A dynamic and static dual-mode knitted sensor, a preparation method and a remote control operation control system

Abstract

The application discloses a dynamic-static dual-mode knitted sensor, a preparation method and a remote control operation control system, relates to the technical field of flexible wearable sensing, and the method comprises the following steps: the dynamic-static dual-mode knitted sensor is a plating flat-knitted fabric structure, and comprises a friction sensing part and a tensile resistance sensing part integrated in the same fabric; the friction sensing part is formed by plating knitting of core-spun yarn A and yarn B; the core-spun yarn A and the yarn B respectively constitute the front and back of the plating flat-knitted fabric structure; the friction sensing part is used for outputting a triboelectric dynamic signal when the plating flat-knitted fabric structure is bent, contacted, separated or rubbed, so as to represent dynamic change information in the process of joint movement; the tensile resistance sensing part is composed of core-spun yarn C; the core-spun yarn C is parallelly inserted into a preset deformation region of the friction sensing part; and the tensile resistance sensing part is used for outputting a resistance change static signal when the plating flat-knitted fabric structure is bent and deformed and keeps a posture, so as to represent the static bending angle of the joint.

Description

Technical Field

[0001] This application relates to the field of flexible wearable sensing technology, and in particular to a dynamic and static dual-mode knitted sensor, its preparation method, and a remote control operation and control system. Background Technology

[0002] With the development of virtual reality, human-computer interaction, and robot remote control technologies, the demand for accurate and continuous monitoring of human movement is increasing, especially in capturing complex movements of joints such as fingers, elbows, and knees. This places higher demands on the flexibility, fit, and comfort of sensors. Compared to traditional rigid sensors, knitted electronic fabrics are soft, breathable, stretchable, and easily conform to the curves of the human body, making them suitable for wearable motion monitoring devices and possessing the potential for long-term stable wear.

[0003] Human joint movements typically involve both dynamic changes and static pauses. Therefore, sensors used for joint monitoring need to be able to sense not only rapid bending and extension movements but also to stably characterize the bending state when the joint is at rest. Existing flexible sensors with single sensing mechanisms often struggle to meet both of these monitoring requirements. For example, triboelectric sensors are sensitive to dynamic stimuli such as contact, separation, sliding, and rapid deformation, making them suitable for dynamic motion detection. However, when the joint is stationary, their output signal decays rapidly, making it difficult to accurately reflect the static bending angle. Tensile-resistance sensors can stably characterize the degree of joint bending through changes in resistance, making them suitable for static state detection. However, they are prone to response lag during rapid movements, making it difficult to accurately reflect the speed of motion changes. Thus, it is evident that a single sensing mechanism cannot fully record the complex movement process of human joints.

[0004] To achieve coordinated monitoring of dynamic and static states, existing technologies typically employ methods such as splicing, stitching, or layering different sensor components to construct a dual-modal sensing system. However, such approaches often compromise the integrity of the fabric, increase device thickness, and reduce the fabric's softness and tensile properties, thereby affecting wearability. Furthermore, additional friction or interlayer interference may occur between multi-layer structures, leading to decreased accuracy of the sensing signal and hindering long-term stable monitoring.

[0005] Added-yarn knitting structures can organize different functional yarns on both sides of a single-layer fabric, achieving material partitioning without the need for multiple layers. This helps maintain the fabric's lightness, softness, and stretchability, while reducing interference between different functional materials. Therefore, how to provide a dual-modal knitted sensor based on added-yarn knitting structures that integrates dynamic and static sensing functions within the same fabric, while also possessing good softness and stretchability, has become a pressing technical problem to be solved in this field. Summary of the Invention

[0006] The purpose of this application is to provide a dynamic and static dual-mode knitting sensor, its preparation method, and a remote control operation system, which can simultaneously achieve the coordinated output of dynamic and static signals within a single layer of knitted fabric, thereby providing a more complete characterization of complex joint motion processes.

[0007] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a dynamic and static dual-mode knitting sensor, which is a plain knitted fabric structure with added yarn and includes a friction sensing part and a tension and resistance sensing part integrated in the same fabric. The friction sensing part is formed by core-spun yarn A and yarn B through a weaving process; the core-spun yarn A and the yarn B respectively constitute the front and back sides of the weaving plain knit fabric structure; the inner core of the core-spun yarn A is a conductive metal wire, and the outer layer is covered with negative electrode friction fibers, while the yarn B is a positive electrode friction fiber; the friction sensing part is used to output triboelectric dynamic signals when the weaving plain knit fabric structure undergoes bending, contact, separation, or friction, so as to characterize the dynamic changes during joint movement. The tension-resistance sensing part is composed of core-spun yarn C; the core-spun yarn C is interwoven parallel to the preset deformation area of ​​the friction sensing part; the inner core of the core-spun yarn C is an elastic conductive composite yarn, and the outer layer is covered with insulating and wear-resistant yarn; the tension-resistance sensing part is used to output a static signal of resistance change when the knitted fabric structure undergoes bending deformation and maintains its posture, so as to characterize the static bending angle of the joint.

[0008] Optionally, the conductive metal wire is aluminum wire, copper wire, silver wire, or stainless steel wire; the negative electrode friction fiber is polyvinylidene fluoride, polytetrafluoroethylene, polyimide, or polyvinyl chloride; the positive electrode friction fiber is nylon, wool, silk, or cotton; and the elastic conductive composite yarn is copper-plated nylon, silver-plated nylon, silver-plated polyester, or carbon nanotube composite yarn.

[0009] Optionally, the transverse density of the padded knit fabric structure is 20 stitches / 5cm to 25 stitches / 5cm, and the longitudinal density is 15 rows / 5cm to 40 rows / 5cm.

[0010] Optionally, the core-spun yarn C is interlaced in parallel in the middle region of the friction sensing part or in a preset high-deformation region.

[0011] Optionally, the dynamic and static dual-mode knitting sensor is a single-layer knitting structure, and the friction sensing part and the tension sensing part are integrally formed in the same knitting process.

[0012] Secondly, this application provides a method for fabricating a dynamic-static dual-mode knitting sensor, comprising: Core-spun yarn A, yarn B, and core-spun yarn C are prepared respectively. Core-spun yarn A is composed of conductive metal wire and negative electrode friction fiber, and core-spun yarn C is composed of elastic conductive composite yarn and insulating wear-resistant yarn. The friction sensing part is formed by weaving core-spun yarn A and yarn B together using a plain knitting process, so that core-spun yarn A and yarn B are distributed on the front and back of the fabric, respectively. During the weaving process, the core-spun yarn C is embedded parallel to the preset deformation area of ​​the friction sensing part to form the tension-resistance sensing part; The knitted sensor formed by weaving has triboelectric signal output terminal and tensile resistance signal output terminal.

[0013] Thirdly, this application provides a remote operation control system based on the aforementioned dynamic and static dual-mode knitting sensor, including: a remote operation glove, a data processing unit, and a robot execution end; The remote control operating glove is equipped with several of the dynamic and static dual-mode knitting sensors as sensing units. The data processing unit is connected to the sensing unit and the robot execution end respectively, and is used to collect the triboelectric dynamic signal and tensile-resistance static signal output by the sensing unit, and convert the triboelectric dynamic signal and tensile-resistance static signal into control commands and send them to the robot execution end.

[0014] Optionally, the data processing unit includes a data acquisition module, a signal processing module, a mapping and conversion module, and a communication module; The data acquisition module is used to acquire triboelectric dynamic signals and tensile resistance static signals; The signal processing module is used to filter, extract features, and digitize triboelectric dynamic signals and tensile / resistive static signals. The mapping and conversion module is used to map human motion data into robot control data; The communication module is used to send control data to the robot's execution end.

[0015] Optionally, the mapping and conversion module is used to redirect and match the collected joint motion data according to the differences in structural parameters between the operator and the robot, so as to generate control instructions suitable for different robot models.

[0016] Optionally, the triboelectric dynamic signal output by the friction sensing part is used to characterize the joint movement speed or action intensity; the tensile static signal output by the resistance sensing part is used to characterize the bending angle when the joint is stationary; the data processing unit fuses the two types of signals to generate a synchronous control command.

[0017] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a dynamic and static dual-mode knitted sensor, its fabrication method, and a remote control operation system. Through a yarn-adding plain knitting process, a friction sensing component and a tensile resistance sensing component are integrated into a single layer of fabric. This utilizes the triboelectric effect's sensitivity to dynamic deformation to accurately capture dynamic information such as joint movement speed and intensity. It also utilizes the tensile resistance effect's stable change in resistance with tensile deformation to stably characterize the static bending angle of the joint. This achieves dynamic and static dual-mode sensing without the need for multi-layered structures, solving the problems of traditional single-sensor mechanisms failing to fully monitor complex joint movements, and multi-device splicing schemes damaging the overall fabric flexibility and easily causing signal interference. It can completely acquire dynamic and static information during joint movement while ensuring fabric softness, breathability, and wearing comfort, providing accurate and continuous sensing data support for human motion capture and robot remote control operation. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a dynamic and static dual-mode knitting sensor structure provided in an embodiment of this application.

[0020] Figure 2 This is a structural diagram of core-spun yarn A, yarn B, and core-spun yarn C provided in an embodiment of this application.

[0021] Figure 3 This is a dynamic signal response diagram of a sensor provided in an embodiment of this application.

[0022] Figure 4 This is a static bending signal response diagram of a sensor provided in an embodiment of this application.

[0023] Figure 5 This is an integrated diagram of a sensing system provided in an embodiment of this application.

[0024] Figure label: 1- Friction sensing part, 2- Tension and resistance sensing part. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] To address the challenges of existing technologies where a single sensing mechanism cannot simultaneously monitor both the dynamic and static states of human joint movement, and the issues of existing multi-layer splicing or stitching dual-modal sensors such as heavy structure, reduced flexibility and tensile performance, and significant interlayer interference.

[0027] This application provides a dynamic and static dual-mode knitted sensor that can simultaneously output dynamic and static signals within a single layer of knitted fabric, thereby providing a more complete characterization of complex joint motion processes. Furthermore, by utilizing the lightweight, soft, stretchable, and integrated knitting characteristics of the knitted structure, the increased thickness and additional interference caused by multi-layered structures are reduced. This ensures the sensor's tensile performance while improving long-term wear comfort. Additionally, the rational arrangement of the friction sensing substrate and the tension yarn reduces non-target physical interference, improving the accuracy and stability of the signal output.

[0028] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] Example 1 like Figure 1 and Figure 2 As shown, this embodiment provides a dynamic and static dual-mode knitting sensor. The dynamic and static dual-mode knitting sensor is a plain knitted fabric structure with added yarn and includes a friction sensing part 1 and a tension and resistance sensing part 2 integrated in the same fabric. The friction sensing part 1 is formed by core-spun yarn A and yarn B through a weaving process; the core-spun yarn A and the yarn B respectively constitute the front and back sides of the weaving plain knit fabric structure; the inner core of the core-spun yarn A is a conductive metal wire, and the outer layer is covered with negative electrode friction fibers, while the yarn B is a positive electrode friction fiber; the friction sensing part 1 is used to output triboelectric dynamic signals when the weaving plain knit fabric structure undergoes bending, contact, separation, or friction, so as to characterize the dynamic changes during joint movement. The tension-resistance sensing part 2 is composed of core-spun yarn C; the core-spun yarn C is interwoven parallel to the preset deformation area of ​​the friction sensing part 1; the inner core of the core-spun yarn C is an elastic conductive composite yarn, and the outer layer is covered with insulating and wear-resistant yarn; the tension-resistance sensing part 2 is used to output a static signal of resistance change when the knitted fabric structure undergoes bending deformation and maintains its posture, so as to characterize the static bending angle of the joint.

[0030] The conductive metal wire is made of aluminum, copper, silver, or stainless steel; the negative electrode friction fiber is made of polyvinylidene fluoride, polytetrafluoroethylene, polyimide, or polyvinyl chloride; the positive electrode friction fiber is made of nylon, wool, silk, or cotton; and the elastic conductive composite yarn is made of copper-plated nylon, silver-plated nylon, silver-plated polyester, or carbon nanotube composite yarn.

[0031] In some embodiments, the transverse density of the padded knitted fabric structure is 20 to 25 stitches / 5cm, and the longitudinal density is 15 to 40 rows / 5cm. The outer surface of the sensor is further covered with a flexible insulating protective layer to improve the device's abrasion resistance, insulation, and wear stability. The core-spun yarn C is interlaced parallel to the middle region of the friction sensing part 1 or a preset high-deformation region. The dynamic and static dual-mode knitted sensor is a single-layer knitted structure, and the friction sensing part 1 and the tension / resistance sensing part 2 are integrally formed during the same knitting process.

[0032] To obtain Figure 3 and Figure 4 Based on the test results, this embodiment prepared a specific dynamic and static dual-modal knitted sensor test sample. The conductive metal wire in core-spun yarn A is 0.1 mm aluminum wire, and the negative electrode friction fiber is 630D polyvinylidene fluoride fiber; the positive electrode yarn B is 210D six-ply nylon. The elastic composite yarn in core-spun yarn C is 70D copper-plated nylon, and the outer layer yarn is 210D three-ply nylon. The test sample has a transverse density of 20 stitches / 5cm and a longitudinal density of 20 rows / 5cm.

[0033] When performing dynamic signal response testing on the aforementioned dual-mode knitting sensor, such as Figure 3 As shown, the dynamic response performance of the sensor in this embodiment was tested. During the test, the sensor was fixed on the test platform, and periodic mechanical stimulation was applied to the sensor under different external load conditions. The loading forces were 5 N, 20 N, 35 N, 50 N and 65 N, respectively, and the voltage signal output by the friction sensing part 1 was collected.

[0034] Test results show that under different loading forces, the sensor can output stable and periodic triboelectric voltage signals, and the output voltage amplitude gradually increases with the increase of the applied load. Figure 3 As shown, the sensor exhibits good periodic response characteristics in the range of 5 N to 65 N, indicating that the friction sensing part 1 can effectively respond to external dynamic mechanical stimuli and characterize rapid bending, extension and contact changes during joint movement.

[0035] The results show that the friction sensing part 1 of the sensor provided in this embodiment has good dynamic response capability and is suitable for reflecting the dynamic motion state of the joint, especially for detecting motion speed, motion intensity and transient mechanical change information.

[0036] When performing a static bending response test on the aforementioned dynamic-static dual-mode knitting sensor, such as Figure 4 As shown, the static bending monitoring performance of the sensor in this embodiment was tested. The sensor was fixed to the surface of the bending test device, and different bending angles were set to measure the relative resistance change rate ΔR / R0 of the tensile-resistance sensing part 2. The test angles can be set to 0°, 30°, 60°, and 90°.

[0037] Test results show that as the bending angle increases, the relative resistance change rate of the sensor gradually increases, exhibiting a good linear relationship with the bending angle. Figure 4 It can be seen that the fitting correlation coefficient R between ΔR / R0 and the bending angle is... 2 The value of 0.998 indicates that the tension-resistance sensing part 2 described in this embodiment can stably and accurately characterize the static posture information after the joint is bent.

[0038] Therefore, the tension and resistance sensing part 2 of the sensor in this embodiment is suitable for static angle detection and can continuously output a stable signal when the human joint is in a bent state, thereby making up for the inadequacy of a single triboelectric sensor in characterizing static posture.

[0039] Example 2 This embodiment provides a method for fabricating a dynamic and static dual-mode knitting sensor, including: Step 1: Prepare core-spun yarn A, yarn B and core-spun yarn C respectively. Core-spun yarn A is composed of conductive metal wire and negative electrode friction fiber, and core-spun yarn C is composed of elastic conductive composite yarn and insulating wear-resistant yarn. Step 2: Use the yarn-adding plain knitting process to knit the core-spun yarn A and yarn B to form the friction sensing part 1, so that the core-spun yarn A and yarn B are distributed on the front and back of the fabric respectively; Step 3: During the weaving process, the core-spun yarn C is embedded parallel to the preset deformation area of ​​the friction sensing part 1 to form the tension-resistance sensing part 2; Step 4: Lead out the triboelectric signal output terminal and the tensile resistance signal output terminal of the knitted sensor formed by knitting.

[0040] Example 3 like Figure 5 As shown, this embodiment provides a remote control operation control system based on the aforementioned dynamic and static dual-mode knitting sensor, including: a remote control operation glove, a data processing unit, and a robot execution end; The remote-controlled operating glove is equipped with several dynamic and static dual-mode knitted sensors as sensing units; wherein, the dual-mode knitted sensors are respectively arranged on each finger part of the glove to sense the dynamic bending process and static stationary state of the finger joints in real time.

[0041] The data processing unit is connected to the sensing unit and the robot execution end respectively, and is used to collect the triboelectric dynamic signal and tensile-resistance static signal output by the sensing unit, and convert the triboelectric dynamic signal and tensile-resistance static signal into control commands and send them to the robot execution end.

[0042] The data processing unit includes a data acquisition module, a signal processing module, a mapping and conversion module, and a communication module. The data acquisition module is used to acquire triboelectric dynamic signals and tensile resistance static signals; The signal processing module is used to filter, extract features, and digitize triboelectric dynamic signals and tensile / resistive static signals. The mapping and conversion module is used to map human motion data into robot control data; The communication module is used to send control data to the robot's execution end.

[0043] The mapping and conversion module is used to redirect and match the collected joint motion data according to the differences in structural parameters between the operator and the robot, so as to generate control instructions suitable for different robot models.

[0044] The friction sensing part 1 outputs a triboelectric dynamic signal to characterize the joint movement speed or action intensity; the tension and resistance sensing part 2 outputs a tension and resistance static signal to characterize the bending angle when the joint is stationary; the data processing unit fuses the two types of signals to generate a synchronous control command.

[0045] During use, after the operator wears the remote-controlled gloves, the bending speed of the finger joints can be characterized by the dynamic signal output by the friction sensor 1, and the finger stopping angle can be characterized by the static signal output by the tension and resistance sensor 2. By fusing these two types of signals, a more complete recognition of the finger movement state can be achieved, and further converted into corresponding robot control commands, thereby realizing remote synchronous control of the robot hand or mechanical actuator.

[0046] In this embodiment, the sensing system can be applied to scenarios such as remote-controlled gloves, virtual reality interactive devices, wearable motion capture devices, and robot remote control systems.

[0047] In summary, this application has the following technical effects: The sensor provided in this application has both dynamic and static monitoring functions and can be used to monitor the movement state of human hand joints. It also relates to applications in human-computer interaction and robot remote control operation control systems.

[0048] The sensor provided in this application can simultaneously output dynamic and static signals within a single layer of knitted fabric, thereby providing a more complete characterization of complex joint motion processes. Furthermore, by utilizing the lightweight, soft, stretchable, and integrated knitting characteristics of the knitted structure, the increased thickness and additional interference caused by multi-layered structures are reduced. This ensures the sensor's tensile performance while improving long-term wear comfort. Additionally, the rational arrangement of the friction sensing substrate and the resistance yarns reduces non-target physical interference, improving the accuracy and stability of the signal output.

[0049] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0050] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A dynamic and static dual-mode knitting sensor, characterized in that, The dynamic and static dual-mode knitting sensor is a plain knitted fabric structure with added yarn, and includes a friction sensing part and a tension / resistance sensing part integrated in the same fabric. The friction sensing part is formed by core-spun yarn A and yarn B through a weaving process; the core-spun yarn A and the yarn B respectively constitute the front and back sides of the weaving plain knit fabric structure; the inner core of the core-spun yarn A is a conductive metal wire, and the outer layer is covered with negative electrode friction fibers, while the yarn B is a positive electrode friction fiber; the friction sensing part is used to output triboelectric dynamic signals when the weaving plain knit fabric structure undergoes bending, contact, separation, or friction, so as to characterize the dynamic changes during joint movement. The tension-resistance sensing part is composed of core-spun yarn C; the core-spun yarn C is interwoven parallel to the preset deformation area of ​​the friction sensing part; the inner core of the core-spun yarn C is an elastic conductive composite yarn, and the outer layer is covered with insulating and wear-resistant yarn; the tension-resistance sensing part is used to output a static signal of resistance change when the knitted fabric structure undergoes bending deformation and maintains its posture, so as to characterize the static bending angle of the joint.

2. The dynamic and static dual-mode knitting sensor according to claim 1, characterized in that, The conductive metal wire is aluminum wire, copper wire, silver wire or stainless steel wire; the negative electrode friction fiber is polyvinylidene fluoride, polytetrafluoroethylene, polyimide or polyvinyl chloride; the positive electrode friction fiber is nylon, wool, silk or cotton; the elastic conductive composite yarn is copper-plated nylon, silver-plated nylon, silver-plated polyester or carbon nanotube composite yarn.

3. The dynamic and static dual-mode knitting sensor according to claim 1, characterized in that, The transverse density of the plain knitted fabric structure is 20 stitches / 5cm to 25 stitches / 5cm, and the longitudinal density is 15 rows / 5cm to 40 rows / 5cm.

4. The dynamic and static dual-mode knitting sensor according to claim 1, characterized in that, The core-spun yarn C is interwoven in parallel in the middle region or a preset high-deformation region of the friction sensing part.

5. A dynamic and static dual-mode knitting sensor according to claim 1, characterized in that, The dynamic and static dual-mode knitted sensor has a single-layer knitted structure, and the friction sensing part and the tension sensing part are integrally formed in the same knitting process.

6. A method for preparing a dynamic-static dual-mode knitting sensor according to any one of claims 1-5, characterized in that, include: Core-spun yarn A, yarn B, and core-spun yarn C are prepared respectively. Core-spun yarn A is composed of conductive metal wire and negative electrode friction fiber, and core-spun yarn C is composed of elastic conductive composite yarn and insulating wear-resistant yarn. The friction sensing part is formed by weaving core-spun yarn A and yarn B together using a plain knitting process, so that core-spun yarn A and yarn B are distributed on the front and back of the fabric, respectively. During the weaving process, the core-spun yarn C is embedded parallel to the preset deformation area of ​​the friction sensing part to form the tension-resistance sensing part; The knitted sensor formed by weaving has triboelectric signal output terminal and tensile resistance signal output terminal.

7. A remote control operation control system based on a dynamic and static dual-mode knitting sensor according to any one of claims 1-5, characterized in that, include: Remote control gloves, data processing unit, and robot actuator; The remote control operating glove is equipped with several of the dynamic and static dual-mode knitting sensors as sensing units. The data processing unit is connected to the sensing unit and the robot execution end respectively, and is used to collect the triboelectric dynamic signal and tensile-resistance static signal output by the sensing unit, and convert the triboelectric dynamic signal and tensile-resistance static signal into control commands and send them to the robot execution end.

8. The remote control operation control system according to claim 7, characterized in that, The data processing unit includes a data acquisition module, a signal processing module, a mapping conversion module, and a communication module; The data acquisition module is used to acquire triboelectric dynamic signals and tensile resistance static signals; The signal processing module is used to filter, extract features, and digitize triboelectric dynamic signals and tensile / resistive static signals. The mapping and conversion module is used to map human motion data into robot control data; The communication module is used to send control data to the robot's execution end.

9. The remote control operation control system according to claim 8, characterized in that, The mapping and conversion module is used to redirect and match the collected joint motion data according to the differences in structural parameters between the operator and the robot, so as to generate control commands suitable for different robot models.

10. The remote control operation control system according to claim 7, characterized in that, The triboelectric dynamic signal output by the friction sensing part is used to characterize the joint movement speed or action intensity; the tensile and resistive static signal output by the tensile and resistive sensing part is used to characterize the bending angle when the joint is stationary; the data processing unit fuses the two types of signals to generate a synchronous control command.

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