An exoskeleton module and its usage method

Abstract

The present application relates to exoskeleton module technical field, disclose a kind of exoskeleton module and use method, including: exoskeleton module ontology, sensor group, battery module, drive assembly and control module;Control module includes acquisition unit, judging unit, processing unit;Acquisition unit is configured to real-time acquisition detachable counterweight generated assist torque, according to assist torque to establish assist torque set, according to assist torque set to calculate the change rate of assist torque;Judging unit is configured to compare change rate with change rate threshold, whether the number of detachable counterweight is adjusted according to the comparison result;Processing unit adjusts the number of detachable counterweight according to heart rate data.The adjustment mechanism based on heart rate of the present application not only can improve the motion efficiency of user, also can prevent sports injury to a certain extent, ensure that user is in the range of safe movement.

Description

Technical Field

[0001] This invention relates to the field of exoskeleton module technology, and more specifically, to an exoskeleton module and its method of use. Background Technology

[0002] An exoskeleton module is a wearable mechanical device designed to enhance or assist the human body's mobility and strength. It typically consists of multiple independent modules that can be combined and configured to suit different application scenarios. Exoskeleton modules are widely used in medical rehabilitation, industrial operations, military protection, and daily living assistance.

[0003] Traditional exoskeleton modules often lack sufficient intelligent adjustment mechanisms and cannot adjust according to the user's actual movement status and physiological response, which limits their performance and comfort in practical applications. Summary of the Invention

[0004] In view of this, the present invention proposes an exoskeleton module and a method of use, aiming to solve the problem that the current technology lacks sufficient intelligent adjustment mechanisms and cannot adjust according to the user's actual movement state and physiological response.

[0005] In one aspect, the present invention proposes an exoskeleton module, comprising:

[0006] The exoskeleton module comprises a main body, a sensor group, a battery module, a drive assembly, and a control module. The sensor group, battery module, drive assembly, and control module are housed within the main body of the exoskeleton module. The sensor group includes a posture sensor, a force sensor, and a heart rate sensor. The battery module includes multiple battery cells connected in series or parallel. The drive assembly includes a drive motor, a connecting rod, and a detachable counterweight. The output end of the drive motor is perpendicularly connected to one end of the connecting rod, and the detachable counterweight is connected to the other end of the connecting rod. The drive motor can drive the detachable counterweight to perform non-uniform circular motion via the connecting rod. The control module includes a data acquisition unit, a judgment unit, and a processing unit.

[0007] The acquisition unit is configured to acquire the assist torque generated by the detachable counterweight in real time, establish an assist torque set based on the assist torque, and calculate the rate of change of the assist torque based on the assist torque set.

[0008] The judgment unit is configured to compare the rate of change with a rate of change threshold, and determine whether to adjust the number of detachable counterweights based on the comparison result.

[0009] When it is determined that the number of detachable counterweights needs to be adjusted, the determination unit controls the acquisition unit to acquire the user's posture angle and movement speed, and establishes a posture angle dataset and a movement speed dataset based on the posture angle and movement speed respectively; the posture angle dataset and the movement speed dataset are fused to obtain a fused dataset; the similarity between the fused dataset and the movement pattern template is calculated, the similarity is compared with a similarity threshold, and the number of detachable counterweights is adjusted based on the comparison result;

[0010] The processing unit is configured to control the acquisition unit to acquire the user's heart rate data when the similarity is less than the similarity threshold, and to adjust the number of detachable counterweights based on the heart rate data.

[0011] Further, establishing a set of assist torques based on the assist torque, and calculating the rate of change of the assist torque based on the set of assist torques, includes:

[0012] The collected assist torques are recorded sequentially according to time.

[0013] The assist torque in the assist torque concentration is filtered to remove noise and outliers;

[0014] The rate of change is obtained by calculating the derivative of the assist torque with time using a numerical differentiation method.

[0015] Further, when comparing the rate of change with a rate of change threshold, and determining whether to adjust the number of detachable counterweights based on the comparison result, the following steps are included:

[0016] When the rate of change is less than or equal to the rate of change threshold, the determination unit determines that the number of detachable counterweights should not be adjusted.

[0017] When the rate of change is greater than the rate of change threshold, the determination unit determines to adjust the number of detachable counterweights.

[0018] Furthermore, when fusing the attitude angle dataset and the motion velocity dataset to obtain the fused dataset, the following steps are included:

[0019] Extract attitude feature data from the attitude angle dataset, the attitude feature data including pitch angle, roll angle and yaw angle;

[0020] Extract motion feature data from the motion velocity dataset, the motion feature data including linear velocity and angular velocity;

[0021] The attitude feature data and the motion feature data are fused using the Kalman filter algorithm to obtain the fused dataset.

[0022] Furthermore, the exercise mode templates include a walking mode template, a running mode template, and a hill climbing mode template.

[0023] Furthermore, when calculating the similarity between the fused dataset and the motion pattern template, the following steps are included:

[0024] The similarity is obtained by the following formula:

[0025]

[0026] Where Di represents the similarity, Fi represents the i-th feature value in the fused dataset, and T i,j This represents the j-th feature value of the motion pattern template for different types.

[0027] Further, when comparing the similarity with a similarity threshold and adjusting the number of detachable counterweights based on the comparison result, the following steps are included:

[0028] When the similarity is greater than or equal to the similarity threshold, the processing unit controls the acquisition unit to collect historical data and adjusts the number of detachable counterweights based on the historical data;

[0029] When the similarity is less than the similarity threshold, the processing unit controls the acquisition unit to collect the user's heart rate data and adjusts the number of detachable counterweights based on the heart rate data.

[0030] Furthermore, the historical data includes

[0031] Historical assist torque data, historical posture angle data, and historical movement speed data of users in different sports modes.

[0032] Further, when the similarity is less than the similarity threshold, the processing unit controls the acquisition unit to acquire the user's heart rate data, and when adjusting the number of detachable counterweights based on the heart rate data, the process includes:

[0033] The heart rate status is determined based on the heart rate data; the heart rate status includes high heart rate, low heart rate, and normal heart rate.

[0034] The amount of adjustment for each time the detachable counterweight is preset;

[0035] Calculate the difference between the heart rate data and the standard heart rate, and adjust the number of detachable counterweights based on the difference:

[0036] When the heart rate is high, the number of detachable counterweights is reduced according to the difference. At this time, the difference is multiplied by the adjustment amount to obtain the reduced number of detachable counterweights.

[0037] When the heart rate is low, the number of detachable counterweights is increased according to the difference. At this time, the difference is multiplied by the adjustment amount to obtain the increased number of detachable counterweights.

[0038] When the heart rate is normal, the number of detachable counterweights is not adjusted.

[0039] Compared with existing technologies, the advantages of this invention are as follows: The exoskeleton module provided by this invention monitors heart rate data in real time and makes dynamic adjustments, enabling it to better adapt to the user's physiological changes and provide more humanized assistance. This heart rate-based adjustment mechanism not only improves the user's exercise efficiency but also prevents sports injuries to a certain extent, ensuring that the user exercises within a safe range. By continuously optimizing the number of weight blocks, the exoskeleton module can provide users with a more comfortable and efficient wearing experience, further promoting the application of wearable devices in the fields of sports and rehabilitation.

[0040] In another aspect, the present invention also proposes a method for using an exoskeleton module, comprising the following steps:

[0041] S100: Real-time acquisition of the assisting torque generated by the detachable counterweight, establishment of an assisting torque set based on the assisting torque, and calculation of the rate of change of the assisting torque based on the assisting torque set;

[0042] S200: Compare the rate of change with a rate of change threshold, and determine whether to adjust the number of detachable counterweights based on the comparison result.

[0043] S300: When it is determined that the number of detachable counterweights needs to be adjusted, the determination unit controls the acquisition unit to acquire the user's posture angle and movement speed, and establishes a posture angle dataset and a movement speed dataset respectively based on the posture angle and movement speed; the posture angle dataset and the movement speed dataset are fused to obtain a fused dataset; the similarity between the fused dataset and the movement pattern template is calculated, the similarity is compared with a similarity threshold, and the number of detachable counterweights is adjusted according to the comparison result;

[0044] S400: When the similarity is less than the similarity threshold, control the acquisition unit to acquire the user's heart rate data, and adjust the number of detachable counterweights according to the heart rate data.

[0045] It is understandable that the exoskeleton modules and their usage methods described above have the same beneficial effects, and will not be elaborated upon here. Attached Figure Description

[0046] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0047] Figure 1 This is a schematic diagram of the overall structure of the exoskeleton module provided in an embodiment of the present invention;

[0048] Figure 2 This is a flowchart illustrating the method of using the exoskeleton module provided in an embodiment of the present invention.

[0049] In the diagram: 100, exoskeleton module body; 110, sensor group; 120, battery module; 130, drive assembly; 131, connecting rod; 132, detachable counterweight; 140, control module. Detailed Implementation

[0050] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art. It should be noted that, unless otherwise specified, embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0051] See Figure 1 As shown, in some embodiments of this application, this embodiment provides an exoskeleton module, including:

[0052] The exoskeleton module body 100, sensor group 110, battery module 120, drive assembly 130, and control module 140 are disposed inside the exoskeleton module body 100. The sensor group 110 includes an attitude sensor, a force sensor, and a heart rate sensor. The battery module 120 includes multiple battery units connected in series or parallel. The drive assembly 130 includes a drive motor, a connecting rod 131, and a detachable counterweight 132. The output end of the drive motor is perpendicularly connected to one end of the connecting rod 131, and the detachable counterweight 132 is connected to the other end of the connecting rod 131. The drive motor can drive the detachable counterweight 132 to perform non-uniform circular motion through the connecting rod 131. The control module 140 includes a data acquisition unit, a judgment unit, and a processing unit.

[0053] The acquisition unit is configured to acquire the assist torque generated by the detachable counterweight 132 in real time, establish an assist torque set based on the assist torque, and calculate the rate of change of the assist torque based on the assist torque set.

[0054] The judgment unit is configured to compare the rate of change with a rate of change threshold, and determine whether to adjust the number of detachable counterweights 132 based on the comparison result.

[0055] When it is determined that the number of detachable counterweights 132 needs to be adjusted, the determination unit controls the acquisition unit to collect the user's posture angle and movement speed, and establishes posture angle dataset and movement speed dataset respectively based on posture angle and movement speed; the posture angle dataset and movement speed dataset are fused to obtain a fused dataset; the similarity between the fused dataset and the movement pattern template is calculated, the similarity is compared with a similarity threshold, and the number of detachable counterweights 132 is adjusted according to the comparison result;

[0056] The processing unit is configured to control the acquisition unit to collect the user's heart rate data when the similarity is less than the similarity threshold, and adjust the number of detachable counterweights 132 according to the heart rate data.

[0057] As can be seen, in some embodiments of the present invention, the exoskeleton module includes an exoskeleton module body 100, a sensor group 110, a battery module 120, a drive component 130, and a control module 140. The exoskeleton module body 100 is the basic structure of the entire exoskeleton module, used to support other components; the sensor group 110 is used to monitor the user's physiological and movement status in real time, including key parameters such as posture, strength, and heart rate; the battery module 120 provides a continuous energy supply to the exoskeleton module, ensuring long-term operation; the drive component 130 assists the exoskeleton module through motors and counterweights, improving the wearer's movement efficiency.

[0058] As can be seen, the acquisition unit collects the assist torque generated by the user while wearing the exoskeleton module in real time. This data is crucial for optimizing the exoskeleton module's performance. The judgment unit makes intelligent decisions based on the collected data and preset thresholds to ensure that the exoskeleton module provides appropriate assistance in different movement modes. The processing unit further adjusts the number of weights based on the user's physiological data, such as heart rate. For example, if the user's heart rate is too high, indicating that the user may be fatigued, the processing unit will reduce the number of weights to reduce the user's burden. Conversely, if the user's heart rate is low and the posture angle and movement speed data indicate that the user can withstand greater assistance, the processing unit will increase the number of weights to improve exercise efficiency.

[0059] Specifically, when establishing a set of assist torques based on the assist torque, and calculating the rate of change of the assist torque based on the set of assist torques, the following steps are included:

[0060] The collected assist torques are recorded sequentially according to time.

[0061] Filter the concentrated assist torque to remove noise and outliers;

[0062] The rate of change of the assist torque is obtained by calculating the derivative of the assist torque with time using numerical differentiation methods.

[0063] It can be seen that recording the collected assist torque sequentially according to time can ensure the continuity and integrity of the data, which is convenient for subsequent analysis and processing; filtering can effectively improve the data quality and ensure that the calculation results of the rate of change are more accurate and reliable; the numerical differentiation method can accurately calculate the rate of change based on the trend of the assist torque over time, thus providing an important basis for decision-making by the judgment unit.

[0064] Specifically, when comparing the rate of change with a rate of change threshold, and determining whether to adjust the number of detachable counterweights 132 based on the comparison result, the following steps are taken:

[0065] When the rate of change is less than or equal to the rate of change threshold, the judgment unit determines that the number of detachable counterweights 132 should not be adjusted.

[0066] When the rate of change is greater than the rate of change threshold, the judgment unit determines to adjust the number of detachable counterweights 132.

[0067] As can be seen, when the rate of change exceeds the threshold, it indicates that the user may be experiencing strenuous exercise or requires additional assistance. At this point, the judgment unit will initiate an adjustment procedure. The specific adjustment process includes: First, the control unit collects the user's posture angle and movement speed, which are crucial for understanding the user's movement state. The fusion of the posture angle dataset and the movement speed dataset provides a more comprehensive analysis of movement patterns, thereby more accurately determining the user's current movement needs.

[0068] Specifically, when fusing the attitude angle dataset and the motion velocity dataset to obtain the fused dataset, the following steps are included:

[0069] Extract attitude feature data from the attitude angle dataset, which includes pitch angle, roll angle and yaw angle;

[0070] Extract motion feature data from the motion velocity dataset, which includes linear velocity and angular velocity;

[0071] The Kalman filter algorithm is used to fuse the attitude feature data and motion feature data to obtain a fused dataset.

[0072] Specifically, the sports mode templates include walking mode templates, running mode templates, and hill climbing mode templates.

[0073] It can be seen that the fused dataset processed by the Kalman filter algorithm can effectively reduce noise and errors, and improve data accuracy. The similarity calculation between the fused dataset and the motion pattern template is achieved by comparing the feature differences between the two.

[0074] Specifically, calculating the similarity between the fused dataset and the motion pattern template includes:

[0075] Similarity is obtained using the following formula:

[0076]

[0077] Where Di represents similarity, Fi represents the i-th feature value in the fused dataset, and T i,j This represents the j-th feature value of different types of motion pattern templates.

[0078] Specifically, when comparing the similarity with a similarity threshold and adjusting the number of detachable counterweights 132 based on the comparison results, the following steps are taken:

[0079] When the similarity is greater than or equal to the similarity threshold, the processing unit controls the acquisition unit to collect historical data and adjusts the number of detachable counterweights 132 based on the historical data.

[0080] When the similarity is less than the similarity threshold, the processing unit controls the acquisition unit to collect the user's heart rate data and adjusts the number of detachable counterweights 132 according to the heart rate data.

[0081] Specifically, historical data includes historical assist torque data, historical posture angle data, and historical movement speed data for users in different sports modes.

[0082] It is evident that the collection and analysis of historical data is crucial for optimizing the performance of exoskeleton modules. By analyzing historical assist torque data, historical posture angle data, and historical movement speed data of users in different movement modes, a more accurate understanding of users' movement habits and needs can be achieved. For example, if historical data shows that users frequently require additional assistance in specific movement modes, the processing unit can adjust the number of weights accordingly to provide more suitable assistance.

[0083] Specifically, when the similarity is less than the similarity threshold, the processing unit controls the acquisition unit to collect the user's heart rate data. When adjusting the number of detachable counterweights 132 based on the heart rate data, the following steps are taken:

[0084] Heart rate status is determined based on heart rate data; heart rate status includes high heart rate, low heart rate, and normal heart rate.

[0085] The amount of adjustment for each time of the detachable counterweight 132 is preset;

[0086] Calculate the difference between the heart rate data and the standard heart rate, and adjust the number of detachable weights 132 based on the difference:

[0087] When the heart rate is high, the number of detachable counterweights 132 is reduced according to the difference. At this time, the difference is multiplied by the number to be adjusted to obtain the number of detachable counterweights 132 that have been reduced.

[0088] When the heart rate is low, the number of detachable counterweights 132 is increased according to the difference. At this time, the difference is multiplied by the adjustment number to obtain the increased number of detachable counterweights 132.

[0089] When the heart rate is at a normal heart rate, the number of detachable counterweights 132 is not adjusted.

[0090] It can be seen that adjusting the number of weights based on heart rate data can more personally meet the user's physiological needs. Heart rate, as an important indicator of a user's physical state, directly indicates the user's current exercise intensity and fatigue level. When a user's heart rate is high, it indicates that the user may be experiencing high-intensity exercise or physical fatigue. In this case, reducing the number of weights can reduce the user's burden and prevent overexertion. Conversely, when a user's heart rate is low, it may mean that the user's exercise intensity is low. In this case, increasing the number of weights can provide more assistance and help the user complete the exercise task more effectively. When the heart rate is within the normal range, keeping the number of weights constant can maintain the user's current exercise state and level of assistance.

[0091] Understandably, by monitoring heart rate data in real time and making dynamic adjustments, exoskeleton modules can better adapt to users' physiological changes and provide more humanized support. This heart rate-based adjustment mechanism not only improves users' exercise efficiency but also helps prevent sports injuries to some extent, ensuring that users exercise within a safe range. By continuously optimizing the number of weights, exoskeleton modules can provide users with a more comfortable and efficient wearing experience, further promoting the application of wearable devices in the fields of sports and rehabilitation.

[0092] See Figure 2 As shown, in some embodiments of this application, this embodiment provides a method for using an exoskeleton module, including the following steps:

[0093] S100: Real-time acquisition of the assisting torque generated by the detachable counterweight, establishment of an assisting torque set based on the assisting torque, and calculation of the rate of change of the assisting torque based on the assisting torque set;

[0094] S200: Compare the rate of change with a rate of change threshold, and determine whether to adjust the number of detachable counterweights based on the comparison result.

[0095] S300: When it is determined that the number of detachable counterweights needs to be adjusted, the determination unit controls the acquisition unit to acquire the user's posture angle and movement speed, and establishes a posture angle dataset and a movement speed dataset respectively based on the posture angle and movement speed; the posture angle dataset and the movement speed dataset are fused to obtain a fused dataset; the similarity between the fused dataset and the movement pattern template is calculated, the similarity is compared with a similarity threshold, and the number of detachable counterweights is adjusted according to the comparison result;

[0096] S400: When the similarity is less than the similarity threshold, control the acquisition unit to acquire the user's heart rate data, and adjust the number of detachable counterweights according to the heart rate data.

[0097] It is evident that by monitoring heart rate data in real time and making dynamic adjustments, the exoskeleton module can better adapt to the user's physiological changes, providing more humanized assistance. This heart rate-based adjustment mechanism not only improves the user's exercise efficiency but also, to some extent, prevents sports injuries, ensuring that the user exercises within a safe range. By continuously optimizing the number of weights, the exoskeleton module can provide users with a more comfortable and efficient wearing experience, further promoting the application of wearable devices in the fields of sports and rehabilitation.

[0098] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods 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.

[0099] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. 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... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] 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.

[0101] 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 1The steps of the function specified in one or more boxes.

[0102] 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 module, characterized by, The external skeleton module body, a sensor group, a battery module, a driving assembly and a control module are arranged inside the external skeleton module body; the sensor group includes a posture sensor, a force sensor and a heart rate sensor; the battery module includes a plurality of battery units connected in series or in parallel; the driving assembly includes a driving motor, a connecting rod and a detachable counterweight, one end of the connecting rod is connected with the output end of the driving motor in a vertical manner, the other end of the connecting rod is connected with the detachable counterweight, and the driving motor can drive the detachable counterweight to move in a non-uniform speed circular motion through the connecting rod; the control module includes an acquisition unit, a judgment unit and a processing unit; The acquisition unit is configured to acquire a power torque generated by the detachable counterweight in real time, establish a power torque set according to the power torque, and calculate a change rate of the power torque according to the power torque set; The judgment unit is configured to compare the change rate with a change rate threshold, and judge whether to adjust the number of the detachable counterweights according to a comparison result: When it is determined to adjust the number of the detachable counterweights, the judgment unit controls the acquisition unit to acquire a posture angle and a movement speed of a user, establishes a posture angle data set and a movement speed data set according to the posture angle and the movement speed respectively, fuses the posture angle data set and the movement speed data set to obtain a fused data set, calculates a similarity between the fused data set and a movement mode template, compares the similarity with a similarity threshold, and adjusts the number of the detachable counterweights according to a comparison result; The processing unit is configured to control the acquisition unit to acquire heart rate data of the user when the similarity is less than the similarity threshold, and adjust the number of the detachable counterweights according to the heart rate data. When the power torque set is established according to the power torque, and the change rate of the power torque is calculated according to the power torque set, the following steps are included:

2. The exoskeleton module according to claim 1, characterized in that, The acquired power torque is recorded in sequence according to time; The power torque in the power torque set is filtered to remove noise and abnormal values; The derivative of the power torque with respect to time is calculated by a numerical differentiation method to obtain the change rate. When the change rate is compared with the change rate threshold, and whether to adjust the number of the detachable counterweights is judged according to a comparison result, the following steps are included:

3. The exoskeleton module of claim 2, wherein, When the change rate is less than or equal to the change rate threshold, the judgment unit determines not to adjust the number of the detachable counterweights; When the change rate is greater than the change rate threshold, the judgment unit determines to adjust the number of the detachable counterweights. When the posture angle data set and the movement speed data set are fused to obtain a fused data set, the following steps are included:

4. The exoskeleton module of claim 3, wherein, Posture feature data in the posture angle data set is extracted, and the posture feature data includes a pitch angle, a roll angle and a yaw angle; ​ extracting motion feature data in the motion speed dataset, the motion feature data including linear speed and angular speed; fusing the attitude feature data and the motion feature data by using a Kalman filtering algorithm to obtain the fused dataset.

5. The exoskeleton module of claim 4, wherein, The motion mode template includes a walking mode template, a running mode template, and a climbing mode template.

6. The exoskeleton module of claim 5, wherein, When calculating the similarity between the fused dataset and the motion mode template, the following is included: The similarity is obtained by the following formula: Wherein, Di represents the similarity, Fi represents the i-th feature value in the fusion data set, T i,j represents the j-th feature value of the motion mode template of different types.

7. The exoskeleton module of claim 6, wherein, When comparing the similarity with a similarity threshold value, and adjusting the number of detachable weight blocks according to the comparison result, the following is included: When the similarity is greater than or equal to the similarity threshold value, the processing unit controls the acquisition unit to acquire historical data, and adjusts the number of detachable weight blocks according to the historical data; When the similarity is less than the similarity threshold value, the processing unit controls the acquisition unit to acquire heart rate data of the user, and adjusts the number of detachable weight blocks according to the heart rate data.

8. The exoskeleton module of claim 7, wherein, The historical data includes historical assist torque data, historical attitude angle data, and historical motion speed data of the user under different motion modes.

9. The exoskeleton module of claim 7, wherein, When the similarity is less than the similarity threshold value, the processing unit controls the acquisition unit to acquire heart rate data of the user, and adjusts the number of detachable weight blocks according to the heart rate data, the following is included: determining a heart rate state according to the heart rate data; the heart rate state includes high heart rate, low heart rate, and normal heart rate; pre-setting an adjustment amount of the detachable weight blocks each time; calculating a difference value between the heart rate data and a standard heart rate, and adjusting the number of detachable weight blocks according to the difference value: When the heart rate state is high heart rate, the number of detachable weight blocks is adjusted downward according to the difference value, and the difference value is multiplied by the adjustment amount to obtain the adjusted number of detachable weight blocks; When the heart rate state is low heart rate, the number of detachable weight blocks is adjusted upward according to the difference value, and the difference value is multiplied by the adjustment amount to obtain the adjusted number of detachable weight blocks; When the heart rate state is normal heart rate, the number of detachable weight blocks is not adjusted.

10. A method for using an exoskeleton module, applied to the exoskeleton module according to any one of claims 1-9, characterized in that, including: acquiring an assist torque generated by the detachable weight blocks in real time, establishing an assist torque set according to the assist torque, and calculating a change rate of the assist torque according to the assist torque set; comparing the change rate with a change rate threshold value, and determining whether to adjust the number of detachable weight blocks according to the comparison result: When it is determined to adjust the number of detachable weight blocks, the determination unit controls the acquisition unit to acquire an attitude angle and a motion speed of the user, establishes an attitude angle dataset and a motion speed dataset according to the attitude angle and the motion speed respectively, fuses the attitude angle dataset and the motion speed dataset to obtain a fused dataset, calculates a similarity between the fused dataset and a motion mode template, compares the similarity with a similarity threshold value, and adjusts the number of detachable weight blocks according to the comparison result. When the similarity is less than the similarity threshold, controlling the acquisition unit to acquire heart rate data of the user, and adjusting the number of detachable counterweights according to the heart rate data.

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