Parameter determination method, device and equipment for human exoskeleton and program product

Abstract

The embodiment of the invention provides a parameter determination method and device for a human exoskeleton, equipment and a program product, relates to the technical field of human exoskeletons, and can improve the auxiliary accuracy of exoskeleton auxiliary equipment, improve the auxiliary effect of exoskeleton auxiliary equipment, improve the movement speed and operation efficiency of a wearer and improve the user experience. And the safety risk of a wearer in the wearing process is reduced. The method comprises the steps that object information of a target carrying object is acquired; obtaining a carrying path of the target carrying object; according to the object information and the carrying path, determining a motion data acquisition point location of a target carrying person; on the basis of the motion data acquisition point location, motion data of a target carrying person is acquired; and determining compensation motion parameters of the target exoskeleton according to the object information, the carrying path and the motion data.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of human exoskeleton, and in particular to a method, device, equipment and program product for determining parameters of a human exoskeleton. Background Art

[0002] Activities involving heavy lifting and repeated lifting often cause certain impacts and damage to the body structure of the personnel involved. Especially when carrying heavy objects and working for long periods of time, the human skeleton, muscles, joints and other parts will be under greater pressure and fatigue, affecting the health of the personnel involved and increasing the risk of occupational diseases and other diseases. Therefore, for activities with high intensity, practitioners usually need to be equipped with exoskeleton devices to assist in movement in order to reduce the pressure on the human skeleton, muscles and joints.

[0003] However, traditional exoskeleton assistive equipment is usually difficult to accurately assist the wearer's different movements, resulting in poor assistive effect of the exoskeleton assistive equipment, affecting the wearer's movement speed and work efficiency, and increasing the wearer's safety risks during the wearing process. Summary of the invention

[0004] The parameter determination method, device, equipment and program product for a human exoskeleton provided in the embodiments of the present application can improve the accuracy of assistance provided by exoskeleton accessory equipment, improve the auxiliary effect of exoskeleton auxiliary equipment, increase the movement speed and work efficiency of the wearer, and reduce the safety risks of the wearer during the wearing process.

[0005] According to a first aspect of an embodiment of the present application, a method for determining parameters of a human exoskeleton is provided, comprising:

[0006] Obtaining object information of a target transport object;

[0007] Acquire a transport path of the target transport object;

[0008] Determine the movement data collection points of the target transporter according to the object information and the transport path;

[0009] Based on the motion data collection points, acquiring motion data of the target transporter;

[0010] The compensation motion parameters of the target exoskeleton are determined according to the object information, the transport path and the motion data.

[0011] In some embodiments, the object information includes at least one of the shape, weight, and material of the target transport object.

[0012] In some embodiments, the motion data includes at least one of muscle force information and bone curvature information corresponding to the motion data collection point.

[0013] In some embodiments, the compensation motion parameter includes at least one of the motion form, support point position, and support strength of the target exoskeleton.

[0014] In some embodiments, determining the motion data collection points of the target transporter according to the object information and the transport path includes:

[0015] When it is determined according to the object information and the transport path that the target transport object is in the in-situ lifting mode, the motion acquisition point position includes at least one of a back muscle and a lumbar intervertebral disc; or,

[0016] When it is determined that the target transport object is in the transport mode according to the object information and the transport path, the motion acquisition point includes at least one of an elbow joint, a shoulder joint and a lumbar intervertebral disc; or,

[0017] When it is determined that the target transport object is in a weight-bearing motion mode according to the object information and the transport path, the motion collection point is determined to include at least one of a hip joint, a knee joint, and an ankle joint.

[0018] In some embodiments, determining the compensation motion parameters of the target exoskeleton according to the object information, the transport path, and the motion data includes:

[0019] Determining target motion parameters corresponding to the motion collection points according to the object information and the transport path;

[0020] The compensation motion parameter of the target exoskeleton is determined based on the difference between the target motion parameter corresponding to the same motion acquisition point and the motion data.

[0021] According to a second aspect of an embodiment of the present application, there is provided a parameter determination device for a human exoskeleton, comprising:

[0022] A first acquisition module, used to acquire object information of a target transport object;

[0023] A second acquisition module, used to acquire a transport path of the target transport object;

[0024] A first determination module is used to determine the movement data collection points of the target transporter according to the object information and the transport path;

[0025] A third acquisition module is used to acquire the motion data of the target transporter based on the motion data collection points;

[0026] The second determination module is used to determine the compensation motion parameters of the target exoskeleton according to the object information, the transport path and the motion data.

[0027] According to a third aspect of an embodiment of the present application, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method for determining parameters of a human exoskeleton described in any one of the first aspects are implemented.

[0028] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for determining parameters of a human exoskeleton described in any one of the first aspects are implemented.

[0029] According to a fifth aspect of the embodiments of the present application, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the method for determining parameters of a human exoskeleton according to any one of the first aspects are implemented.

[0030] The embodiments of the present application provide a parameter determination method, device, equipment and program product for a human exoskeleton. By acquiring the object information and the transport path of the target transport object, the main force-generating position and the main force-bearing position of the target transporter during the transport process can be determined. Further, the object information and the transport path of the target transport object can be used to determine the motion data collection point. The motion data of the position that is prone to fatigue or injury during the transport process can be collected, and the compensation motion parameters of the target exoskeleton can be determined based on the object information, the transport path and the motion data, so that the target exoskeleton can accurately assist the transporting activities of the target transporter based on the motion data required to complete the transport task and the motion data of the actual action of the target transporter. The accuracy of the assistance of the exoskeleton auxiliary equipment can be improved, the auxiliary effect of the exoskeleton auxiliary equipment can be improved, and the movement speed and work efficiency of the wearer can be further improved, and the safety risks of the wearer during the wearing process can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0032] FIG1 is a schematic flow chart of a method for determining parameters of a human exoskeleton provided in an embodiment of the present application;

[0033] FIG2 is a schematic diagram of the human body position of a target transporter in a method for determining parameters of a human exoskeleton provided in an embodiment of the present application;

[0034] FIG3 is a force analysis diagram of a method for determining parameters of a human exoskeleton provided in an embodiment of the present application;

[0035] FIG4 is a schematic diagram of a human spine structure for a method for determining parameters of a human exoskeleton provided in an embodiment of the present application;

[0036] FIG5 is a force analysis diagram of another parameter determination method for a human exoskeleton provided in an embodiment of the present application;

[0037] FIG6 is a force analysis diagram of another method for determining parameters of a human exoskeleton provided in an embodiment of the present application;

[0038] FIG7 is a schematic structural diagram of a method and device for determining parameters of a human exoskeleton provided in an embodiment of the present application;

[0039] FIG8 is a schematic structural diagram of a computer device provided in an embodiment of the present application;

[0040] FIG9 is a schematic structural diagram of a computer-readable storage medium provided in an embodiment of the present application;

[0041] FIG10 is a schematic structural diagram of a computer program product provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to facilitate understanding of the present application, the present application will be described more fully below with reference to the relevant drawings. Embodiments of the present application are provided in the drawings. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application.

[0044] When used herein, the singular forms "a", "an" and " / the" may also include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the terms "include / comprise" or "have" and the like specify the presence of stated features, wholes, steps, operations, components, parts or combinations thereof, but do not exclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts or combinations thereof. At the same time, in this specification, the term "and / or" includes any and all combinations of the relevant listed items.

[0045] Activities involving heavy lifting and repeated lifting often cause certain impacts and damage to the body structure of the personnel involved. Especially when carrying heavy objects and working for long periods of time, the human skeleton, muscles, joints and other parts will be under greater pressure and fatigue, affecting the health of the personnel involved and increasing the risk of occupational diseases and other diseases. Therefore, for activities with high intensity, practitioners usually need to be equipped with exoskeleton devices to assist in movement in order to reduce the pressure on the human skeleton, muscles and joints.

[0046] However, traditional exoskeleton assistive equipment is usually difficult to accurately assist the wearer's different movements, resulting in poor assistive effect of the exoskeleton assistive equipment, affecting the wearer's movement speed and work efficiency, and increasing the wearer's safety risks during the wearing process.

[0047] Therefore, proposing a method that can drive the exoskeleton to accurately assist the activities of the transport personnel is an urgent problem to be solved.

[0048] As shown in Figure 1, Figure 1 is a schematic flow chart of a method for determining parameters of a human exoskeleton provided in an embodiment of the present application. In a first aspect of an embodiment of the present application, a method for determining parameters of a human exoskeleton is provided, comprising:

[0049] Step S110: Obtain object information of the target transport object.

[0050] Exemplarily, the object information of the target transport object may be acquired through an image detection device or the like, and the object information of the target transport object may also be acquired by retrieving a task list of a target transporter.

[0051] Step S120: Acquire the transport path of the target transport object.

[0052] For example, the transport path of the target transport object may be determined by acquiring image information of the transport site of the target transporter, and the transport path of the target transport object may be acquired by retrieving a task list of the target transporter.

[0053] Exemplarily, the transport path may include at least one of the transport environment, transport direction, transport height and transport distance of the target transport object. The target transport objects of the same weight are lifted to different heights to complete the same number of actions. As the lifting height increases, the energy consumption of the human body increases accordingly. This process can be understood as the difference in the potential energy increase of the target transport objects of the same weight. Therefore, according to the law of conservation of energy, the transport work of lifting to a higher position is more physically demanding. The impact of unloading the transport work of target transport objects of different heights on the transport capacity is similar to that of the lifting height. In addition, the transport environment may also have an impact on the psychology of the target transport personnel, and further affect the transport activities. For example: if the road is rugged, the light is dim, the ground is slippery, etc., the transport speed of the target transport personnel will slow down, resulting in a further increase in the fatigue rate of the target transport personnel.

[0054] Step S130: Determine the motion data collection points of the target transporter according to the object information and the transport path.

[0055] Exemplarily, the motion data collection point is at least one of a direct or indirect force-generating position and a force-receiving position on the body of the target transporter. The motion data collection point of the target transporter can be determined according to the motion data collection method. For example, when the collection method is image collection or thermal imaging collection, the point where the signal can be stably collected and transmitted according to the transport path is determined as the motion data collection point.

[0056] Step S140: acquiring the motion data of the target transporter based on the motion data collection points.

[0057] For example, the curvature of the joint can be obtained through an angle sensor, the strength of the force or force applied to the muscles and joints can be obtained through a pressure sensor, and the information on the force or force applied to the muscles can be obtained through an electromyographic signal sensor.

[0058] Step S150: Determine the compensation motion parameters of the target exoskeleton according to the object information, the transport path and the motion data.

[0059] Exemplarily, the compensated motion parameters are used to drive the target exoskeleton motion to assist the target transporter's transport activities.

[0060] The embodiment of the present application provides a parameter determination method for a human exoskeleton. By acquiring the object information and the transport path of the target transport object, the main force-generating position and the main force-bearing position of the target transporter during the transport process can be determined. Further, the object information and the transport path of the target transport object can be used to determine the motion data collection point. The motion data of the position that is prone to fatigue or injury during the transport process can be collected, and the compensation motion parameters of the target exoskeleton can be determined based on the object information, the transport path and the motion data, so that the target exoskeleton can accurately assist the transporting activities of the target transporter based on the motion data required to complete the transport task and the motion data of the actual action of the target transporter. The accuracy of the assistance of the exoskeleton auxiliary equipment can be improved, the auxiliary effect of the exoskeleton auxiliary equipment can be improved, and the movement speed and work efficiency of the wearer can be further improved, and the safety risks of the wearer during the wearing process can be reduced.

[0061] In some feasible implementations, the object information includes at least one of the shape, weight, and material of the target transport object.

[0062] It should be noted that the human body's own bone shape and reach are fixed, so the carrying speed is different when carrying target objects of different shapes. Manual target object handling generally accepts objects within 50% of its own arm span. When the target object is too long or too high, two people are required to cooperate in carrying it. Similarly, if the target object is too high, it is easy to block the line of sight during handling, resulting in inconvenience in walking during handling, which poses a major safety hazard.

[0063] It should be noted that the heavier the target object is, the more intense the force exerted and the force received by the target transporter during the transport process will be, and the greater the need for exoskeleton assistance will be.

[0064] It should be noted that the common forms of transported objects in handling work are solid and fluid. Solid transported objects are usually easier to grasp and fix, and the center of gravity of solid transported objects is usually more stable than that of liquid transported objects. In addition, the auxiliary design of the transported objects, such as the handles of boxes and plastic bags, is crucial to improving the transport efficiency of the transporters.

[0065] The embodiment of the present application provides a parameter determination method for a human exoskeleton. By acquiring the shape, weight and material of the target transport object, the comprehensiveness of the object information can be improved, and the effectiveness of the motion data collection points can be further improved. According to the object information of the target transport object, the compensation motion parameters can be further corrected, so that the target exoskeleton can accurately assist the transporting activities of the target transporter. The accuracy of the assistance of the exoskeleton auxiliary equipment can be improved, the auxiliary effect of the exoskeleton auxiliary equipment can be improved, and the movement speed and work efficiency of the wearer can be further improved, and the safety risks of the wearer during the wearing process can be reduced.

[0066] In some feasible implementations, the motion data includes at least one of muscle force information and bone curvature information corresponding to the motion data collection point.

[0067] The embodiment of the present application provides a parameter determination method for a human exoskeleton. By acquiring the muscle force information and bone curvature information corresponding to the motion data collection point, the comprehensiveness of the motion data can be further improved, thereby improving the accuracy of the compensation motion parameters, so that the target exoskeleton can accurately assist the target transporter's transport activities. The accuracy of the assistance of the exoskeleton's auxiliary equipment can be improved, the auxiliary effect of the exoskeleton auxiliary equipment can be improved, and the movement speed and work efficiency of the wearer can be further improved, and the safety risks of the wearer during the wearing process can be reduced.

[0068] In some feasible implementations, the compensation motion parameter includes at least one of the motion form, support point position, and support strength of the target exoskeleton.

[0069] The embodiment of the present application provides a parameter determination method for a human exoskeleton, by which the target exoskeleton assists the carrying motion of a target carrying person according to the motion form, support points and support strength of the target exoskeleton in the compensating motion parameters, thereby improving the comprehensiveness and diversity of the compensating motion parameters, facilitating precise control of the auxiliary motion of the target exoskeleton, thereby improving the auxiliary effect of the exoskeleton auxiliary equipment, further improving the movement speed and work efficiency of the wearer, and reducing the safety risks of the wearer during the wearing process.

[0070] In some feasible implementations, the motion data collection points of the target transporter are determined based on the object information and the transport path, including: when the target transport object is determined to be in a transport mode based on the object information and the transport path, determining that the motion collection points include at least one of the elbow joint, shoulder joint and lumbar intervertebral disc.

[0071] As shown in Figure 2, the body orientation of the human body can be defined anatomically by three axes and three planes. The three axes include the sagittal axis, the coronal axis and the vertical axis, and the three planes are the horizontal plane, the coronal plane and the sagittal plane. The sagittal axis is formed by the intersection of the sagittal plane and the horizontal plane; the coronal axis is formed by the intersection of the horizontal plane and the coronal plane; the vertical axis is formed by the intersection of the sagittal plane and the coronal plane. The 3 axes and 3 planes can accurately describe the limb movement of the human body. For the characteristic analysis of the carrying action, the motion characteristic analysis can be selected from the sagittal plane.

[0072] As shown in Figure 3, by simplifying the human body's carrying motion, the human body's limbs are regarded as rigid bodies, so the movement of the limbs can be regarded as the movement of rigid bodies. In the weight-carrying motion, the force direction of each force-generating muscle group of the human arm is basically determined, among which the brachioradialis of the forearm, the biceps of the upper arm, and the deltoid muscle of the shoulder are the main force-generating muscle groups. The movement of the fingers is ignored here, so the arm force is mainly the biceps brachii that provides torque R for the elbow joint. ej and the shoulder triangle provide torque R to the shoulder joint sj , the two torques are generated to resist the downward gravity of the heavy object. The back muscles are mainly provided by the erector spinae. The reason for the erector spinae is that when the human body carries heavy objects, the center of gravity of the heavy object and the arm is at a certain offset distance from the rotation center of the human waist in the front of the abdomen. When standing and walking, the shoulders and waist can be approximately regarded as on the same vertical line, so the offset distance is also l 2 , which in turn causes the waist of the human body to exert force to generate a moment R to straighten the waist jw , to avoid the upper body bending forward.

[0073] The gravitational force G generated by the weight 0 :

[0074]

[0075] The weight exerts a torque R on the elbow joint. ej :

[0076]

[0077] The moment R generated by the weight on the shoulder joint sj :

[0078]

[0079] The moment generated on the waist is the resultant moment R generated by the weight and the gravity of the upper limbs of the human body. jw :

[0080]

[0081] Among them, m 0 is the mass of the transported material, g is the acceleration due to gravity, l1 is the horizontal distance from the center of gravity of the material to the elbow joint, l 2 is the horizontal distance from the material to the shoulder joint. It can be seen that when the mass of the arm is ignored, the torque generated by the weight on the arm is related to the mass of the weight and the position of the weight when it is lifted and held. The torque generated by the increase in the mass of the weight also increases accordingly. When holding the weight, the closer the weight is to the body, the smaller the torque generated. Therefore, when carrying and holding heavy objects, the weight should be kept as close to the body as possible to reduce the excessive burden on the arm. It can be seen that when carrying and holding heavy objects, the torque burden on the waist caused by the heavy object is also related to the mass and position of the heavy object. In addition, it is also related to the angle of the upper limb body leaning forward. When the bending angle increases, 4l will increase accordingly, thereby increasing the load on the waist. Therefore, when carrying and holding heavy objects, you should also pay attention to the angle of the body leaning forward, and try to keep your waist and back straight.

[0082] In some feasible implementations, the motion data collection points of the target transporter are determined based on the object information and the transport path, including: when it is determined that the target transported object is in an in-situ lifting mode based on the object information and the transport path, determining that the motion collection points include at least one of the back muscles and the lumbar intervertebral disc.

[0083] Lifting and carrying requires the coordination of the upper limbs, lower limbs and waist. According to research, the waist is most susceptible to fatigue damage during lifting and carrying. Common injuries to the waist and back include lumbar disc herniation and lumbar muscle strain, which is also one of the common work injuries in modern manufacturing. Through structural analysis of the spine structure, the spine structure is shown in Figure 4. The spine is located in the middle of the posterior wall of the trunk and consists of 33 vertebrae.

[0084] The function of the spine is to support weight, provide movement and protect internal organs. The vertebrae are usually divided into cervical, thoracic, lumbar, sacrum and coccyx. The cervical spine consists of 7 vertebrae C1-C7, the thoracic spine consists of 12 vertebrae T1-T12, the lumbar spine consists of 5 vertebrae L1-L5, and the sacrum consists of 5 vertebrae S1-S5. The vertebrae start from the front and gradually widen from top to bottom, with the second sacral vertebra being the widest. From the side, the S shape of the spine is called the physiological curve, indicating cervical lordosis, thoracic kyphosis, lumbar lordosis and sacral kyphosis. The upper limbs are connected to the spine through the humerus, clavicle and sternum, and the lower limbs are connected to the spine through the pelvis. Various activities of the upper and lower limbs are adjusted through the spine to maintain body balance. In addition to support and protection, the spine also has flexible movement functions. Although the range of motion between two adjacent vertebrae is small, when the activities of multiple vertebrae are accumulated, they can perform a wide range of motion, such as flexion and extension, lateral flexion and rotation. However, lumbar flexion and extension are often associated with intervertebral disc pressure, which can lead to different degrees of low back pain. A simplified biomechanical model was established for repeated lifting movements, as shown in Figure 5, which shows the mechanical model of the heavy object and upper limbs on the lumbar spine during repeated lifting.

[0085] The moment M generated by the weight on the lumbar spine 0 :

[0086]

[0087] Among them, m 1 is the mass of the upper body, then the torque M generated by the upper body limbs on the lumbar spine 1：

[0088]

[0089] The torque generated by the back muscles on the lumbar spine is :

[0090]

[0091] According to the principle of torque balance:

[0092]

[0093] The force exerted by the back muscles during lifting and carrying can be calculated :

[0094]

[0095] The pressure on the lumbar spine can be obtained :

[0096]

[0097] According to the calculation results, it can be seen that the strength of the back muscles is mainly related to the mass of the heavy object being carried and the distance between the heavy object and the lumbar spine. It is also related to the angle at which the body leans forward. , The increase in the pressure at the lumbar spine increases the load on the waist muscles. By calculating the pressure at the lumbar spine, it is found that the pressure on the intervertebral disc is mainly related to the angles α and β, and increases with the increase of the α angle. Both angles are caused by bending over, so the greater the bending amplitude, the greater the load on the lumbar spine. Therefore, when completing repeated lifting and carrying, it is very important to use the correct carrying posture, and try to keep the back straight during carrying. In addition, the weight should not be too heavy, and when it exceeds the load that the human body can bear, it will cause great harm.

[0098] As shown in Figure 6, by establishing a biomechanical model of handling, the influence of the burden on the arms and waist caused by carrying heavy objects during the handling process is analyzed. When engaged in handling work, attention should be paid to the correct use of the handling movement and the control of the handling quality. From the perspective of the design of the handling exoskeleton, it can be found that the movement direction of the elbow joint and the shoulder joint of the arm is consistent during handling. The lifting is carried out by the biceps and deltoid muscles to resist the downward gravity of the heavy objects, and the erector spinae muscles of the back are used to provide torque for the waist to stand up the upper body. In view of this carrying force law, the carrying exoskeleton needs to provide arm assistance and waist assistance to the wearer, as shown in the figure. The arm assistance adopts flexible drive assistance, which provides an oblique upward pulling force along the line connecting the palm to the shoulder with the help of flexible steel wire. Because the rotation direction of the wrist joint, elbow joint and shoulder joint of the arm is consistent when lifting heavy objects, the entire arm can be assisted by pulling the palm alone. The use of such an assistance method can reduce the use of power components and reduce the swing inertia caused by the weight of the exoskeleton on the arm. The waist assistance method is mainly concentrated between the legs and waist of the human body. The exoskeleton is required to provide a torque to straighten the waist when bending. It is conceivable to install elastic elements between the waist and legs. When bending, the elastic elements are stretched to store energy, and when straightening, the elastic potential energy is released to assist. Whether bending or straightening, it will cause a great load on the lumbar spine and back muscles. Therefore, in both actions, it is necessary to provide a rotational torque when straightening the waist, provide protection when bending, and provide assistance when straightening the waist to make it easier, thereby relieving the pressure on the lumbar spine and the load on the back muscles.

[0099] In some feasible implementations, the motion data collection points of the target transporter are determined based on the object information and the transport path, including: when it is determined that the target transported object is in a weight-bearing motion mode based on the object information and the transport path, determining that the motion collection points include at least one of the hip joint, knee joint and ankle joint.

[0100] When the human body is carrying a load, the lower limbs of the human body need a certain degree of assistance because they need to carry the load. The main purpose of the lower limb exoskeleton design is to solve this problem. Before determining the overall design plan, in order to make walking smoother and safer, it is necessary to pay attention to its wearability. Therefore, the joint freedom and movement angle distribution of the lower limb exoskeleton robot should be similar to that of the human body. In terms of wearing comfort, in order to ensure that the gait of humans and machines is consistent, the design of the overall structure should comply with relevant principles such as ergonomics and biomechanics, and adopt anthropomorphic design standards.

[0101] Weighted walking is mainly accomplished by the waist, hip joints, knee joints, calf ankle joints and other parts, so these parts will be analyzed one by one and a series of assistance will be provided for these parts.

[0102] According to the principles of human anatomy, a simplified biomechanical model is established for weight-bearing movements, as shown in the figure. Gait analysis is usually done in a two-dimensional plane, so all force analysis and moment calculations are only calculated on the sagittal plane.

[0103] For the force analysis diagram of the three segments of the lower limb, Newton's second law is used for the joints of each segment in the horizontal, vertical and rotational directions:

[0104] In the horizontal direction:

[0105]

[0106] In the vertical direction:

[0107]

[0108] In the direction of rotation:

[0109]

[0110] Where: is the load-bearing mass, is the moment of inertia, Measuring angular acceleration, represent Direction linear acceleration, represent Direction linear acceleration.

[0111] Solving the model shows that in a gait cycle, the movement angle of the hip joint shows a sinusoidal function trend; the torque is positive and negative, indicating that it is a bidirectional drive; although the work done by the hip joint is also positive and negative, it tends to do positive work overall. Through the above analysis, it can be concluded that the hip joint plays an active role in the walking of the lower limbs of the human body. Therefore, when designing the hip joint, active drive should be designed in the sagittal plane; the movement angle of the knee joint has the largest change range, the torque is positive and negative, but it tends to do negative work overall, indicating that under normal gait, the knee joint plays a passive role, mainly playing a role of buffering and bearing weight, so it can be designed as a passive drive; the movement angle change of the ankle joint is the most complex, and it is also a bidirectional drive. It only does concentrated work when pushing the ground hard, and does not do work most of the time, so a passive drive is used, which mainly plays a supporting and load-bearing role.

[0112] In some feasible implementations, the compensating motion parameters of the target exoskeleton are determined based on the object information, the transport path and the motion data, including: determining the target motion parameters corresponding to the motion acquisition points based on the object information and the transport path; and determining the compensating motion parameters of the target exoskeleton based on the difference between the target motion parameters corresponding to the same motion acquisition point and the motion data.

[0113] The RS-EMG8 biological signal amplification and acquisition system is used to obtain the electromyographic information corresponding to the human body's moving muscles. The sampling frequency of the electromyographic sensor is 1000Hz, and the joint angle data is collected in combination with the Witt Intelligent WT901WIFI angle sensor with a sampling frequency of 100Hz.

[0114] However, the original sEMG signal is easily affected by noise signals during the acquisition process. The frequency range of sEMG signals is 0~500Hz, and the main frequency bands related to human body movement are concentrated in 30~300Hz. Therefore, a Butterworth bandpass filter of 30~500Hz and a notch filter of 50Hz are used to remove noise. The feature extraction of sEMG signals after preprocessing has a crucial impact on generalization ability. Good feature selection helps to reduce data redundancy and input data bandwidth and improve prediction accuracy. The present invention selects two time domain features, root mean square value and slope change number, and two frequency domain features, median frequency and average power frequency, as feature parameters to be extracted.

[0115] RMS value ( ) can comprehensively display the effective value of sEMG signal; the slope change number ( ) can perfectly indicate the state that the sEMG signal is about to fluctuate and change. The calculation formula is as follows:

[0116]

[0117]

[0118] Where: is a single-channel sEMG signal sequence, i=1,2,…,N; N is the length of the sEMG signal sequence used to calculate the eigenvalue, and the present invention selects N=200 sample points; , is the threshold value.

[0119] Median frequency ( ) and the average power frequency ( ) represent the frequency median and the average of the power frequency distribution of the sEMG signal respectively. The calculation formula is as follows:

[0120]

[0121]

[0122] Where: f is the frequency; is the power spectral density function of the sEMG signal; n is the number of sample points; is the integral accumulation function.

[0123] Using the above feature extraction method, each feature sample contains 6 EMG channels, each EMG channel is extracted separately. , , and These four electromyographic features form a 24-dimensional feature vector. The expression is as follows:

[0124] .

[0125] For example, taking the carrying of heavy objects, in a green converter station, a worker needs to carry a material weighing about 25 kg, and the walking distance is about 10 meters.

[0126] First, we conduct a biomechanical analysis of manual material handling. This analysis defines the orientation of the human body through three axes and three planes, including the sagittal axis, coronal axis, and vertical axis. The three planes are the horizontal plane, coronal plane, and sagittal plane. The motor sensor sampling frequency is 1000Hz, and the angle sensor collects joint angle data at a sampling frequency of 100Hz. The collection of these two types of data helps to accurately describe the limb movement of the human body, thereby analyzing the movement characteristics.

[0127] Then, we conducted a biomechanical analysis of the carrying scenario by creating a weight-carrying walking model in the sagittal plane. In this model, the torque generated by the weight on the arm is related to the mass of the weight and the holding position. For example, the torque generated is smaller when the weight is held closer to the body. When carrying and walking, if the weight is held closer to the body, the burden on the arm can be reduced.

[0128] Next, we conduct a biomechanical analysis of the arm lifting scenario. This analysis analyzes the repetitive lifting action by establishing a simplified biomechanical model. In this model, the strength of the back muscles is related to the mass of the heavy object being carried and the distance between the heavy object and the lumbar spine, as well as the angle at which the body leans forward. For example, the greater the bending angle, the greater the load on the back muscles.

[0129] The last part is the biomechanical analysis of weight-bearing scenarios, which analyzes weight-bearing actions by establishing a simplified biomechanical model. For example, the model observed that in a gait cycle, the movement angle of the hip joint shows a sinusoidal function change.

[0130] Finally, the RS-EMG8 biological signal amplification and acquisition system was used to obtain the electromyographic information corresponding to the human muscles. The preprocessed sEMG signal was de-noised using a 30-500 Hz Butterworth bandpass filter and a 50 Hz notch filter. Signal feature extraction used the root mean square value and slope change as time domain features and the median frequency and average power frequency as frequency domain features.

[0131] The embodiment of the present application provides a parameter determination method for a human exoskeleton. By determining the target motion parameters corresponding to the motion collection points based on the object information and the transport path, the target motion parameters actually required in the process of the target transport personnel transporting the target transport object can be determined. Further, through the difference between the target motion parameters and the motion data, the compensatory transport parameters required for the target exoskeleton-assisted transport can be determined. This can improve the accuracy of the assistance of the exoskeleton auxiliary equipment, improve the auxiliary effect of the exoskeleton auxiliary equipment, further improve the movement speed and work efficiency of the wearer, and reduce the safety risks of the wearer during the wearing process.

[0132] Based on the same inventive concept, the embodiment of the present application also provides a parameter determination device for a human exoskeleton for implementing the parameter determination method for a human exoskeleton involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the parameter determination device for a human exoskeleton provided below can refer to the limitations of the parameter determination method for a human exoskeleton above, and will not be repeated here.

[0133] As shown in Fig. 7, the second aspect of the embodiment of the present application provides a parameter determination device for a human exoskeleton, comprising: a first acquisition module 100, a second acquisition module 200, a first determination module 300, a third acquisition module 400, and a second determination module 500. The first acquisition module 100 is used to acquire the object information of the target transport object; the second acquisition module 200 is used to acquire the transport path of the target transport object; the first determination module 300 is used to determine the motion data collection points of the target transport personnel according to the object information and the transport path; the third acquisition module 400 is used to acquire the motion data of the target transport personnel based on the motion data collection points; the second determination module 500 is used to determine the compensation motion parameters of the target exoskeleton according to the object information, the transport path, and the motion data.

[0134] The embodiment of the present application provides a parameter determination device for a human exoskeleton. By acquiring the object information and the transport path of the target transport object, the main force-generating position and the main force-bearing position of the target transporter during the transport process can be determined. Further, the object information and the transport path of the target transport object can be used to determine the motion data collection point. The motion data of the position that is prone to fatigue or injury during the transport process can be collected, and the compensation motion parameters of the target exoskeleton can be determined based on the object information, the transport path and the motion data, so that the target exoskeleton can accurately assist the transporting activities of the target transporter based on the motion data required to complete the transport task and the motion data of the actual action of the target transporter. The accuracy of the assistance of the exoskeleton auxiliary equipment can be improved, the auxiliary effect of the exoskeleton auxiliary equipment can be improved, and the movement speed and work efficiency of the wearer can be further improved, and the safety risks of the wearer during the wearing process can be reduced.

[0135] Each module in the above-mentioned parameter determination device for human exoskeleton can be implemented in whole or in part by software, hardware and a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0136] FIG8 is a schematic structural diagram of a computer device provided in an embodiment of the present application. As shown in FIG8, in a third aspect of an embodiment of the present application, a computer device is provided, which may be a server. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, a near field communication (NearFieldCommunication, NFC) or other technologies. When the computer program is executed by the processor, a parameter determination method for a human exoskeleton is implemented. The display unit of the computer device is used to form a visually visible picture, and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball, or touchpad provided on the computer device housing, or an external keyboard, touchpad, or mouse, etc.

[0137] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0138] Fig. 9 is a schematic structural diagram of a computer-readable storage medium provided in an embodiment of the present application. As shown in Fig. 9, in a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the parameter determination methods for a human exoskeleton in the first aspect are implemented.

[0139] Figure 10 is a schematic structural diagram of a computer program product provided in an embodiment of the present application. As shown in Figure 10, in a fifth aspect of an embodiment of the present application, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any one of the above-mentioned first aspect of the method for determining parameters of a human exoskeleton.

[0140] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0141] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0142] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining parameters of a human exoskeleton, characterized in that: include: Obtaining object information of a target transport object; Acquire a transport path of the target transport object; Determine the movement data collection points of the target transporter according to the object information and the transport path; Based on the motion data collection points, acquiring motion data of the target transporter; The compensation motion parameters of the target exoskeleton are determined according to the object information, the transport path and the motion data.

2. The method for determining parameters of a human exoskeleton according to claim 1, characterized in that: The object information includes at least one of a shape, a weight, and a material of the target transport object.

3. The method for determining parameters of a human exoskeleton according to claim 1, characterized in that: The motion data includes at least one of muscle force information and bone curvature information corresponding to the motion data collection point.

4. The method for determining parameters of a human exoskeleton according to claim 1, characterized in that: The compensation motion parameter includes at least one of the motion form, support point position and support strength of the target exoskeleton.

5. The method for determining parameters of a human exoskeleton according to claim 1, characterized in that: Determining the movement data collection points of the target transporter according to the object information and the transport path includes: When it is determined according to the object information and the transport path that the target transport object is in the in-situ lifting mode, the motion acquisition point position includes at least one of a back muscle and a lumbar intervertebral disc; or, When it is determined that the target transport object is in the transport mode according to the object information and the transport path, the motion acquisition point includes at least one of an elbow joint, a shoulder joint and a lumbar intervertebral disc; or, When it is determined that the target transport object is in a weight-bearing motion mode according to the object information and the transport path, the motion collection point is determined to include at least one of a hip joint, a knee joint, and an ankle joint.

6. The method for determining parameters of a human exoskeleton according to claim 5, characterized in that: The step of determining the compensation motion parameters of the target exoskeleton according to the object information, the transport path and the motion data includes: Determining target motion parameters corresponding to the motion collection points according to the object information and the transport path; The compensation motion parameter of the target exoskeleton is determined based on the difference between the target motion parameter corresponding to the same motion acquisition point and the motion data.

7. A parameter determination device for a human exoskeleton, characterized in that: include: A first acquisition module, used to acquire object information of a target transport object; A second acquisition module, used to acquire a transport path of the target transport object; A first determination module is used to determine the movement data collection points of the target transporter according to the object information and the transport path; A third acquisition module is used to acquire the motion data of the target transporter based on the motion data collection points; The second determination module is used to determine the compensation motion parameters of the target exoskeleton according to the object information, the transport path and the motion data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the parameter determination method for a human exoskeleton according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the parameter determination method for a human exoskeleton according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the parameter determination method for a human exoskeleton according to any one of claims 1 to 6 are implemented.

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