Method and system for evaluating the performance of lower limb-assisted exoskeleton based on continuous stair-climbing gait

Abstract

The present invention discloses a method and system for evaluating the performance of a lower limb power-assisted exoskeleton based on a continuous stair-climbing gait. The method includes performing a continuous stair-climbing test on a number of test subjects, and each test subject performs a continuous stair-climbing test with and without an exoskeleton, wherein the continuous stair-climbing test includes multiple complete stair-climbing gait cycles, wherein the stair-climbing gait cycle includes a first double-support period, a single-support period, a second double-support period, and a swing period; muscle activity data and metabolic cost data of the continuous stair-climbing test with and without an exoskeleton are collected; statistical data processing is performed on the collected muscle activity data and metabolic cost data; and the processed data is analyzed to draw conclusions. The power consumption reduction ratio and power-assisted efficiency of the power-assisted exoskeleton are calculated by analyzing the test subject's electromyographic signal, oxygen consumption, and carbon dioxide exhalation, and a comprehensive evaluation of the exoskeleton's performance is performed. The evaluation method is accurate, stable, simple, and easy to implement.

Description

Technical Field

[0001] The present invention relates to a method and a system for evaluating the energy efficiency of a lower limb power-assisting exoskeleton on a human body in a continuous stair-climbing gait. Background Art

[0002] The lower limb assist exoskeleton is a wearable mechanical device that is connected in parallel to the lower limbs of the human body. It can be used to enhance or restore the body's motor ability. It can also be used for gait rehabilitation for patients with knee dysfunction. It can follow the body's movement intentions and assist or support the lower limbs. The current active lower limb assist exoskeleton is still in the laboratory stage.

[0003] In the prior art, the degree of assistance of lower limb exoskeleton is usually tested by calculating the torque at the lower limb joints. For example, a three-link model of the human lower limbs is constructed through a three-dimensional motion capture system and a three-dimensional force plate, and then the joints and joint torques of the human body are solved. In this process, it is necessary to collect information such as the surface electromyography signals, plantar pressure, and lower limb movement status of the subject (or wearer).

[0004] However, since human muscles are flexible and the exoskeleton assists when interacting with the human body, there will be a delay in the assist effect of the exoskeleton. In other words, the torque calculation at the lower limb joints is only a prediction of the degree or effect of the exoskeleton assist, and does not directly reflect the assist effect of the exoskeleton on the lower limbs of the subject during the test period. In addition, this method requires the collection of multiple parameters and the solution of multiple models and equations, which is complicated to operate. Moreover, since multiple parameters need to be collected (for example, electromyographic signals, plantar pressure, etc.), the corresponding supporting testing facilities are also numerous, resulting in high testing costs, which is not conducive to widespread application.

[0005] In addition, the prior art also tests the assistance effect by testing metabolic costs. However, when the base of the subject's metabolic cost is relatively small, the error in the test process may be relatively large, thereby reducing the reliability of the test results.

[0006] Although lower limb assisted exoskeletons have become one of the current research hotspots, there is no unified testing standard for the performance evaluation method of lower limb assisted exoskeletons. Summary of the invention

[0007] In view of this, the present invention provides a method and system for evaluating the performance of a lower limb assisted exoskeleton based on a continuous stair-climbing gait, which are used to uniformly and accurately evaluate the performance of a lower limb assisted exoskeleton.

[0008] In order to solve the above technical problems, the technical solution of the present invention is to adopt a method for evaluating the performance of lower limb assisted exoskeleton based on continuous stair-climbing gait, including: performing a continuous stair-climbing test on a number of testers, and each tester performs a continuous stair-climbing test with and without an exoskeleton, the continuous stair-climbing test including a plurality of complete stair-climbing gait cycles, the stair-climbing gait cycle including a first double support period, a single support period, a second double support period and a swing period; collecting muscle activity data and metabolic cost data of the continuous stair-climbing test with and without an exoskeleton; and performing statistical data processing on the collected muscle activity data and metabolic cost data.

[0009] The use of myoelectric signal reduction ratio to evaluate exoskeleton assistance has a high degree of accuracy. The reason is that human muscles are flexible, and exoskeleton assistance occurs when interacting with the human body, so there will be a delay in assistance. The calculation of the torque at the joint is only a pre-judgment evaluation of the exoskeleton assistance, while the actual assistance effect of the exoskeleton is more direct and accurate from the physiological reaction. To evaluate whether the exoskeleton produces assistance, it mainly depends on whether the exoskeleton reduces the local muscle force required to complete the same action and whether the overall metabolic cost is reduced.

[0010] In addition, compared with walking on flat roads and steep slopes, the range of variation of the angle of motion of the lower limb joints of the human body in the stair-climbing gait is larger, and the force characteristics of the core muscles of each part are more obvious, which can better highlight the performance of the exoskeleton in assisting the core muscles. Secondly, the continuous stair-climbing gait requires lifting one's own weight, and the comprehensive energy consumption is much greater than walking on flat roads and steep slopes. In the comprehensive metabolic cost test, it can effectively avoid the problem of large measurement errors caused by a small base.

[0011] As an improvement, the test subjects are all males aged 20 to 30 years old.

[0012] As a further improvement, the average speed during the continuous stair climbing test with and without the exoskeleton was about 40 to about 70 steps / min, and the step height was about 15 to about 30 cm.

[0013] As another further improvement, both the continuous stair-climbing test with and without an exoskeleton needs to be performed after fatigue is completely eliminated.

[0014] As an improvement, the interval between the continuous stair climbing test with wearing an exoskeleton and the continuous stair climbing test without wearing an exoskeleton is greater than about 2 hours.

[0015] As an improvement, the continuous stair climbing test with and without the exoskeleton lasted for 5 to 15 minutes.

[0016] As an improvement, the muscle activity data are electromyographic signals of the tester's lower limb muscles (including: the tester's left and right lower limb thigh muscle groups and calf muscle groups); the metabolic cost data are oxygen consumption and carbon dioxide exhalation.

[0017] As an improvement, a surface electromyography tester is used to collect muscle activity data; before the test, impurities on the surface of the test muscle are removed and the electrode sheet is fixed along the direction of the muscle.

[0018] As an improvement, in the statistical data processing of the collected muscle activity data, the collected electromyographic signals are filtered, rectified and root mean square value preprocessed to obtain the first electromyographic signal data; data statistics are performed on the first electromyographic signal data to obtain the second electromyographic signal data; and the second electromyographic signal data is normalized.

[0019] As an improvement, using the formula

[0020]

[0021] The second electromyographic signal is normalized; wherein sEMG% is the electromyographic amplitude after normalization, sEMG_i is the peak value of the electromyographic signal of the corresponding muscle in each step-up gait cycle, and sEMG_MAX is the maximum value of the peak values ​​of the electromyographic signal of the corresponding muscle.

[0022] As a modification, the oxygen consumption and carbon dioxide exhalation are recorded during the last about 1 to about 3 minutes of the test.

[0023] As an improvement, in the statistical data processing of the collected metabolic cost data, the formula

[0024] H=(14.48VO 2 +4.48VCO 2 ) / 60

[0025] Calculate the average energy consumption power of each tester during the continuous step-up test, where H is the average energy consumption power in W / kg; VO 2 VCO is oxygen consumption, in ml / min / kg; 2 It is the amount of carbon dioxide exhaled, and its unit is ml / min / kg.

[0026] As an improvement, the method further includes the steps of: analyzing the processed data to draw conclusions; the analysis of the processed data includes: performing a paired sample t-test on the electromyographic signal of each test subject to obtain the P value, t value and assistance efficiency; performing a paired sample t-test on the average power consumption of each test subject to obtain the P value, t value and power consumption reduction ratio.

[0027] As an improvement, using the formula

[0028]

[0029] Calculate the power efficiency of the lower limb power exoskeleton; where η a To help efficiency, E a1 is the normalized electromyographic amplitude without exoskeleton, E a2 It is the normalized electromyographic amplitude when wearing the exoskeleton.

[0030] As an improvement, using the formula

[0031]

[0032] Calculate the power consumption reduction ratio of the lower limb power-assisted exoskeleton; where η b To reduce the ratio, E b1 is the average energy consumption power without exoskeleton, E b2 is the average energy consumption when wearing the exoskeleton.

[0033] As an improvement, the processed data is analyzed to draw conclusions.

[0034] If the t-test of the electromyographic signal test results and the t-test of the metabolic cost test results both meet P≤0.05&t<0, then the lower limb assist exoskeleton can alleviate local muscle fatigue damage and reduce muscle activity, while reducing metabolic costs and improving the efficiency of continuous stair climbing;

[0035] If the t-test of the electromyographic signal test result satisfies P≤0.05&t<0 but the t-test of the metabolic cost test result does not satisfy P≤0.05&t<00, then the lower limb assist exoskeleton can effectively alleviate local muscle fatigue damage and reduce muscle activity, but cannot significantly reduce the metabolic cost of continuous stair climbing;

[0036] If the t-test of the metabolic cost test result satisfies P≤0.05&t<0 but the t-test of the electromyography signal test result does not satisfy P≤0.05&t<0, then the exoskeleton can significantly reduce the metabolic cost η when climbing stairs continuously, but does not provide significant assistance to the muscles of the test site.

[0037] If the electromyographic signal measurement results and the metabolic cost test results do not satisfy P≤0.05&t<0, the lower limb power-assisted exoskeleton cannot provide assistance for continuous stair climbing.

[0038] The present invention also provides a lower limb assisted exoskeleton performance evaluation system based on continuous step-climbing gait, comprising: a muscle activity data acquisition unit, used to collect electromyographic signals of the lower limb muscles of the tester during the test (for example, the thigh muscle groups and calf muscle groups of the left and right lower limbs of the tester); a metabolic cost data acquisition unit, used to collect the oxygen consumption and carbon dioxide exhalation of the tester during the test; a statistical data processing unit, which performs statistical data processing on the collected electromyographic signals of the lower limb muscles of the tester and the collected oxygen consumption and carbon dioxide exhalation of the tester; a data analysis unit, which analyzes the statistically processed data and draws conclusions; the data analysis unit is connected to the statistical data processing unit.

[0039] The benefit of the present invention lies in that the power consumption reduction ratio and power-assisting efficiency of the power-assisted exoskeleton are calculated by analyzing the test subject's electromyographic signals, oxygen consumption, and carbon dioxide exhalation, thereby conducting a comprehensive evaluation of the exoskeleton's performance.

[0040] Compared with the prior art, the present invention only needs to collect the tester's electromyographic signal and metabolic cost data, and directly evaluates the exoskeleton's assistance effect by the reduction ratio of the electromyographic signal and whether the comprehensive metabolic cost is reduced, which is more accurate. And because only the electromyographic signal and metabolic cost data need to be tested, the matching test equipment only needs two acquisition units (muscle activity data acquisition unit and metabolic cost data acquisition unit) to complete the collection of test data, thereby simplifying the test equipment, thereby simplifying the test operation steps, and reducing the test cost.

[0041] Oxygen consumption can reflect the metabolic cost of the tester during the test, and the electromyographic signal can characterize the muscle fatigue damage or muscle activity of the tester during the test. It is generally believed that the lower the electromyographic signal and oxygen consumption, the better the power-assisting effect of the exoskeleton. However, the change relationship between the electromyographic signal and oxygen consumption of each muscle group of the lower limb muscles is not positively correlated. That is to say, when the electromyographic signal of one or more muscle groups of the lower limb muscles is significantly reduced, the oxygen consumption may not necessarily be significantly reduced, or when the oxygen consumption is reduced, the electromyographic signal of each muscle group in the lower limb may not necessarily be significantly reduced. Therefore, in order to ensure the reliability and accuracy of the power-assisting evaluation results, the present invention characterizes the degree of power-assisting of the exoskeleton by combining the test results of metabolic cost and muscle activity.

[0042] Furthermore, since the lower limb muscles include hip muscles, thigh muscles, calf muscles and foot muscles, by collecting electromyographic signals from different parts of the tester's lower limbs, the degree of assistance provided by the exoskeleton to each joint of the lower limbs (for example, hip joints, knee joints, ankle joints) can be further explored, and the corresponding evaluation results can be fed back to the design of the lower limb exoskeleton, which is of great significance for the research on the assistance mechanism and structural design of lower limb exoskeletons such as hip joint assistance exoskeleton, knee joint assistance exoskeleton and ankle main exoskeleton. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Schematic diagram of the step-climbing gait cycle;

[0044] Figure 2 is a flow chart of the present invention;

[0045] Figure 3 It is a structural principle diagram of the present invention;

[0046] Figure 4 A schematic diagram of a continuous stair climbing test of a lower limb exoskeleton in an exemplary embodiment of the present invention;

[0047] Figure 5 A schematic diagram of an exemplary lower limb exoskeleton test and evaluation process of the present invention. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with specific implementation methods.

[0049] Herein, the terms "about" and "approximately" are typically expressed as + / -5% of the value, more typically + / -4% of the value, more typically + / -3% of the value, more typically + / -2% of the value, even more typically + / -1% of the value, even more typically + / -0.5% of the value, or indicate a value that is understood by those skilled in the art to include the customary range of error in the art.

[0050] In this specification, some embodiments may be disclosed in a format of being in a certain range. It should be understood that such description of "being in a certain range" is only for convenience and brevity, and should not be interpreted as a rigid limitation on the disclosed range. Therefore, the description of the range should be considered to have specifically disclosed all possible sub-ranges and independent numerical values ​​within this range.

[0051] For example, the description of "about 15 cm to about 30 cm" should be considered to have specifically disclosed sub-ranges such as from 15 cm to 20 cm, 19 cm to 28 cm, 25 cm to 30 cm and individual numbers within this range, for example, 15 cm, 18 cm, 26 cm, 30 cm. For another example, the description of "greater than about 2 h" should be considered to have disclosed a range equal to 2 h. Regardless of the breadth of the range, the above rules apply.

[0052] like Figure 1As shown, the dotted line is the left leg and the solid line is the right leg. The complete stair-climbing gait cycle includes the first double support period, the single support period, the second double support period and the swing period. The first double support period: the foot of the supporting leg (left foot) begins to touch the first step. At this time, the left leg begins to bear the weight, and the lower limb on the main supporting side bears the weight transmitted by the posterior limb. Single support period: the supporting leg (left leg) begins to continue supporting, the foot of the swinging leg (right foot) leaves the ground, and the body moves forward steadily to the supporting side limb, accompanied by the lifting of the body. The second double support period: the foot of the swinging leg (right foot) begins to touch the second step, until the foot of the supporting leg (left foot) is about to leave the first step, and the center of gravity of the body is transferred from the supporting leg (left foot) to the swinging leg (right foot). Swing period: the foot of the supporting leg (left foot) leaves the first step until it touches the third step. In the present invention, it is necessary to collect data of several stair-climbing gait cycles of the test subject.

[0053] In addition, the evaluation method provided by the present invention is applicable to lower limb assisted exoskeletons, including hip assisted exoskeletons, knee assisted exoskeletons and ankle assisted exoskeletons. Hip assisted exoskeleton: The main assisted joint is the hip joint. The exoskeleton is driven by elastic elements or motors to help the wearer's hip joint extend and flex, providing auxiliary torque for the hip joint. Knee assisted exoskeleton: The main assisted joint is the knee joint. The exoskeleton is driven by elastic elements or motors to help the wearer's thigh and calf exert force, and actively assist the knee joint extension process. Ankle assisted exoskeleton: The main assisted joint is the ankle joint. The exoskeleton is driven by elastic elements or motors to actively assist the wearer's ankle plantar / dorsiflexion.

[0054] like Figure 2 and Figure 5 As shown, the method for evaluating the performance of a lower limb-assisted exoskeleton based on a continuous stair-climbing gait provided by the present invention includes:

[0055] S1 conducted a continuous stair climbing test on several test subjects, and each test subject performed the continuous stair climbing test with and without the exoskeleton. The continuous stair climbing test included multiple complete stair climbing gait cycles, and the stair climbing gait cycle included the first double support period, the single support period, the second double support period, and the swing period.

[0056] The test subjects are healthy male adults aged 20 to 30 years old, who have not reported any musculoskeletal diseases in the three months before the test. Before the test, the experimenters will first conduct training on wearing and using the exoskeleton, and all test items will be informed to the subjects in advance. Figure 4, the continuous stair climbing gait is simulated by a stair machine. In this embodiment, the step height of the stair machine is between about 15cm and about 30cm, and the width and length are not limited. The speed of the stair machine can be set to adjust the test evaluation. In this embodiment, the average speed is about 40 steps / min to about 70 steps / min. Before the test, the experimenter first debugs the equipment, and then assists the subject to wear the experimental equipment and the exoskeleton. Both the continuous stair climbing test wearing the exoskeleton and the continuous stair climbing test without the exoskeleton need to be carried out after completely eliminating fatigue. In this embodiment, the subject is required to walk on the stair machine for about 5 minutes to about 15 minutes when wearing the exoskeleton. For example, the subject is required to walk on the stair machine for about 10 minutes when wearing the exoskeleton, and then walk on the stair machine for about 10 minutes without the exoskeleton after a good rest (the interval time is greater than about 2 hours).

[0057] S2 collects muscle activity data and metabolic cost data of continuous step-up tests with and without the exoskeleton; the muscle activity data are the electromyographic signals of the test subject's lower limb muscles (including the left and right lower limb thigh muscles and calf muscles) in the two tests, collected using a surface electromyography tester; before the test, impurities on the surface of the tested muscle parts are removed, and the electrode sheets are fixed along the muscle direction. The metabolic cost data are the oxygen consumption and carbon dioxide exhalation in the two tests, recording the oxygen consumption and carbon dioxide exhalation of each test subject in the last approximately 1 minute to approximately 3 minutes of the test process.

[0058] S3 performs statistical data processing on the collected muscle activity data and metabolic cost data.

[0059] The collected electromyographic signal is filtered (20 Hz-300 Hz), rectified and pre-processed by root mean square value (RMS, 500 ms) to obtain first electromyographic signal data;

[0060] Performing data statistics on the first electromyographic signal data to obtain second electromyographic signal data;

[0061] The second electromyographic signal data is normalized. Specifically, the formula

[0062]

[0063] The second electromyographic signal is normalized; wherein sEMG% is the electromyographic amplitude after normalization, sEMG_i is the peak value of the electromyographic signal of the corresponding muscle of the tester in each step-up gait cycle, and sEMG_MAX is the maximum value of the peak values ​​of the electromyographic signals of the corresponding muscle of the tester in all step-up gait cycles.

[0064] Using the formula

[0065] H=(14.48VO 2+4.48VCO 2 ) / 60

[0066] Calculate the average energy consumption power of each tester during the continuous step-up test, where H is the average energy consumption power in W / kg; VO 2 VCO is oxygen consumption, in ml / min / kg; 2 It is the amount of carbon dioxide exhaled, and its unit is ml / min / kg.

[0067] The first electromyographic signal data refers to the original electromyographic signal after preprocessing. Due to the presence of noise and other factors, the original electromyographic signal is not accurate for direct comparison and analysis. Therefore, the original signal is usually band-pass filtered (low frequency threshold 20Hz, high frequency threshold 300Hz), positive rectification (the original signal is an oscillating signal near 0V), and root mean square smoothing (RMS processing, smoothing time window is 500ms).

[0068] The second electromyographic signal data refers to the first electromyographic signal after preprocessing. Each muscle has a force peak in each step-up gait cycle. Because the test is a continuous gait test, the data sample is obtained by statistically analyzing each muscle's gait peak. This is the second electromyographic signal data. sEMG_MAX is the maximum value of the statistical peak value of each muscle, which is used for normalization processing to eliminate individual differences among subjects due to physical factors.

[0069] S4 analyzes the processed data and draws conclusions.

[0070] A paired sample t-test was performed on the electromyographic signals of each test subject in the two tests to obtain the P value, t value, and power efficiency. Similarly, a paired sample t-test was performed on the average power consumption of each test subject in the two tests to obtain the P value, t value, and power consumption reduction ratio.

[0071] P ≤ 0.05 indicates a significant difference, and t value (exoskeleton-no exoskeleton) less than 0 indicates that the exoskeleton can significantly reduce muscle activity in the test area. P value and t value are obtained by paired sample t test analysis using SPSS software.

[0072] The conclusion is as follows:

[0073] If the t-test of the electromyographic signal test results and the t-test of the metabolic cost test results both meet P≤0.05&t<0, then the lower limb assist exoskeleton can alleviate local muscle fatigue damage and reduce muscle activity, while reducing metabolic costs and improving the efficiency of continuous stair climbing;

[0074] If the t-test of the electromyographic signal test result satisfies P≤0.05&t<0 but the t-test of the metabolic cost test result does not satisfy P≤0.05&t<00, then the lower limb assist exoskeleton can effectively alleviate local muscle fatigue damage and reduce muscle activity, but cannot significantly reduce the metabolic cost of continuous stair climbing;

[0075] If the t-test of the metabolic cost test result satisfies P≤0.05&t<0 but the t-test of the electromyography signal test result does not satisfy P≤0.05&t<0, then the exoskeleton can significantly reduce the metabolic cost η when climbing stairs continuously, but does not provide significant assistance to the muscles of the test site.

[0076] If the electromyographic signal measurement results and the metabolic cost test results do not satisfy P≤0.05&t<0, the lower limb power-assisted exoskeleton cannot provide assistance for continuous stair climbing.

[0077] In addition, using the formula Calculate the power efficiency of the lower limb power exoskeleton; where η a To help efficiency, E a1 is the normalized electromyographic amplitude without exoskeleton, E a2 It is the normalized electromyographic amplitude when wearing the exoskeleton.

[0078] You can also use the formula Calculate the power consumption reduction ratio of the lower limb power-assisted exoskeleton; where η b To reduce the ratio, E b1 is the average energy consumption power without exoskeleton, E b2 is the average energy consumption when wearing the exoskeleton.

[0079] like Figure 3 As shown, the present invention also provides a lower limb assisted exoskeleton performance evaluation system based on continuous step-ascending gait, including: a muscle activity data acquisition unit, used to collect the electromyographic signals of the lower limb muscles of the tester during the test (specifically, including the thigh muscle groups and calf muscle groups of the left and right lower limbs of the tester); a metabolic cost data acquisition unit, used to collect the oxygen consumption and carbon dioxide exhalation of the tester during the test; a statistical data processing unit, which performs statistical data processing on the collected electromyographic signals of the lower limb muscles of the tester and the collected oxygen consumption and carbon dioxide exhalation of the tester; a data analysis unit, which analyzes the statistically processed data and draws conclusions; the data analysis unit is connected to the statistical data processing unit.

[0080] The above are only preferred embodiments of the present invention. It should be noted that the above preferred embodiments should not be regarded as limiting the present invention, and the protection scope of the present invention should be based on the scope defined by the claims. For ordinary technicians in this technical field, several improvements and modifications can be made without departing from the spirit and scope of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention.

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Claims

1. A method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait, characterized in that include: Conduct a continuous stair climbing test on several test subjects, and each test subject performs the continuous stair climbing test with and without the exoskeleton; The continuous stair climbing test includes multiple complete stair climbing gait cycles, and the stair climbing gait cycle includes a first double support period, a single support period, a second double support period and a swing period; the continuous stair climbing test with an exoskeleton and the continuous stair climbing test without an exoskeleton both last for 5 minutes to 15 minutes; Collect muscle activity data and metabolic cost data of continuous step-climbing tests with and without the exoskeleton; the muscle activity data is the electromyographic signals of the lower limb muscles of the tester in the continuous step-climbing test; The metabolic cost data are the oxygen consumption and carbon dioxide exhalation of the test subject during the last 1 to 3 minutes of the continuous step-climbing test; Performing statistical data processing on the collected muscle activity data and metabolic cost data; Using the formula Calculate the power-assisting efficiency of the lower limb power-assisting exoskeleton in continuous stair-climbing gait; To help improve efficiency, is the normalized electromyographic amplitude without exoskeleton, is the normalized electromyographic amplitude when wearing the exoskeleton; Using the formula Calculate the power consumption reduction ratio of the lower limb power-assisted exoskeleton during continuous stair-climbing gait; To reduce the ratio, is the average energy consumption power without exoskeleton, is the average energy consumption when wearing the exoskeleton.

2. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 1, characterized in that: The average speed of continuous stair climbing tests with and without the exoskeleton was about 40 steps / min to about 70 steps / min, and the step height was between about 15 cm and about 30 cm.

3. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 1, characterized in that: Both the continuous stair climbing test with and without an exoskeleton need to be performed after fatigue is completely eliminated.

4. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 3, characterized in that: The interval between the continuous stair climbing test with the exoskeleton worn and the continuous stair climbing test without the exoskeleton worn was greater than approximately 2 hours.

5. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 1, characterized in that: The muscle activity data is collected using a surface electromyography tester; before testing, impurities on the surface of the tested muscle are removed and the electrode sheet is fixed along the direction of the muscle.

6. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 1 is characterized in that In the statistical data processing of the collected muscle activity data, the collected electromyographic signal is filtered, rectified and preprocessed with a root mean square value to obtain first electromyographic signal data; Performing data statistics on the first electromyographic signal data to obtain second electromyographic signal data; The second electromyographic signal data is normalized.

7. The method for evaluating the performance of a lower limb-assisted exoskeleton based on a continuous stair-climbing gait according to claim 6 is characterized in that Using the formula ； The second electromyographic signal data is normalized; wherein is the normalized EMG amplitude, is the peak value of the electromyographic signal of the corresponding muscle in each step-up gait cycle, is the maximum value of the peak value of the electromyographic signal of the corresponding muscle.

8. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 1, characterized in that: Record the oxygen consumption and carbon dioxide exhaled during the last approximately 1 minute to approximately 3 minutes of the test.

9. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 1 is characterized in that In the statistical data processing of the collected metabolic cost data, the formula is used ； Calculate the average energy consumption power of each tester during the continuous step-ascending test, where H is the average energy consumption power, in W / kg; VO2 is the oxygen consumption, in ml / min / kg; VCO2 is the exhaled carbon dioxide, in ml / min / kg.

10. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 8, characterized in that It also includes the steps of: analyzing the processed data to draw conclusions; Among them, the step of analyzing the processed data includes: performing a paired sample t-test on the electromyographic signal of each tester to obtain the P value, t value and assistance efficiency; performing a paired sample t-test on the average power consumption of each tester to obtain the P value, t value and power consumption reduction ratio.

11. The method for evaluating the performance of a lower limb-assisted exoskeleton based on continuous stair-climbing gait according to claim 10, characterized in that The analysis of the processed data leads to the conclusion that If the t-test of the electromyographic signal test results and the t-test of the metabolic cost test results both meet P≤0.05 & t<0, then the lower limb assist exoskeleton can alleviate local muscle fatigue damage and reduce muscle activity, while reducing metabolic costs and improving the efficiency of continuous stair climbing; If the t-test of the electromyographic signal test result satisfies P≤0.05 & t<0 but the t-test of the metabolic cost test result does not satisfy P≤0.05 & t<00, then the lower limb assist exoskeleton can effectively alleviate local muscle fatigue damage and reduce muscle activity, but cannot significantly reduce the metabolic cost of continuous stair climbing; If the t-test of the metabolic cost test result satisfies P≤0.05&t<0 but the t-test of the electromyographic signal test result does not satisfy P≤0.05&t<0, then the exoskeleton can significantly reduce the metabolic cost η of continuous stair climbing, but does not provide significant assistance to the muscles of the test site; If the electromyographic signal measurement results and the metabolic cost test results do not satisfy P≤0.05&t<0, the lower limb power-assisted exoskeleton cannot provide assistance for continuous stair climbing.

12. A system for evaluating the performance of lower limb-assisted exoskeleton based on continuous stair-climbing gait, characterized in that include: The muscle activity data acquisition unit is used to collect the electromyographic signals of the lower limb muscles of the tester during the continuous step-up test; The test of the tester climbing stairs continuously while wearing the exoskeleton and the test of the tester climbing stairs continuously while not wearing the exoskeleton both lasted for 5 minutes to 15 minutes; Metabolic cost data collection unit, used to collect the tester's oxygen consumption and carbon dioxide exhalation in the last 1 minute to 3 minutes of the continuous step-up test; A statistical data processing unit performs statistical data processing on the collected electromyographic signals of the lower limb muscles of the tester in the continuous step-up test and the collected oxygen consumption and carbon dioxide exhaled volume of the tester; A data analysis unit, which analyzes the statistically processed data and draws conclusions, wherein the data analysis unit is connected to the statistical data processing unit; Wherein, the data analysis unit uses the formula Calculate the power-assisting efficiency of the lower limb power-assisting exoskeleton in continuous step-climbing gait; and use the formula Calculate the power consumption reduction ratio of the lower limb power-assisted exoskeleton during continuous stair-climbing gait; in To help improve efficiency, is the normalized electromyographic amplitude without exoskeleton, is the normalized electromyographic amplitude when wearing the exoskeleton; To reduce the ratio, is the average energy consumption power without exoskeleton, is the average energy consumption when wearing the exoskeleton.

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