconds. In the working state, the wearable module 93 can collect the knee joint activity during exercise in real time. The knee joint injury early warning algorithm based on the deep learning model is used to determine whether there is an injury risk. If the injury risk threshold is exceeded, the electrical stimulation module 1 will automatically apply electrical stimulation to the corresponding muscle position to prompt the muscle group to contract to help the knee joint reset, thereby realizing the monitoring and prevention of knee joint ligament injuries for sports practitioners and enthusiasts and reducing the risk of knee joint injuries.

[0040] Further, the wearable module 93 includes a knee pad 8, a tension sensor 7, a processor 36, a fixer 6 and a flexible circuit 2, the knee pad 8 is connected to the tension sensor 7, the processor 36 and the flexible circuit 2 respectively, and the fixer 6 is connected to the tension sensor 7;

[0041] The knee pad 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 of the tension sensor 7, communicate with the host computer 9 and control the electrical stimulation module 1;

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

[0045] The flexible circuit 2 is used for communication among the controller 3 , the tension sensor 7 and the electrical stimulation module 1 and for power supply 34 management.

[0046] In the embodiment of the present invention, the knee pad 8 is used as a carrier of the intelligent device. In order not to affect the range of motion of the knee joint, the knee pad 8 removes the material of the front part of the knee joint. The knee pad 8 is made of highly elastic and thin 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 change of the anterior displacement in real time during the movement of the knee joint. Through real-time monitoring feedback, the excessive anterior displacement of the tibia can be effectively identified at an early stage, and appropriate electrical stimulation can be applied to give feedback and intervention before the anterior cruciate ligament is injured, so as to prevent the occurrence of anterior cruciate ligament rupture. There are three sensors in total. The first sensor is basically consistent with the projection of the anterior cruciate ligament on the body surface, starting from the lateral condyle of the femur and ending at the Gerdy tubercle or the center of the tibial tuberosity on the tibial side; the second A sensor is located on the outside of the knee joint, starting from the lateral condyle of the femur and ending at the center of the head of the fibula, to simulate the position of the lateral collateral ligament on the body surface; the third sensor is located on the inside of the knee joint, starting from the medial condyle of the femur and ending at the medial condyle of the tibia, to simulate the position of the medial collateral ligament on the body surface. The processor 36 collects and analyzes the data of the tension sensor 7, communicates with the host computer 9 and controls the electrical stimulation module 1; the fixer 6 is used to fix the two ends of the tension sensor 7, and the fixer 6 has the performance and characteristics of small size, stable fixing performance, and can be combined with the fabric of the knee pad 8. The flexible circuit 2 is used for communication and power supply 34 management between the controller 3, the tension sensor 7 and the electrical stimulation module 1, and 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 part 72 and an elastic sensor circuit interface 713, the elastic membrane 711 is arranged on one side of the tension sensor fixing part 72, the elastic element 712 is arranged on one side of the elastic membrane 711, and the elastic sensor circuit interface 713 is connected to the elastic membrane 711.

[0048] In the embodiment of the present invention, in order to improve the durability of the tension sensor 7, the sensor as a whole is a sandwich structure, the elastic element 712 is attached with elastic membranes 711 above and below, the elastic sensor circuit interface 713 is located at one end of the elastic membrane 711, and the elastic sensor circuit interface 713 connects the elastic element 712 and the data line, so that the tension data can be smoothly transmitted to the processor 36. The types of the elastic element 712 include but are not limited to the resistance strain type tension sensor 7, the piezoelectric tension sensor 7, and the magnetoelastic tension 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 fixing part 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 fixing part 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 fixing part 35 and is located on a side of the processor fixing part 35 away from the power supply 34, and the controller top 37 is on one side of the controller base 31.

[0050] In the embodiment of the present invention, the controller base 31 is provided with a groove inside to allow the power supply 34 to be fixed on the controller base 31; the controller base 31 is provided with a protrusion inside to be combined with the processor fixing part 35 to fix the processor fixing part 35; the processor fixing part 35 is provided with a groove to fix the processor 36; the controller base 31 is provided with a protrusion outside, and the controller top 37 is provided with a groove to combine the controller base 31 and the controller top 37.

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

[0052] In the embodiment of the present invention, the fixture support 61 and the fixture nut 62 are used together to fix the two ends of the tension sensor 7 .

[0053] In order to better understand the present technical solution, the following embodiments are provided for further explanation:

[0054] Example 1

[0055] Figure 1 This is a schematic diagram of the front view of the structure of the smart wearable device for knee joint injury detection and prevention provided in an embodiment of the present application, Figure 2 A side view structural diagram of a smart wearable device for knee injury detection and prevention provided in an embodiment of the present application, such as Figure 1-2 As shown, the present embodiment includes an electrical stimulation module 1; a flexible circuit 2; a controller 3; a tension sensor data transmission line 4; a suction cup 5; a fixer 6; a tension sensor 7; and a knee pad 8. The knee pad 8 in the present embodiment has two layers of material, and the smart wearable device is placed between the two layers of material to form a sandwich structure. The inner layer material of the knee pad 8 has good perspiration absorption and wicking ability, and the outer layer of the knee pad is a stain resistance material, so that the knee pad 8 has good thermal and moisture comfort and easy cleaning; the upper end of the knee pad 8 is located in the middle of the thigh, and the lower end is located at the lower edge of the tibial tuberosity. The knee pad 8 removes the material of the front part of the knee joint, so that the knee pad 8 has good wrapping without affecting the range of motion of the knee joint; preferably, the knee pad 8 is made of a highly elastic, thin, and perspiration absorbing material. In this embodiment, there are three tension sensors 7 for measuring the anterior displacement and torsion of the tibia. The first sensor is basically consistent with the projection of the anterior cruciate ligament on the body surface, starting from the lateral femoral condyle and ending at the Gerdy tubercle or the center of the tibial tuberosity on the tibial side; the second sensor is located on the outside of the knee joint, starting 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; the third sensor is located on the inside of the knee joint, starting from the medial femoral condyle and ending at the medial tibia condyle to simulate the position of the medial collateral ligament on the body surface. The starting and ending points of the tension sensor 7 are fixed to the corresponding bony landmarks by the fixator 6.

[0056] Example 2

[0057] like Figure 1 and Figure 5As shown, there are five fixators 6 in this embodiment, three of which are located in the calf link, which are combined with the fabric of the knee pad 8 by suturing or adhesion, and are the end points of the tension sensor 7; the fixator 6 located in the thigh link is fixed to the bony landmark point on the body surface by a suction cup 5 or adhesive, because the fabric is not attached to the bony landmark point, and is the starting point of the tension sensor 7. From top to bottom, from outside to inside, the first fixator 6 is located at the lateral condyle of the femur, and the second fixator 6 is located at the lateral condyle of the tibia, which is 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 is used together with the first sensor to fix the tension sensor corresponding to the anterior cruciate ligament; the fourth and fifth sensors are located at the medial condyle of the femur and the medial condyle of the tibia, respectively, and are used to fix the tension sensor corresponding to the medial collateral ligament. The fastener 6 combined with the fabric of the knee pad 8 includes a fastener low support 61 and a fastener nut 62, between which the tension sensor fastener 72 is embedded. The fastener low support 61 is combined with the fabric by sewing or adhesion, and the fastener nut 62 is combined with the fastener low support 61 by a knob or a slot.

[0058] Example 3

[0059] like Figure 1 and Figure 5 As shown, the tension sensor of this embodiment includes: an elastic membrane 711; an elastic element 712; a tension sensor fixing part 72; and an elastic sensor circuit interface 713. In order to improve the durability of the tension sensor, the sensor as a whole is a sandwich structure, the elastic element is attached to the elastic membrane 711 above and below, and the elastic sensor circuit interface 713 is located at one end of the elastic membrane 711. The elastic sensor circuit interface 713, the connecting elastic element 712 and the tension sensor data transmission line 4 enable the tension data to be smoothly transmitted to the processor. The types of the elastic element 712 include but are not limited to resistive strain type tension sensors, piezoelectric tension sensors, and magnetoelastic tension sensors. The elastic membrane has good flexibility, ductility and chemical stability. As Figure 1 and Figure 4As shown, the electrical stimulation module of this embodiment is placed at the biceps femoris position on the back of the thigh, including an electrode sheet 11, an electrode sheet gel 12 and the flexible circuit 2. When the risk of injury is detected, the electrode sheet discharges, and the electrode sheet 11 and the flexible circuit 2 are embedded between the inner layer 82 of the knee pad and the outer layer 81 of the knee pad. The inner layer 82 of the knee pad is provided with holes at the corresponding position of the electrode sheet 11 so that the electrode sheet 11 and the electrode sheet gel 12 can be combined to improve the 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 pulse current that can induce muscle movement or simulate autonomous movement. The intensity, frequency and mode of the electrical stimulation can be adjusted individually. The intensity of the electrical stimulation released can just stimulate muscle contraction, but will not cause physical damage to the tissue. The intensity ranges from 0mA to 60mA, and the stimulation frequency ranges from 1 to 200Hz. The electrical stimulation mode includes but is not limited to bidirectional symmetrical square waves and bidirectional asymmetrical square waves.

[0060] Example 4

[0061] like Figure 1 and Figure 4 As shown, the controller used in this embodiment is sewed or bonded to the outer side of the upper part of the knee pad to reduce the impact on the movement, including: a controller base 31, a charging interface 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 and bottom combination device 311, a power supply groove 312, a controller base inner wall protrusion 313, a processor groove 351, a charging port 352, and a power supply and processor connection hole 353. Among them, the controller base 31 is provided with a power supply groove 312 inside for fixing the power supply 34; the controller base 31 is provided with an inner wall protrusion 313 for fixing the processor fixing device 35. The processor fixing device 35 is provided with a processor groove 351 to fix the processor 36; at the same time, 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 to connect the smart wearable device to an external power supply for charging. The controller base 31 is provided with a protrusion on the outside, and the controller top 37 is provided with a groove to combine the controller base 31 and the controller top 37. The controller base 31 and the controller top 37 are combined in such a way that the controller surface bottom combination device protrusion 311 is screwed into the groove 371. The lower ends of the controller base 31 and the controller top 37 are provided with a charging interface 32 and a tension sensor data transmission line port 33 to allow an external power supply 34 to be connected to the tension sensor 7. Through the above structure, the power supply 34 and the processor 36 are integrated to avoid shaking of the power supply 34 and the processor 36 during movement.

[0062] What is disclosed above is only a preferred embodiment of a wearable device control system for knee injury detection and prevention of the present invention. Of course, this cannot be used to limit the scope of rights of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiments and equivalent changes made in accordance with the claims of the present invention still fall within the scope of the invention.

Claims

1. A wearable device control system for knee 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 view the power 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 the activity of the human knee joint; The electrical stimulation module is used to stimulate the human muscle system; The wearable module is used to collect the knee joint activity status during human movement in real time, and to determine whether there is an injury risk based on the knee joint injury early warning algorithm of the deep learning model.

2. The wearable device control system for knee injury detection and prevention as claimed in claim 1, characterized in that ； The wearable module includes a knee pad, a tension sensor, a processor, a fixator and a flexible circuit, the knee pad is connected to the tension sensor, the processor and the flexible circuit respectively, and the fixator is connected to the tension sensor; The knee pad 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 fixer is used to fix the two ends of the tension sensor; The flexible circuit is used for communication and power management among the controller, the tension sensor and the electrical stimulation module.

3. The wearable device control system for knee injury detection and prevention as claimed in claim 2, characterized in that; The tension sensor includes an elastic membrane, an elastic element, a tension sensor fixing part and an elastic sensor circuit interface. The elastic membrane is arranged on one side of the tension sensor fixing part, the elastic element is arranged 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 injury detection and prevention as claimed in claim 2 is characterized in that ； The controller includes a controller base, a processor fixing, 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 fixing 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 fixing and is located on a side of the processor fixing away from the power supply, and the controller top is on one side of the controller base.

5. The wearable device control system for knee injury detection and prevention as claimed in claim 3 is characterized in that ； The fixer comprises a fixer low support and a fixer nut. The fixer low support is arranged on one side of the tension sensor fixing piece, and the fixer nut is arranged on one side of the fixer low support.

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