CN117860533A - Walking mode acquisition method and system of exoskeleton device - Google Patents
Walking mode acquisition method and system of exoskeleton device Download PDFInfo
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- 238000001514 detection method Methods 0.000 claims description 57
- 244000309466 calf Species 0.000 claims description 12
- 210000002414 leg Anatomy 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 9
- 210000002027 skeletal muscle Anatomy 0.000 claims description 8
- 241000489861 Maximus Species 0.000 claims description 4
- 210000003314 quadriceps muscle Anatomy 0.000 claims description 4
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- 210000003423 ankle Anatomy 0.000 description 4
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- A61H3/00—Appliances for aiding patients or disabled persons to walk about
- A61H2003/007—Appliances for aiding patients or disabled persons to walk about secured to the patient, e.g. with belts
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61H—PHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
- A61H2230/00—Measuring physical parameters of the user
- A61H2230/62—Posture
- A61H2230/625—Posture used as a control parameter for the apparatus
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Abstract
The invention belongs to the technical field of exoskeleton devices, and provides a walking mode acquisition method and system of an exoskeleton device, wherein the method comprises the following steps: step S1: detecting information of the muscular movement pressure of the thigh, information of the muscular movement pressure of the shank, and information of angles of the thigh and the shank when a wearer of the exoskeleton device walks; step S2: sampling the muscle movement pressure data based on the angle information to obtain denoised muscle movement pressure data; step S3: obtaining angle information and a scatter diagram of denoised muscle movement pressure data; step S4: and obtaining a walking pattern model according to the scatter diagram. According to the present invention, the exercise pressure of the muscle is detected in a partial area of the specific muscle distribution area, and the walking pattern of the wearer is obtained based on the detected pressure data and the angle information, so that the driving of the exoskeleton device is identical to the walking pattern of the user, and the walking fatigue of the user is reduced.
Description
Technical Field
The invention belongs to the technical field of exoskeleton devices, and particularly relates to a walking mode acquisition method and system of an exoskeleton device.
Background
Recently, with the development of robotics, the art is developing muscle assistance devices that assist in human movement. Some of the muscle assistance devices generate movement power using rotation of a motor, for example, korean laid-open patent: 10-2019-0004854 discloses a wearable muscle assistance device and a control method thereof; the above prior art documents include: the leg pulleys are arranged on two sides of the main body, and the plurality of steel wire parts are connected to the leg pulleys to provide tension for the plurality of steel wire parts and provide driving force for rotating the plurality of leg pulleys.
Most of the muscle assistance devices include a battery, a decelerator for decelerating the rotation of a motor and pulleys to replace joints of a human body, and generate driving forces to drive them according to a pre-stored driving control, and the prior art has mainly the following disadvantages: when a muscle assistance device (exoskeleton device) is used, if the driving of the exoskeleton device is different from the walking pattern of the user, the walking fatigue of the user increases.
Disclosure of Invention
The invention aims to provide a walking mode acquisition method of an exoskeleton device, which aims to solve the technical problems existing in the prior art.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a walking pattern acquisition method of an exoskeleton device, comprising:
step S1: detecting information of the muscular movement pressure of the thigh, information of the muscular movement pressure of the shank, and information of angles of the thigh and the shank when a wearer of the exoskeleton device walks;
step S2: sampling the muscle movement pressure data based on the angle information to obtain denoised muscle movement pressure data;
step S3: obtaining angle information and a scatter diagram of denoised muscle movement pressure data;
step S4: and obtaining a walking pattern model according to the scatter diagram.
In one embodiment, in the step S1, angle information of the thigh and the shank is detected by an upper side angle detection sensor and a lower side angle detection sensor mounted on the exoskeleton device; the pressure sensors worn on the legs of the wearer detect the thigh muscle movement pressure information and the calf muscle movement pressure information.
In one embodiment, in the step S1, detecting the information of the muscular movement pressure of the thigh includes: the movements of at least 1 or more of the iliotibial band, rectus femoris, sartorius, mid-thigh, ilio-psoas constituting the anterior thigh muscle, the gluteus maximus, adductor femoris, semitendinosus, gracilis, semimembrana, and biceps thigh; the detection of the muscle movement pressure information of the lower leg includes movement of the gastrocnemius muscle or the soleus muscle constituting the rear lower leg muscle.
In one embodiment, the specific method of step S2 is as follows:
step S2.1: obtaining a covariance matrix of the muscle movement pressure data based on the angle information, and calculating a data interval distance according to formula (1) based on the covariance matrix:(1) In Sigma -1 Representing a covariance matrix, wherein, a letter represents a data vector, μ represents an average vector, and T represents a transpose;
step S2.2: calculating a cut-off region by using chi-square distribution;
step S2.3: and judging the data exceeding the cut-off area as noise, and sampling the data in the cut-off area as effective data to obtain denoised muscle movement pressure data.
In one embodiment, the specific method of step S3 is as follows:
step S3.1: calculating the covariance of the angle information and the denoised muscle movement pressure data;
step S3.2: normalizing the covariance and calculating a correlation coefficient by the formula (2)：/>（2）
Wherein S is angle information, E is denoised muscle movement pressure data;
step S3.3: and obtaining a scatter diagram corresponding to the angle information according to the correlation coefficient.
In one embodiment, the specific method of step S4 is as follows:
applying the scatter plot to the single detection data according to equation (3) to obtain a walking pattern model:(3) Wherein e is the detection data, alpha is the angle correction constant, beta is the scatter plot of the individual detection data, < >>The walking model data is represented, and n represents a constant.
In order to achieve the above object, the present invention provides a walking pattern acquisition system for implementing the walking pattern acquisition method of an exoskeleton device described above, comprising:
a pressure detecting section including an upper pressure detecting unit for detecting movement of thigh muscles of a wearer, and a lower pressure detecting unit for detecting movement of calf muscles of the wearer;
an exoskeleton device including a body and left and right connectors;
an angle detection unit which is mounted on the exoskeleton device and is used for detecting angle information between thigh wires and shank wires of waist wires of a wearer; the angle detection part comprises an upper side angle detection sensor and a lower side angle detection sensor which are installed on the exoskeleton device;
the controller comprises a signal sampling module for sampling the muscle movement pressure information based on the angle information, a related calculating module for calculating a scatter diagram of the angle information and the detection data, and a walking mode obtaining module for obtaining a walking mode model based on the scatter diagram and the muscle movement pressure information.
Further, the left and right connecting bodies comprise middle supporting bodies, upper supporting bodies connected with the upper sides of the middle supporting bodies, lower supporting bodies connected with the lower sides of the middle supporting bodies, and foot seats connected with the lower supporting bodies; the upper side angle detection sensor is used for detecting an angle formed by the middle support body and the upper side support body, and the lower side angle detection sensor is used for detecting an angle formed by the middle support body and the lower side support body.
Further, a battery is mounted on the main body, and the controller is arranged on the main body.
Further, the intermediate support body is provided with an upper driving part for driving the upper support body and a lower driving part for driving the lower support body.
Compared with the prior art, the invention has the following beneficial effects:
(1) According to the invention, the exercise pressure of the muscle is detected in a part of the specific muscle distribution field, and the walking mode of the wearer is obtained based on the detected pressure data and the angle information, so that the driving of the exoskeleton device is the same as the walking mode of the user, and the walking fatigue of the user is reduced, thereby effectively solving the problems existing in the prior art;
(2) According to the present invention, driving control of the exoskeleton device can be performed using leg muscle movement pressure information of a wearer wearing the exoskeleton device, and angle control optimized for the walking pattern of the wearer can be performed.
Drawings
Fig. 1 is a schematic diagram showing the wearing state of the present invention-example 1.
Fig. 2 is a schematic structural view of the pressure detecting portion in embodiment 1 of the present invention.
Fig. 3 is a schematic view of the structure of the exoskeleton device of embodiment 1 of the present invention.
FIG. 4 is a schematic diagram of the structure of the left and right connectors in the embodiment 1 of the present invention.
Fig. 5 is a schematic diagram of the controller in embodiment 1 of the present invention.
Fig. 6 is a schematic diagram showing correlation between detection data and angle data of a pressure sensor.
FIG. 7 is a schematic flow chart of the present invention-example 2.
Wherein, the names corresponding to the reference numerals are as follows: 100-a pressure detection part; 200-exoskeleton device; 300-an angle detection section; 400-a controller;
an upper pressure detection unit, 120-a lower pressure detection unit; 1101-pressure sensor, 1102-magic tape;
a main body, 220-left and right connectors; 221-middle support body, 222-upper side support body, 223-lower side support body, 224-foot seat and 225-connection table;
2211-upper side drive, 2212-lower side drive, 2213-cover; 2241-fixed rings and 2242-bending parts;
410-a signal sampling module, 420-a correlation calculation module, 430-a walking pattern acquisition module.
Detailed Description
The present invention will be further described in detail with reference to examples so as to enable those skilled in the art to more clearly understand and understand the present invention. It should be understood that the following specific embodiments are only for explaining the present invention, and it is convenient to understand that the technical solutions provided by the present invention are not limited to the technical solutions provided by the following embodiments, and the technical solutions provided by the embodiments should not limit the protection scope of the present invention.
Unless otherwise defined, technical or scientific terms used in the present disclosure should be given the ordinary meaning as understood by one of ordinary skill in the art to which the present disclosure pertains. The use of the terms "comprising" or "includes" and the like in this application is intended to cover an element or article appearing before the term but not to exclude other elements or articles from the list of elements or articles appearing after the term and the equivalents thereof. The positions Guan Jici "up", "down", "left", "right", "front", "rear", and the like are determined in accordance with the layout directions of the drawings of the specification, and are merely for representing the relative positional relationship, which is also likely to be changed when the absolute position of the object to be described is changed.
Examples
As shown in fig. 1 to 5, the present embodiment provides a walking pattern acquisition system, which includes a pressure detection unit, an exoskeleton device, an angle detection unit, and a controller; the pressure detection part is used for detecting pressure information according to leg muscle movement of a wearer, the exoskeleton device is used for being worn, the angle detection part is arranged on the exoskeleton device and used for detecting angle information between thigh wires and shank wires of waist wires of the wearer, and the controller is used for receiving data, processing the data, generating and sending control signals and the like.
In this embodiment, the pressure detecting portion includes an upper pressure detecting unit for detecting movement of the thigh muscle of the wearer, and a lower pressure detecting unit for detecting movement of the calf muscle of the wearer. The upper pressure detecting unit and the lower pressure detecting unit may be respectively worn on the left and right legs of the wearer, and in this embodiment, the upper pressure detecting unit and the lower pressure detecting unit are identical in structure, and include a pad having a belt shape and at least two pressure sensors mounted on the pad with the upper pressure detecting unit as a description reference.
Preferably, the upper detection unit may detect movements of at least 1 or more of iliotibial band, rectus femoris, sartorius, mid-thigh, ilio-psoas constituting the anterior thigh muscle, and may detect movements of at least 1 or more of gluteus maximus, adductor femoris, semitendinous, gracilis, semimembranous, and biceps thigh muscle constituting the posterior thigh muscle; the lower detection unit may detect the movement of gastrocnemius muscle or soleus muscle constituting the rear side calf muscle.
It should be noted that any muscle object can detect different pressure values according to the position; based on the above-described detection object, preferably, the pressure sensor is provided in an area where the front thigh muscle, the rear thigh muscle, and the rear calf muscle are located. In this embodiment, the magnitude of pressure data according to the position muscle movement is focused, and thus, the pressure sensor can be installed in an area where a specific muscle is expected to exist, and can be attached anywhere in the area where a muscle exists.
The pressure information of the muscle movement detected by the upper pressure detecting unit and the lower pressure detecting unit, that is, pressure data is transmitted to the controller.
In this example, the exoskeleton device includes a main body and left and right connectors, the main body is mounted on the back of the human body when worn, the main body includes a housing, a battery and a controller are disposed in the housing, the battery is used for supplying power to the pressure detection portion, the angle detection portion and the controller, and meanwhile, the battery also supplies power for driving the exoskeleton device, and as a preferred choice, the battery is a rechargeable battery; the shape of the housing is not particularly limited, and a regular rectangular shape or the like may be generally employed.
The main body and the left and right connectors are respectively connected through the left and right connecting tables. The connection table extends from the lower portion of the main body from left and right sides, then bends forward, and then bends downward, and its specific structure is as follows: the connecting table comprises a first L-shaped structural member and a second L-shaped structural member, wherein the first L-shaped structural member is positioned at the lower part of the main body, one end of the first L-shaped structural member is vertically connected with the first L-shaped structural member, the other end of the first L-shaped structural member is vertically connected with one end of the second L-shaped structural member, and the other end of the second L-shaped structural member is connected with the left and right connecting bodies.
The left and right connectors comprise a middle support body, an upper support body connected with the upper side of the middle support body, a lower support body connected with the lower side of the middle support body, and a foot seat connected with the lower support body.
The middle support body is provided with an upper driving part and a lower driving part, the upper driving part drives the upper support body, and the lower driving part drives the lower support body; the upper driving part and the lower driving part have the same structure, and the upper driving part is used as a description reference, and comprises a driving motor and a speed reducer connected with the driving motor. The driving motor is powered by a battery, the driving motor generates a rotating force, the speed reducer reduces the rotation times of the driving motor, and the rotating torque is increased.
The foot supporting body comprises a fixing ring which wraps the ankle of a wearer and bending parts which are fixed on two sides of the fixing ring and support the sole of the wearer, wherein the fixing ring can be composed of a fixing semicircular ring fixed on the lower side bracket and a rotating semicircular ring connected with the fixing semicircular ring. As an example, the rotary semicircle is connected from the fixing semicircle, the ankle of the wearer is fixed inside the fixing semicircle, and then the rotary semicircle is closed on the fixing semicircle.
In the embodiment, the connecting port is arranged on the main body of the exoskeleton device, and the connecting port can be firmly fixed on the upper body of the human body; in addition, a foot stand is connected at the ankle of the wearer, and thus, the upper side support and the lower side support are respectively fixed to the upper body and the ankle, and the upper side support, the middle support, and the lower side support may be connected at a predetermined angle when walking.
The angle detection part is arranged on the exoskeleton device, specifically, the angle detection part is arranged on the left and right connectors of the exoskeleton device and is used for detecting angle information between thigh wires and shank wires of waist wires of a wearer.
In this embodiment, the angle detection section includes an upper side angle detection sensor and a lower side angle detection sensor mounted on the left and right connection bodies; the upper side angle detection sensor is used for detecting an angle formed by the middle support body and the upper side support body, and the lower side angle detection sensor is used for detecting an angle formed by the middle support body and the lower side support body.
The detected pressure information and angle information of the muscle movement are generated to the controller, and meanwhile, the controller can generate control instructions according to the received information and is used for driving and controlling the upper driving part and the lower driving part so as to realize driving and controlling of the exoskeleton device.
In this embodiment, according to the functional module distinction, the controller includes a signal sampling module that samples the muscle movement pressure information based on the angle information, a correlation calculation module that calculates a scatter pattern of the angle information and the detection data, and a walking pattern acquisition module that obtains a walking pattern model based on the scatter pattern and the muscle movement pressure information. It should be noted that, the controller includes a CPU, the model is samsung artik-710, the hardware structure of the controller adopts the existing mature hardware structure, and the above functional modules are used to implement the corresponding program and can be integrated in the CPU, so the hardware structure is not described herein.
Examples
As shown in fig. 6 and 7, wherein the ordinate of fig. 6 is pressure and the abscissa is angle, the present embodiment provides a walking pattern obtaining method of an exoskeleton device, which includes the following steps:
step S1: detecting information on thigh muscle movement pressure, information on calf muscle movement pressure, and information on thigh and calf angle while walking by a wearer of the exoskeleton device
In this step, angle information of the thigh and the shank is detected by an upper side angle detection sensor and a lower side angle detection sensor mounted on the exoskeleton device; the pressure sensors worn on the legs of the wearer detect the thigh muscle movement pressure information and the calf muscle movement pressure information.
Detecting muscle movement pressure information of the thigh includes: the movements of at least 1 or more of the iliotibial band, rectus femoris, sartorius, mid-thigh, ilio-psoas constituting the anterior thigh muscle, the gluteus maximus, adductor femoris, semitendinosus, gracilis, semimembrana, and biceps thigh; the detection of the muscle movement pressure information of the lower leg includes movement of the gastrocnemius muscle or the soleus muscle constituting the rear lower leg muscle.
It should be noted that any muscle object can detect different pressure values according to the position; based on the above-described detection object, preferably, the pressure sensor is provided in an area where the front thigh muscle, the rear thigh muscle, and the rear calf muscle are located. In this embodiment, the magnitude of pressure data according to the position muscle movement is focused, and thus, the pressure sensor can be installed in an area where a specific muscle is expected to exist, and can be attached anywhere in the area where a muscle exists.
The detected pressure information and angle information are sent to a controller where the data is processed.
Step S2: sampling the muscle movement pressure data based on the angle information to obtain denoised muscle movement pressure data
The method is implemented in a signal sampling module of a controller, and comprises the following steps:
step S2.1, obtaining a covariance matrix of the muscle movement pressure data based on the angle information, and calculating a data interval distance according to a formula (1) based on the covariance matrix:(1) In Sigma -1 Representing a covariance matrix, wherein, a letter represents a data vector, μ represents an average vector, and T represents a transpose;
step S2.2: calculating a cut-off region by using chi-square distribution;
step S2.3: and judging the data exceeding the cut-off area as noise, and sampling the data in the cut-off area as effective data to obtain denoised muscle movement pressure data.
Fig. 6 shows a correlation diagram between detection data and angle data of the pressure sensor, and in fig. 6, an icon R indicates a cut-off region.
Step S3: scatter plot for obtaining angle information and denoised muscle movement pressure data
The method is implemented in a related calculation module of the controller, and comprises the following steps:
step S3.1: calculating the covariance of the angle information and the denoised muscle movement pressure data;
step S3.2: normalizing the covariance and calculating the correlation coefficient by the formula (2)：(2) Wherein S is angle information, E is denoised muscle movement pressure data;
step S3.3: and obtaining a scatter diagram corresponding to the angle information according to the correlation coefficient.
The calculated correlation coefficient is used as a scatter plot of the individual sensed data of the angle information. The calculated correlation coefficient may be a value between 0.4 and 0.95.
Step S4: obtaining walking pattern model from scatter diagram
This step is performed in a walking pattern acquisition module of the controller, and according to formula (3), a walking pattern model is obtained by applying the scatter pattern to the single detection data:(3) Wherein e is the detection data, alpha is the angle correction constant, beta is the scatter plot of the individual detection data, < >>The walking model data is represented, and n represents a constant.
In the formula (3), the detection data may select at least 3 to 5 sensors in order of magnitude.
In this embodiment, the walking mode obtaining method may be implemented by a combination of hardware-driven software, and the walking mode model includes a plurality of walking mode models, and is pre-stored in the walking mode obtaining module, and the optimal walking model is calculated by reading the number of the angle sensors and the pressure sensors during walking, so as to control the exoskeleton to operate at an optimal angle according to the walking mode when the walking mode is used with the exoskeleton, and the wearer walks with an optimal gait. The hardware may be a data processing apparatus including a processor, and the software driven by the hardware may be a program running on the processor.
By the above method, after obtaining the walking pattern of the wearer wearing the exoskeleton device, walking driving conforming to the walking pattern of the wearer can be performed by driving the exoskeleton device, so that the optimal angle of walking of the wearer can be controlled.
The muscle movement formed during walking, each person and each step uses different thigh and shank muscles, if the walking aid is driven on the basis of uniform muscle movement, the person wearing the walking aid will perform unnatural walking actions, and finally the muscles will feel burden, and walking fatigue is easily felt; according to the method of the present invention, the movement pressure of the muscles detected in the partial region of the specific muscle distribution region is detected, and the walking pattern of the wearer is obtained based on the detected pressure data and the angle information, so that the walking fatigue of the wearer can be effectively reduced.
The foregoing is a preferred embodiment of the present invention. It should be noted that those skilled in the art may make several modifications without departing from the design principles and technical solutions of the present invention, and these modifications should also be considered as the protection scope of the present invention.
Claims (10)
1. A walking pattern acquisition method of an exoskeleton device, comprising:
step S1: detecting information of the muscular movement pressure of the thigh, information of the muscular movement pressure of the shank, and information of angles of the thigh and the shank when a wearer of the exoskeleton device walks;
step S2: sampling the muscle movement pressure data based on the angle information to obtain denoised muscle movement pressure data;
step S3: obtaining angle information and a scatter diagram of denoised muscle movement pressure data;
step S4: and obtaining a walking pattern model according to the scatter diagram.
2. The walking pattern acquisition method of an exoskeleton device according to claim 1, wherein: in the step S1, angle information of the thigh and the shank is detected by an upper side angle detection sensor and a lower side angle detection sensor mounted on the exoskeleton device; the pressure sensors worn on the legs of the wearer detect the thigh muscle movement pressure information and the calf muscle movement pressure information.
3. The walking pattern acquisition method of an exoskeleton device according to claim 2, wherein: in the step S1, detecting the information of the muscular movement pressure of the thigh includes: the movements of at least 1 or more of the iliotibial band, rectus femoris, sartorius, mid-thigh, ilio-psoas constituting the anterior thigh muscle, the gluteus maximus, adductor femoris, semitendinosus, gracilis, semimembrana, and biceps thigh; the detection of the muscle movement pressure information of the lower leg includes movement of the gastrocnemius muscle or the soleus muscle constituting the rear lower leg muscle.
4. A walking pattern acquisition method of an exoskeleton device according to claim 3, wherein: the specific method of the step S2 is as follows:
step S2.1: obtaining a covariance matrix of the muscle movement pressure data based on the angle information, and calculating a data interval distance according to formula (1) based on the covariance matrix:
(1) In Sigma -1 Representing a covariance matrix, wherein, a letter represents a data vector, μ represents an average vector, and T represents a transpose; step S2.2: calculating a cut-off region by using chi-square distribution;
step S2.3: and judging the data exceeding the cut-off area as noise, and sampling the data in the cut-off area as effective data to obtain denoised muscle movement pressure data.
5. The walking pattern acquisition method of an exoskeleton device according to claim 4, wherein: the specific method of the step S3 is as follows:
step S3.1: calculating the covariance of the angle information and the denoised muscle movement pressure data;
step S3.2: normalizing the covariance and calculating a correlation coefficient by the formula (2)：（2）
Wherein S is angle information, E is denoised muscle movement pressure data;
step S3.3: and obtaining a scatter diagram corresponding to the angle information according to the correlation coefficient.
6. The walking pattern acquisition method of an exoskeleton device according to claim 5, wherein: the specific method of the step S4 is as follows:
applying the scatter plot to the single detection data according to equation (3) to obtain a walking pattern model:（3）
where e is the detection data, alpha is the angle correction constant, beta is the scatter plot of the individual detection data,the walking model data is represented, and n represents a constant.
7. A walking pattern acquisition system for implementing the walking pattern acquisition method of an exoskeleton device according to any one of claims 1 to 6, comprising:
a pressure detecting section (100) including an upper pressure detecting unit (110) for detecting movement of thigh muscles of a wearer, and a lower pressure detecting unit (120) for detecting movement of calf muscles of the wearer;
an exoskeleton device (200) comprising a body (210) and left and right connectors (220);
an angle detection unit (300) that is mounted on the exoskeleton device (200) and detects angle information between thigh and thigh lines and angle information between thigh and calf lines of a waist line of a wearer; the angle detection part (300) comprises an upper side angle detection sensor and a lower side angle detection sensor which are installed on the exoskeleton device (200);
a controller (400) including a signal sampling module (410) that samples muscle movement pressure information based on the angle information, a correlation calculation module (420) that calculates a scatter pattern of the angle information and the detection data, and a walking pattern acquisition module (430) that obtains a walking pattern model based on the scatter pattern and the muscle movement pressure information.
8. The walking pattern acquisition system of claim 7, wherein: the left and right connectors (220) comprise a middle support body (221), an upper support body (222) connected with the upper side of the middle support body (221), a lower support body (223) connected with the lower side, and a foot seat (224) connected with the lower support body (223); the upper side angle detection sensor is used for detecting an angle formed by the middle support body (221) and the upper side support body (222), and the lower side angle detection sensor is used for detecting an angle formed by the middle support body (221) and the lower side support body (223).
9. The walking pattern acquisition system of claim 8, wherein: the main body (210) is provided with a battery, and the controller (400) is arranged on the main body (210).
10. The walking pattern acquisition system of claim 9, wherein: the intermediate support body (221) is provided with an upper driving part (2211) for driving the upper support body (222), and a lower driving part (2212) for driving the lower support body (223).
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