Hand pressure sensing device, exoskeleton assistance method, device, apparatus, and medium

Abstract

The application belongs to the technical field of intelligent exoskeletons, and particularly relates to a hand pressure sensing device, an exoskeleton assisting method, a device, equipment and a medium. The hand pressure sensing device comprises a hand structure base body and flexible pressure sensors, 5 flexible pressure sensors are arranged at five finger parts, and 20 flexible pressure sensors are arranged at a palm part; the current action type of a user is determined according to pressure data of the flexible pressure sensors; if it is a lifting action, an instruction for starting assistance is generated, and assistance to the user is adjusted in real time according to the pressure data; if it is a false action, the instruction for starting assistance is not generated. The device and the method provided by the application can perceive the current action state of each user, adjust assistance according to actual pressure, and adapt to a cable construction scene.

Description

Technical Field

[0001] This invention belongs to the field of intelligent exoskeleton technology, specifically relating to a hand pressure sensing device, an exoskeleton assistance method, device, equipment, and medium. Background Technology

[0002] Currently, in some work scenarios in logistics warehousing, industrial manufacturing, and military industries, waist exoskeleton robots are gradually being used for heavy object handling, aiming to reduce the stress on the waist and reduce the risk of waist muscle injury to workers. These work scenarios are generally operated by a single person wearing a waist exoskeleton robot, without the need for multiple people to cooperate.

[0003] In the process of lifting high-voltage power cables to cable supports inside tunnels, the limited space prevents the use of large equipment to access the underground space. Currently, power cables hundreds of meters or even kilometers long can only be lifted and positioned by workers by hand or with simple tools such as crowbars and ropes. Since the unit weight of different types of high-voltage power cables can be as high as 15-40 kg / m, long-term heavy-duty handling can easily lead to accidental injuries to workers or cause health problems such as lumbar muscle strain due to overwork. Therefore, lumbar exoskeleton robots can effectively meet the needs of lifting and positioning high-voltage power cables inside tunnels.

[0004] However, for single-person operations in fields such as logistics warehousing, industrial manufacturing, and military industry, the lifting and positioning of high-voltage power cables in tunnels requires multi-person collaboration, and the force on workers in different positions is uneven. Therefore, how to adjust the output assistance of the waist exoskeleton robot in real time according to the force on each person is a problem that urgently needs to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide a hand pressure sensing device, exoskeleton assistance method, device, equipment and medium to solve the problem of uneven force distribution on workers in different positions in the prior art, which requires separate assistance adjustments for each user.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a hand pressure sensing device for data acquisition assisted by an exoskeleton used in cable construction, comprising:

[0008] The hand structure base has its first surface located on the palm side after wearing, fitting snugly against the user's palm and fingers; the hand structure base includes a palm part and a finger part, corresponding to the user's palm and five fingers respectively;

[0009] A flexible pressure sensor is installed on the second side of the hand structure substrate. During use, it can contact the cable to collect pressure data on the hand caused by the cable.

[0010] Furthermore, a flexible material layer is provided on the hand structure substrate, which is used to cover the outside of the flexible pressure sensor, and a wear-resistant layer is also provided on the outside of the flexible material layer.

[0011] Furthermore, five flexible pressure sensors are arranged on each of the five fingers, and 20 flexible pressure sensors are arranged on the palm.

[0012] Among them, the five flexible pressure sensors for a finger are arranged vertically along the finger direction, corresponding to the three phalanges and two joints of each finger, to measure the pressure distribution of each joint; the 20 flexible pressure sensors for the palm are evenly distributed below the end of the finger root joint to acquire palm pressure data.

[0013] Furthermore, 20 flexible pressure sensors are arranged in 5 rows and 4 columns on the palm, with each column corresponding to one finger.

[0014] In a second aspect, the present invention provides an exoskeleton-assisted method, based on pressure data collected by the hand pressure sensing device, comprising the following steps:

[0015] Acquire pressure data collected by the hand pressure sensor;

[0016] The user's current action type is determined based on the pressure data; the action type includes carrying action and accidental action; if it is a carrying action, an instruction to start assist is generated, and the assistance to the user is adjusted in real time according to the pressure data; if it is an accidental action, no instruction to start assist is generated.

[0017] Furthermore, based on the pressure data, the user's current action type is determined, including:

[0018] First pressure data and second pressure data for finger positions are determined from the pressure data; wherein, the first pressure data includes pressure data for the index finger, middle finger, ring finger, and little finger, and the second pressure data is the pressure data for the thumb; a first weight and a second weight are assigned to the first pressure data and the second pressure data, respectively;

[0019] A third pressure data point for the finger area is determined from the pressure data; wherein, the third pressure data point is the pressure data point for the palm area; a third weight is assigned to the third pressure data point.

[0020] The first judgment value is obtained by summing the product of the first pressure data and the first weight, the product of the second pressure data and the second weight, and the product of the third pressure data and the third weight.

[0021] Determine the relationship between the first judgment value and the preset standard value;

[0022] Based on the first pressure data, the second pressure data, and the third pressure data, construct curves of pressure data changing over time, and determine whether the curves of the first pressure data, the second pressure data, and the third pressure data satisfy a linear law;

[0023] If the first judgment value is greater than the preset standard value, and the curves of the first pressure data, the second pressure data, and the third pressure data satisfy the linear law, the current action is considered to be a handling action; otherwise, it is considered a false action.

[0024] Furthermore, the assistance provided to the user is adjusted in real time based on stress data, including:

[0025] Obtain a pre-built database; the database pre-stores standard pressure data and corresponding assist data.

[0026] The user's stress data is matched with corresponding standard stress data in the database to determine the corresponding assistance data, and assistance is provided to the user based on the corresponding assistance data.

[0027] In a third aspect, the present invention provides an exoskeleton assistive device, comprising:

[0028] The data acquisition module is used to acquire pressure data collected by the hand pressure sensing device;

[0029] The assist determination module is used to determine the user's current action type based on the pressure data; wherein the action type includes carrying action and mis-action; if it is a carrying action, an instruction to start assist is generated; if it is a mis-action, an instruction to start assist is not generated.

[0030] In a fourth aspect, the present invention provides an electronic device including a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the exoskeleton assistance method as described above.

[0031] In a fifth aspect, the present invention provides a computer-readable storage medium storing at least one instruction that, when executed by a processor, implements the exoskeleton assistance method as described above.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] The hand pressure sensing device provided by this invention has its sensor distribution designed based on hand characteristics and the outer surface characteristics of the cable. According to hand characteristics, five pressure sensors are arranged on each of the five fingers, corresponding to the three phalanges and two joints of each finger, ensuring pressure data is available for the entire finger area even when gloves are worn. In the palm area, 20 pressure sensors are evenly distributed below the finger joints to avoid the area of ​​greatest deformation during grasping. This avoids interference from pressure data caused by deformation during grasping and clenching, ensuring that the palm pressure data more accurately reflects the pressure data during grasping.

[0034] The exoskeleton-assisted method provided by this invention determines the user's current action type based on pressure data. If it is a lifting action, a command to activate assistance is generated, and the assistance to the user is adjusted in real time according to the pressure data. If it is a mis-action, no command to activate assistance is generated. It can sense the current action state of each user and adjust the assistance according to the actual pressure received, adapting to cable construction scenarios. The exoskeleton-assisted device, electronic device, and computer-readable storage medium provided by this invention also solve the problems raised in the background section. Attached Figure Description

[0035] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0036] Figure 1 This is a schematic diagram of the structure of a hand pressure sensing device according to an embodiment of the present invention;

[0037] Figure 2 This is a flowchart illustrating an exoskeleton-assisted method according to an embodiment of the present invention;

[0038] Figure 3 This is a structural block diagram of an exoskeleton assistive device according to an embodiment of the present invention;

[0039] Figure 4 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0040] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0041] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0042] Example 1

[0043] This invention provides a hand pressure sensing device for data acquisition using an exoskeleton in cable construction. The pressure signal from a flexible hand pressure sensor is transmitted via a spring data cable, processed, and then sent to the control system of a lumbar exoskeleton robot. The exoskeleton determines the wearer's load level and intensity based on the pressure value, providing appropriate assistance to meet the needs of multi-person collaboration. Specifically addressing the lifting and positioning of high-voltage power cables in tunnels, this lumbar exoskeleton robot effectively solves the health risks posed by existing technologies and addresses the issue of uneven force distribution in multi-person collaboration, thereby improving work efficiency and reducing construction costs.

[0044] like Figure 1 As shown, a hand pressure sensing device for data acquisition using an exoskeleton for cable construction includes:

[0045] The hand structure base 1 has a first surface located on the palm side after being worn, fitting in contact with the user's palm and fingers; the hand structure base 1 includes a palm part and a finger part, corresponding to the user's palm and five fingers respectively.

[0046] The flexible pressure sensor 2 is disposed on the second side of the hand structure substrate 1 and can contact the cable during use to collect pressure data of the hand under the cable.

[0047] In one optional embodiment, the main structure of the hand pressure sensing device is made of a special soft material, on which a thin-film pressure sensor is attached and wires are printed. It is comfortable to wear, flexible, and does not hinder normal hand movements, allowing for flexible finger operation even after wearing. Specifically, the hand structure substrate 1 includes a palm-area diving cotton protective layer and a wrist-area diving cotton protective layer, which are directly sewn to the glove. The rear of the hand pressure sensing device is connected to a data integration control box and secured to the user's arm by a forearm fixing strap. Two controller switch buttons are located on the top of the data integration control box, used to control the exoskeleton robot's on / off function or assist adjustment functions. Finally, the data signals collected by the hand are aggregated into the exoskeleton robot via a spring data cable.

[0048] Preferably, considering the usage scenario, since frequent gripping of the cable causes significant wear on the palm area of ​​the hand pressure sensor, a multi-layer structure is designed to address this wear. A flexible material is wrapped around the outer layer of the main structure of the hand pressure sensor to protect the sensor, and a quickly replaceable wear-resistant layer is incorporated into the hand pressure sensor. Specifically, a flexible material layer is provided on the hand structure substrate 1, which covers the outer side of the flexible pressure sensor 2. A wear-resistant layer is also provided on the outer side of the flexible material layer using Velcro. After repeated use and wear, the outer layer can be quickly removed and replaced with a new wear-resistant layer.

[0049] In this scheme, the sensor distribution is designed based on hand characteristics and cable outer surface characteristics.

[0050] Specifically, based on the characteristics of the hand, five flexible pressure sensors 2 are arranged on each of the five fingers, corresponding to the three phalanges and two joints of each finger, ensuring that pressure data is available for the entire finger area when gloves are worn. Twenty flexible pressure sensors 2 are arranged on the palm, evenly distributed below the finger joints, to avoid the area of ​​greatest deformation in the palm during grasping. This avoids interference with pressure data caused by deformation during grasping and clenching, ensuring that the pressure data from the palm more accurately reflects the pressure data during grasping.

[0051] Among them, the five flexible pressure sensors 2 for a finger are arranged vertically along the finger direction, corresponding to the three phalanges and two phalanges of each finger, respectively, to measure the pressure distribution of each phalanx; the 20 flexible pressure sensors 2 for the palm are evenly distributed below the end of the finger root joint to acquire palm pressure data.

[0052] As an example, 20 flexible pressure sensors 2 on the palm are arranged in a 5x4 grid, with each column corresponding to one finger. Random or other arrangements are also possible, with the aim of collecting the most accurate and effective data possible.

[0053] Example 2

[0054] like Figure 2 As shown, an exoskeleton-assisted method, based on pressure data collected by a hand pressure sensing device, includes the following steps:

[0055] S1. Acquire pressure data collected by the hand pressure sensor.

[0056] Specifically, each finger has five pressure points used to measure the pressure distribution across each phalanx. Since a human finger has three phalanges, this design places two points at the fingertip, one to two in the middle, and one to two at the distal phalanx. Due to the uncertainty of glove placement, these five points are evenly distributed across the three phalanges. These points are used to house flexible pressure sensors. The palm also has 20 pressure points distributed in 5 rows and 4 columns, similarly used to house flexible pressure sensors. The collected pressure data includes the pressure data at each point, and this data is used for motion detection and exoskeleton assistance.

[0057] S2. Determine the user's current action type based on the pressure data; wherein, the action type includes carrying action and accidental action; if it is a carrying action, generate an instruction to start assistance and adjust the assistance to the user in real time according to the pressure data; if it is an accidental action, do not generate an instruction to start assistance.

[0058] Specifically, the user's current action type is determined based on the pressure data, including:

[0059] First pressure data and second pressure data for finger positions are determined from the pressure data; wherein, the first pressure data includes pressure data for the index finger, middle finger, ring finger, and little finger, and the second pressure data is the pressure data for the thumb; a first weight and a second weight are assigned to the first pressure data and the second pressure data, respectively;

[0060] A third pressure data point for the finger area is determined from the pressure data; wherein, the third pressure data point is the pressure data point for the palm area; a third weight is assigned to the third pressure data point.

[0061] The first judgment value is obtained by summing the product of the first pressure data and the first weight, the product of the second pressure data and the second weight, and the product of the third pressure data and the third weight.

[0062] Determine the relationship between the first judgment value and the preset standard value;

[0063] Based on the first pressure data, the second pressure data, and the third pressure data, construct curves of pressure data changing over time, and determine whether the curves of the first pressure data, the second pressure data, and the third pressure data satisfy a linear law;

[0064] If the first judgment value is greater than the preset standard value, and the curves of the first pressure data, the second pressure data, and the third pressure data satisfy the linear law, the current action is considered to be a handling action; otherwise, it is considered a false action.

[0065] In the above scheme, the first weight is preferably 60%, the second weight is preferably 30%, and the third weight is preferably 10%.

[0066] In a preferred embodiment, the method further includes a step of judging the action type, including: determining a first high-pressure zone in the finger area and a second high-pressure zone in the palm area; judging the magnitude of the average pressure data in the first and second high-pressure zones; if the first high-pressure zone is smaller than the second high-pressure zone, the current action is considered a erroneous action; otherwise, it is judged as a carrying action. In the case of an erroneous action, the pressure data in the first high-pressure zone is low; the pressure data in the second high-pressure zone is high, but does not show a linear pattern, and the pressure points are distributed randomly, indicating a certain degree of randomness. Therefore, it can be determined that no object grasping has occurred.

[0067] Specifically, the first high-pressure zone is selected from the data of two flexible pressure sensors on the fingertips, and the second high-pressure zone is selected from the data of two or three rows of flexible pressure sensors in the middle of the palm.

[0068] It should be noted that, since different cable diameters may cause different force patterns in flexible pressure sensors or diffusion of high-pressure areas, this solution also collects and samples such data to increase or decrease the range of high-pressure areas, thus obtaining an fuzzy data region.

[0069] Specifically, the assistance provided to the user is adjusted in real time based on stress data, including:

[0070] Obtain a pre-built database; the database pre-stores standard pressure data and corresponding assist data.

[0071] The user's stress data is matched with corresponding standard stress data in the database to determine the corresponding assistance data, and assistance is provided to the user based on the corresponding assistance data.

[0072] The above solution considers the varying forces exerted on workers at different positions during cable lifting and positioning. Existing exoskeletons mostly use a fixed-level assist output mode, while this device's real-time adjustment of assist power avoids prolonged high-power output, thus effectively reducing battery load and increasing endurance. This is the first time an exoskeleton has been used in the construction of high-voltage power cables within tunnels. Using an exoskeleton can effectively reduce the labor intensity of workers, improve work efficiency, reduce labor input, and save project costs.

[0073] In an optional embodiment, a method for lifting and positioning high-voltage power cables within a tunnel is also provided, specifically including:

[0074] Before entering the confined space of the underground tunnel, check that the waist exoskeleton robot and hand pressure sensor are in good condition, the accessories are complete, and the battery is sufficient. Use test blocks of different weights to verify whether the exoskeleton can output different levels of assistance.

[0075] Inside the underground tunnel, properly put on the waist exoskeleton robot, install the battery, and turn on the battery power.

[0076] Based on the site conditions and the worker's height and arm length, adjust the length of the strap connected to the hand pressure sensor so that the arm is slightly bent when the strap is taut. At this time, the weight of the cable will be transmitted from the hand pressure sensor to the rear connector of the waist exoskeleton robot through the strap. This allows the waist exoskeleton robot to share some of the weight of the cable, reducing the burden on the worker's arm, while also securing the hand pressure sensor to the hand.

[0077] Press the start button on the waist exoskeleton robot to power it on.

[0078] Once a group of five to eight people is ready, they begin lifting the power cable. Flexible pressure sensors on their hands contact the cable, changing its resistance. This resistance is converted into a digital signal via an A / D converter, providing feedback on whether the user has started bearing weight and the amount of weight. This also provides a start signal to the lumbar exoskeleton robot, adjusting the motor output force required by the robot to provide different levels of assistance based on the user's load. During the cable lifting process, the lumbar exoskeleton robot protects the worker's lower back and spine while remaining intelligent and flexible, without affecting daily hand movements, making it convenient for the wearer.

[0079] Example 3

[0080] like Figure 3 As shown, based on the same inventive concept as the above embodiments, the present invention also provides an exoskeleton assistive device, comprising:

[0081] The data acquisition module is used to acquire pressure data collected by the hand pressure sensing device;

[0082] The assist determination module is used to determine the user's current action type based on the pressure data; wherein the action type includes carrying action and mis-action; if it is a carrying action, an instruction to start assist is generated; if it is a mis-action, an instruction to start assist is not generated.

[0083] Example 4

[0084] like Figure 4As shown, the present invention also provides an electronic device 100 for implementing an exoskeleton assistance method according to the above embodiments; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104. The memory 101 can be used to store the computer program 103, and the processor 102 implements the steps of the exoskeleton assistance method of Embodiment 2 by running or executing the computer program stored in the memory 101 and calling data stored in the memory 101.

[0085] The memory 101 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0086] At least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 102 may be a microprocessor or any conventional processor. Processor 102 is the control center of electronic device 100, connecting various parts of electronic device 100 via various interfaces and lines.

[0087] The memory 101 in the electronic device 100 stores multiple instructions to implement an exoskeleton assistive method, and the processor 102 can execute multiple instructions to achieve the following:

[0088] Acquire pressure data collected by the hand pressure sensor;

[0089] The user's current action type is determined based on the pressure data; the action type includes carrying action and accidental action; if it is a carrying action, an instruction to start assist is generated, and the assistance to the user is adjusted in real time according to the pressure data; if it is an accidental action, no instruction to start assist is generated.

[0090] Example 5

[0091] If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, and read-only memory (ROM).

[0092] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0093] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0094] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0095] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0096] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An exoskeleton-assisted method, based on pressure data collected by a hand pressure sensing device, characterized in that, Includes the following steps: Acquire pressure data collected by the hand pressure sensor; The user's current action type is determined based on the pressure data; wherein, the action type includes carrying action and mis-action; if it is a carrying action, an instruction to activate assistance is generated, and the assistance to the user is adjusted in real time according to the pressure data; if it is a mis-action, no instruction to activate assistance is generated. The hand pressure sensing device includes: The hand structure substrate (1) has a first surface located on the palm side after being worn, which fits against the user's palm and fingers; the hand structure substrate (1) includes a palm part and a finger part, which correspond to the user's palm and five fingers respectively; A flexible pressure sensor (2) is disposed on the second side of the hand structure substrate (1) and can contact the cable during use to collect pressure data of the hand under the cable. Five flexible pressure sensors (2) are arranged on each of the five fingers, and 20 flexible pressure sensors (2) are arranged on the palm. The five flexible pressure sensors (2) on each finger are arranged vertically along the finger direction, corresponding to the three phalanges and two phalanges of each finger, to measure the pressure distribution of each phalanx. The 20 flexible pressure sensors (2) on the palm are evenly distributed below the end of the finger root joint to obtain pressure data of the palm. Determining the user's current action type based on the pressure data includes: First pressure data and second pressure data for finger positions are determined from the pressure data; wherein, the first pressure data includes pressure data for the index finger, middle finger, ring finger, and little finger, and the second pressure data is the pressure data for the thumb; a first weight and a second weight are assigned to the first pressure data and the second pressure data, respectively; A third pressure data point for the palm region is determined from the pressure data; wherein the third pressure data is the pressure data for the palm region; a third weight is assigned to the third pressure data. The first judgment value is obtained by summing the product of the first pressure data and the first weight, the product of the second pressure data and the second weight, and the product of the third pressure data and the third weight. Determine the relationship between the first judgment value and the preset standard value; Based on the first pressure data, the second pressure data, and the third pressure data, construct curves of pressure data changing over time, and determine whether the curves of the first pressure data, the second pressure data, and the third pressure data satisfy a linear law; When the first judgment value is greater than the preset standard value, and the curves of the first pressure data, the second pressure data, and the third pressure data satisfy a linear law, a first high-pressure area is determined at the finger area, and a second high-pressure area is determined at the palm area. The magnitude of the average pressure data in the first high-pressure area and the second high-pressure area is judged. The first high-pressure area is selected as the data of two flexible pressure sensors at the fingertip, and the second high-pressure area is selected as the data of two or three rows of flexible pressure sensors in the middle of the palm area. By increasing or decreasing the range of the first and second high-pressure zones according to the diameter of different cables, a fuzzy data region for determining the action type is obtained. When the average pressure data in the first high-pressure zone is less than the average pressure data in the second high-pressure zone, the current action is considered a malfunction; when the average pressure data in the first high-pressure zone is not less than the average pressure data in the second high-pressure zone, the current action is considered a handling action. When the first judgment value is not greater than the preset standard value, or when the curves of the first pressure data, the second pressure data, and the third pressure data do not meet the linear law, the current action is considered to be a false action.

2. The exoskeleton assistance method according to claim 1, characterized in that, A flexible material layer is provided on the hand structure substrate (1), which is used to cover the outside of the flexible pressure sensor (2). A wear-resistant layer is also provided on the outside of the flexible material layer.

3. The exoskeleton assistance method according to claim 1, characterized in that, Twenty flexible pressure sensors (2) are arranged in 5 rows and 4 columns on the palm, with each column corresponding to one finger.

4. The exoskeleton assistance method according to claim 1, characterized in that, Adjust assistance to the user in real time based on stress data, including: Obtain a pre-built database; the database pre-stores standard pressure data and corresponding assist data. The user's stress data is matched with corresponding standard stress data in the database to determine the corresponding assistance data, and assistance is provided to the user based on the corresponding assistance data.

5. An exoskeleton assistive device for implementing the exoskeleton assistive method according to any one of claims 1 to 4, characterized in that, include: The data acquisition module is used to acquire pressure data collected by the hand pressure sensing device; The assist determination module is used to determine the user's current action type based on the pressure data; wherein the action type includes carrying action and mis-action; if it is a carrying action, an instruction to start assist is generated; if it is a mis-action, an instruction to start assist is not generated.

6. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the exoskeleton assistance method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements the exoskeleton assistance method as described in any one of claims 1 to 4.

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