Lower limb manipulation comfort assessment method based on surface myoelectricity and joint angle data
Through the evaluation method based on surface electromyography and joint angle data, the problem of incomplete evaluation of lower limb manipulation comfort in the prior art is solved, and more accurate comfort evaluation and more comprehensive optimization of pilot operation experience are achieved.
Patent Information
- Application Number
- CN202510048131.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-13
- Publication Date
- 2025-06-13
AI Technical Summary
The existing methods of lower limb manipulation comfort assessment mainly rely on simulation simulation or human physiological data analysis, resulting in incomplete assessment.
Using an evaluation method based on surface electromyography and joint angle data, by designing multiple typical tasks, the pilot's electromyography data, human joint angle data and preset evaluation data were obtained, muscle activation and posture comfort scores were calculated, and normalized processing was performed to obtain the comprehensive evaluation results.
This method can more accurately reflect the pilot's actual comfort during operation, provide more comprehensive evaluation results, help optimize the pilot's operating experience and improve the efficiency of the flight mission.
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Abstract
Description
Technical Field
[0001] This application belongs to the technical field of aviation human-computer interaction, and particularly relates to a method for evaluating the comfort of lower limb manipulation based on surface electromyography and joint angle data. Background Art
[0002] In the ergonomic design of aircraft cockpits, comfort evaluation, as an important evaluation method for cockpit ergonomics, covers a large amount of information and can comprehensively reflect the ergonomic level. Comfort evaluation mainly focuses on the evaluation of pilots' upper limb manipulation. However, when performing flight tasks such as braking and turning, pilots need to perform lower limb manipulation tasks, such as finely controlling the rudder pedals. A comfortable lower limb manipulation experience can reduce pilots' fatigue and improve their concentration and reaction speed. Therefore, evaluating the comfort of lower limb manipulation helps to optimize pilots' operation experience and improve the execution efficiency of flight tasks. The current evaluation methods mainly rely on simulation or human physiological data analysis, resulting in incomplete evaluation. Summary of the Invention
[0003] The embodiments of this application provide a method for evaluating the comfort of lower limb manipulation based on surface electromyography and joint angle data, which can solve the problem of incomplete evaluation caused by the current evaluation methods mainly relying on simulation or human physiological data analysis.
[0004] In a first aspect, the embodiments of this application provide a method for evaluating the comfort of lower limb manipulation based on surface electromyography and joint angle data, including the following steps: S1: Design multiple typical tasks, and obtain the electromyography data, human joint angle data, and preset evaluation data of the pilot based on the multiple typical tasks; S2: Calculate the muscle activation degree according to the electromyography data; S3: Obtain the human posture comfort score according to the human joint angle data and the posture scoring system for the comfort of the pilot's lower limb manipulation; S4: Normalize the muscle activation degree, the human posture comfort score, and the preset evaluation data to obtain a comprehensive evaluation result.
[0005] In a possible implementation manner of the first aspect, the different types of typical tasks in the above step S1 include tasks involving lower limb manipulation such as braking, turning, and adjusting the aircraft heading.
[0006] Optionally, in another possible implementation manner of the first aspect, the electromyography data in the above step S1 is the electromyography data of the pilot at rest, the maximum voluntary muscle contraction force, and when performing typical tasks.
[0007] Optionally, in another possible implementation manner of the first aspect, the electromyography data in the above step S1 is from the rectus femoris, tibialis anterior, biceps femoris, and gastrocnemius muscles.
[0008] Optionally, in another possible implementation of the first aspect, step S2 specifically includes:
[0009] Obtain the root mean square amplitude average value RMS based on the electromyogram data:
[0010]
[0011] where EMG(t) is the voltage value of the electromyogram signal and T is the length of the time window;
[0012] Obtain the muscle activation degree based on the root mean square amplitude average value:
[0013]
[0014] where RMS experiment is the RMS of the electromyogram signal when performing a typical task, RMS rest is the RMS of the electromyogram signal at rest, and RMS MVC is the RMS of the electromyogram signal during maximum voluntary contraction of the muscle.
[0015] Optionally, in another possible implementation of the first aspect, the human joints include the hip joint, knee joint, and ankle joint. Step S3 specifically includes:
[0016] Set multiple preset angle ranges of the hip joint, knee joint, and ankle joint to different comfort levels in sequence. Among them, both the hip joint and the ankle joint are set to 5 different comfort levels, and the knee joint is set to 2 different comfort levels;
[0017] Correspond the 5 different comfort levels of the hip joint and the ankle joint and the 2 different comfort levels of the knee joint to different human body posture comfort scores to generate a posture scoring system for the pilot's lower limb operation comfort;
[0018] Query according to the human joint angle data in the posture scoring system for the pilot's lower limb operation comfort to obtain the human body posture comfort score.
[0019] Optionally, in another possible implementation of the first aspect, step S4 specifically includes:
[0020] Weight the muscle activation degrees of the rectus femoris, tibialis anterior, biceps femoris, and gastrocnemius muscles to obtain the comprehensive muscle activation degree. The specific calculation formula is:
[0021]
[0022] where MA r is the muscle activation degree of the rectus femoris, MA b is the muscle activation degree of the tibialis anterior, and MAt is the muscle activation degree of the biceps femoris, MA g is the muscle activation degree of the gastrocnemius;
[0023] Normalize the comprehensive muscle activation degree, the human body posture comfort score, and the preset evaluation data respectively;
[0024] Perform weighted average processing on the normalized comprehensive muscle activation degree, the human body posture comfort score, and the preset evaluation data to obtain a comprehensive evaluation result.
[0025] Beneficial effects: In the technical solution of this application, first design multiple typical tasks, obtain the myoelectric data, human joint angle data, and preset evaluation data of the pilot based on the multiple typical tasks, then calculate the muscle activation degree according to the myoelectric data, and then obtain the human body posture comfort score according to the human joint angle data and the posture scoring system for the comfort of the pilot's lower limb operation. Finally, normalize the muscle activation degree, the human body posture comfort score, and the preset evaluation data to obtain a comprehensive evaluation result. Thus, the evaluation method provided by this application can more accurately reflect the actual comfort of the pilot during the operation process and has wide applicability. Description of the Drawings
[0026] In order to more clearly illustrate the technical solutions in the embodiments of this application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.
[0027] Figure 1 is a schematic flowchart of the lower limb operation comfort evaluation method based on surface electromyography and joint angle data provided by an embodiment of this application;
[0028] Figure 2 is an improved Borg subjective evaluation scale provided by an embodiment of this application;
[0029] Figure 3 is a schematic diagram of the horizontal distance from the heel point of the footrest to the reference point of the seat provided by an embodiment of this application;
[0030] Figure 4 is a schematic diagram of the estimated marginal mean values of the electromyography characteristics, human body posture characteristics, and preset evaluation provided by an embodiment of this application. Detailed Embodiments
[0031] In the following description, specific details such as specific system architectures and technologies are presented for purposes of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, those skilled in the art should understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from obscuring the description of the present application.
[0032] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.
[0033] It should also be understood that the term "and / or" used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.
[0034] As used in the specification of the present application and the appended claims, the term "if" can be interpreted as "when" or "once" or "in response to determining" or "in response to detecting" according to the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined" or "in response to determining" or "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]" according to the context.
[0035] In addition, in the description of the specification of the present application and the appended claims, the terms "first", "second", "third", etc. are only used for differentiating descriptions and cannot be understood as indicating or implying relative importance.
[0036] The reference to "one embodiment" or "some embodiments" etc. described in the specification of the present application means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of the present application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way.
[0037] The following provides a detailed description of the lower limb manipulation comfort evaluation method based on surface electromyography and joint angle data provided by the present application with reference to the accompanying drawings.
[0038] Figure 1 The flowchart shows a method for evaluating the lower limb manipulation comfort based on surface electromyogram and joint angle data provided by an embodiment of the present application.
[0039] As Figure 1 shown, the method for evaluating the lower limb manipulation comfort based on surface electromyogram and joint angle data includes the following steps:
[0040] S1: Design multiple typical tasks, and obtain the electromyogram data, human joint angle data and preset evaluation data of the pilot based on the multiple typical tasks.
[0041] It should be noted that different types of typical tasks in step S1 include tasks involving lower limb manipulation such as braking, turning, and adjusting the aircraft heading, or related tasks that the pilot needs to perform lower limb manipulation considering the above different characteristics.
[0042] The electromyogram data in step S1 is the electromyogram data of the pilot at rest, at the maximum voluntary contraction force of the muscle, and when performing typical tasks.
[0043] The electromyogram data in step S1 is sourced from the rectus femoris, tibialis anterior, biceps femoris, and gastrocnemius muscles.
[0044] The human joint angle data of the pilot is the lower limb joint angle information when performing typical tasks. Among them, the electromyogram data and the joint angle data are synchronously collected at the same moment, effectively avoiding the disconnection problem between the virtual environment data and the actual operation data, and ensuring a high degree of consistency when comparing the data.
[0045] S2: Calculate the muscle activation degree according to the electromyogram data.
[0046] Furthermore, in the embodiment of the present application, the above step S2 specifically includes:
[0047] Obtain the root mean square amplitude average value RMS according to the electromyogram data:
[0048]
[0049] where EMG(t) is the voltage value of the electromyogram signal, and T is the length of the time window;
[0050] Obtain the muscle activation degree according to the root mean square amplitude average value:
[0051]
[0052] where RMS experiment is the RMS of the electromyogram signal when performing typical tasks, RMS rest is the RMS of the electromyogram signal at rest, RMS MVCIt is the RMS of the EMG signal when the muscle is at maximum voluntary contraction.
[0053] S3: Obtain the human body posture comfort score according to the human body joint angle data and the posture scoring system for the comfort of the pilot's lower limb operation.
[0054] Further, in the embodiment of the present application, the human body joints include the hip joint, the knee joint and the ankle joint, and the above step S3 specifically includes:
[0055] S301: Sequentially set multiple preset angle ranges of the hip joint, the knee joint and the ankle joint to different comfort levels. Among them, both the hip joint and the ankle joint are set to 5 different comfort levels, and the knee joint is set to 2 different comfort levels;
[0056] S302: One-to-one correspondence between the 5 different comfort levels of the hip joint and the ankle joint and the 2 different comfort levels of the knee joint with different human body posture comfort scores to generate a posture scoring system for the comfort of the pilot's lower limb operation;
[0057] S303: Query according to the human body joint angle data in the posture scoring system for the comfort of the pilot's lower limb operation to obtain the human body posture comfort score.
[0058] In one embodiment, a posture scoring system for the comfort of the pilot's lower limb operation is designed according to the pilot's human body joint angle data, and the human body posture comfort score is calculated. By dividing the angles of the hip joint, the knee joint and the ankle joint and stratifying them according to the comfort level, multiple joint angle features are obtained. The joint angles of the hip joint and the ankle joint are divided into 5 levels, and the joint angles of the knee joint are divided into 2 levels. The joint angle range with the worst comfort is used as the highest level, the joint angle range with the best comfort is used as the lowest level, and the remaining angle ranges are sequentially divided into intermediate levels. Finally, each joint angle range is corresponding to a different comfort level, as shown in Table 1. Then it is converted into the human body posture comfort score, as shown in Table 2.
[0059] Table 1
[0060]
[0061]
[0062] Table 2
[0063]
[0064]
[0065] S4: Normalize the muscle activation degree, the human body posture comfort score and the preset evaluation data to obtain a comprehensive evaluation result.
[0066] Further, in the embodiments of the present application, before the above step S4, the following steps are further included:
[0067] Perform a one-way analysis of variance on the muscle activation degree of the pilot, the evaluation results of the human body posture comfort, and the subjective evaluation results to obtain a P value, and verify the effectiveness of each item of data. If the P value of the one-way analysis of variance is less than 0.05, it indicates that the test conclusion is reliable and scientific.
[0068] Further, in the embodiments of the present application, the above step S4 further includes:
[0069] Weight the muscle activation degrees of the rectus femoris, tibialis anterior, biceps femoris, and gastrocnemius muscles to obtain a comprehensive muscle activation degree. The specific calculation formula is:
[0070]
[0071] where MA r is the muscle activation degree of the rectus femoris, MA b is the muscle activation degree of the tibialis anterior, MA t is the muscle activation degree of the biceps femoris, and MA g is the muscle activation degree of the gastrocnemius muscle;
[0072] Normalize the comprehensive muscle activation degree, the human body posture comfort score, and the preset evaluation data respectively;
[0073] Perform weighted average processing on the normalized comprehensive muscle activation degree, the human body posture comfort score, and the preset evaluation data to obtain a comprehensive evaluation result.
[0074] The lower limb manipulation comfort evaluation method based on surface electromyography and joint angle data provided by the present application first designs multiple typical tasks, obtains the electromyography data, human joint angle data, and preset evaluation data of the pilot based on the multiple typical tasks, then calculates the muscle activation degree according to the electromyography data, and then obtains the human body posture comfort score according to the human joint angle data and the posture scoring system of the pilot's lower limb manipulation comfort. Finally, the muscle activation degree, the human body posture comfort score, and the preset evaluation data are normalized to obtain a comprehensive evaluation result. Thus, the evaluation method provided by the present application can more accurately reflect the actual comfort of the pilot during the operation process and has wide applicability.
[0075] Figure 2The improved Borg subjective assessment scale is presented. The Borg subjective assessment scale is improved according to the cockpit seat position and the typical pilot's operating postures to make it more in line with the comfort feelings of pilots during actual operation. By introducing scoring criteria related to the seat distance and typical operating tasks, the improved scale can more accurately reflect the subjective comfort experience of pilots under different seat settings and operating postures.
[0076] Figure 3 It is a schematic diagram of the horizontal distance from the heel point of the pedal to the seat reference point. Different seat positions may cause pilots to feel different mechanical feedback during operation, thus affecting their comfort. In this paper, three seat positions with horizontal distances from the heel point of the pedal to the seat reference point of 600 mm, 700 mm, and 800 mm are selected for analysis to study the influence of different seat positions on the comfort of lower limb operation.
[0077] Table 3 shows three typical operating postures specified in the Boeing 737 flight manual. According to the standard flight procedures specified in the Boeing 737 flight manual, when performing lower limb tasks, pilots are mainly involved in stages such as takeoff roll and approach landing, and need to operate the pedals to adjust the heading in the air and perform flight tasks such as turning and braking on the ground.
[0078] Table 3
[0079]
[0080] Collect test data to obtain the muscle activation degree, human posture comfort score, and subjective assessment results of the pilots. Calculate the test results to obtain the mean M, analysis of variance results (F value, p value), and effect size (η2). The treatment factors of the experiment are distance (R) and action (P), where: the distance (R) between the seat reference point and the heel point of the pedal for the subjects in the test scenario can be divided into three distances: 600 mm, 700 mm, and 800 mm; under the influence of the same distance (R), the action (P) is also divided into three actions: action 1, action 2, and action 3. Conduct a cross experiment on the above two factors to analyze the main effects of the two factors, and compare the analysis of variance results (F value, p value), effect size (η 2 ) of different effects.
[0081] Table 4 shows the univariate F test results obtained after general linear model analysis of the subjects' comfort. It can be seen from the analysis of variance results that there are significant differences in the main effects of distance (R) on the MA levels of the biceps femoris, tibialis anterior, gastrocnemius, human posture comfort score, and subjective score (p < 0.05). In addition, there are significant differences in the main effects of all evaluation characteristics on action (P) (p < 0.05), indicating that the test conclusions are reliable and scientific.
[0082] Table 4
[0083]
[0084] Table 5 shows the estimated marginal means of various characteristics under the influence of distance (R).
[0085] Table 5
[0086]
[0087] In terms of electromyogram characteristics, the average muscle comfort levels of the four muscles are all the lowest at a distance of 700 mm, and the average muscle comfort levels of the rectus femoris and gastrocnemius are lower than those of the biceps femoris and tibialis anterior, indicating that the rectus femoris and gastrocnemius are more involved in the task. In terms of human body posture characteristics and subjective evaluation, it also shows that the pilot is most comfortable at a seat distance of 700 mm.
[0088] Figure 4 Shows the estimated marginal means of electromyogram characteristics, human body posture characteristics, and subjective evaluations obtained by the pilot when performing different actions under different distance conditions. It can be Figure 4 seen that under the influence of distance, the rectus femoris, biceps femoris, tibialis anterior, gastrocnemius, human body posture comfort score, and subjective score results all prove that the pilot feels most comfortable at a seat distance of 700 mm. Under the influence of actions, Action 2 is more tiring for the pilot, indicating that Action 2 requires more muscle involvement, resulting in a decrease in comfort. The execution of Action 2 may cause a higher sense of fatigue or discomfort, and the pilot has the greatest burden in this action compared to other actions.
[0089] The comprehensive muscle activation degree, human body posture comfort score, and subjective evaluation results of the pilot are normalized respectively, and then the comprehensive evaluation result is obtained by the weighted average method. When the seat distance is 600 mm, the comprehensive evaluation result is 0.397. When the seat distance is 700 mm, the comprehensive evaluation result is 0.322. When the seat distance is 800 mm, the comprehensive evaluation result is 0.356. The results show that when the seat distance is 700 mm, the lower limb operation comfort of the pilot is the best.
[0090] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
[0091] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included within the protection scope of the present application.
Claims
1. A method for evaluating lower limb manipulation comfort based on surface electromyography and joint angle data, characterized in that: The steps include: S1: Design multiple typical tasks, and obtain the pilot's electromyographic data, human joint angle data, and preset evaluation data based on the multiple typical tasks; S2: Calculating muscle activation according to the electromyographic data; S3: obtaining a human posture comfort score according to the human joint angle data and the posture scoring system for pilot lower limb control comfort; S4: Normalize the muscle activation degree, the human posture comfort score and the preset evaluation data to obtain a comprehensive evaluation result.
2. The method for evaluating lower limb manipulation comfort based on surface electromyography and joint angle data according to claim 1, characterized in that: The different types of typical tasks in step S1 include braking, turning, and adjusting the aircraft heading, which are tasks involving lower limb manipulation.
3. The method for evaluating lower limb manipulation comfort based on surface electromyography and joint angle data according to claim 1, characterized in that: The electromyographic data in step S1 are the electromyographic data of the pilot at rest, at maximum voluntary muscle contraction force, and when performing typical tasks.
4. The method for evaluating lower limb manipulation comfort based on surface electromyography and joint angle data according to claim 1, characterized in that: The electromyographic data in step S1 are derived from the rectus femoris, tibialis anterior, biceps femoris and gastrocnemius.
5. The method for evaluating lower limb manipulation comfort based on surface electromyography and joint angle data according to claim 3, characterized in that: The step S2 specifically includes: Get the root mean square amplitude average RMS according to the electromyographic data: Wherein, EMG(t) is the voltage value of the electromyographic signal, and T is the length of the time window; The muscle activation degree is obtained according to the average value of the root mean square amplitude: Among them, RMS experiment is the RMS of the electromyographic signal when performing a typical task, RMS rest is the RMS of the electromyographic signal at rest, RMS MVC It is the RMS value of the electromyographic signal during the maximum voluntary contraction of the muscle.
6. The method for evaluating lower limb manipulation comfort based on surface electromyography and joint angle data according to claim 1, characterized in that: The human body joints include hip joints, knee joints and ankle joints, and step S3 specifically includes: The plurality of preset angle ranges of the hip joint, the knee joint and the ankle joint are respectively set to different comfort levels in sequence, wherein the hip joint and the ankle joint are both set to 5 different comfort levels, and the knee joint is set to 2 different comfort levels; The five different comfort levels of the hip joint and the ankle joint and the two different comfort levels of the knee joint are matched one by one to different human posture comfort scores, so as to generate a posture scoring system for the pilot's lower limb control comfort; The human body joint angle data is queried in the posture scoring system of the pilot's lower limb control comfort to obtain the human body posture comfort score.
7. The method for evaluating lower limb manipulation comfort based on surface electromyography and joint angle data according to claim 4, characterized in that: The step S4 specifically includes: The muscle activation degrees of the rectus femoris, the tibialis anterior, the biceps femoris and the gastrocnemius are weighted to obtain a comprehensive muscle activation degree, and the specific calculation formula is: Among them, MA r is the muscle activation of the rectus femoris, MA b is the muscle activation of the tibialis anterior muscle, MA t is the muscle activation of the biceps femoris, MA g is the muscle activation of the gastrocnemius muscle; Normalizing the comprehensive muscle activation degree, the human posture comfort score and the preset evaluation data respectively; The normalized comprehensive muscle activation degree, the human body posture comfort score and the preset evaluation data are processed by weighted average to obtain the comprehensive evaluation result.