CN113576845A - Human body consciousness recognition control device and method applied to exoskeleton robot - Google Patents
Human body consciousness recognition control device and method applied to exoskeleton robot Download PDFInfo
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- CN113576845A CN113576845A CN202110878653.XA CN202110878653A CN113576845A CN 113576845 A CN113576845 A CN 113576845A CN 202110878653 A CN202110878653 A CN 202110878653A CN 113576845 A CN113576845 A CN 113576845A
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- 238000000034 method Methods 0.000 title claims abstract description 19
- 230000005484 gravity Effects 0.000 claims abstract description 24
- 206010049816 Muscle tightness Diseases 0.000 claims abstract description 17
- 238000005259 measurement Methods 0.000 claims abstract description 6
- 210000000689 upper leg Anatomy 0.000 claims abstract description 4
- 230000008093 supporting effect Effects 0.000 claims description 14
- 230000003993 interaction Effects 0.000 claims description 7
- 230000010354 integration Effects 0.000 claims description 5
- 206010033799 Paralysis Diseases 0.000 description 7
- 230000009286 beneficial effect Effects 0.000 description 4
- 210000003141 lower extremity Anatomy 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 230000036316 preload Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 210000003414 extremity Anatomy 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 230000005021 gait Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
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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
- A61H3/00—Appliances for aiding patients or disabled persons to walk about
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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
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
- A61H2201/12—Driving means
- A61H2201/1207—Driving means with electric or magnetic drive
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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
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
- A61H2201/50—Control means thereof
- A61H2201/5007—Control means thereof computer controlled
- A61H2201/501—Control means thereof computer controlled connected to external computer devices or networks
- A61H2201/5015—Control means thereof computer controlled connected to external computer devices or networks using specific interfaces or standards, e.g. USB, serial, parallel
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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
- A61H2201/00—Characteristics of apparatus not provided for in the preceding codes
- A61H2201/50—Control means thereof
- A61H2201/5058—Sensors or detectors
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Abstract
本发明公开了一种应用于外骨骼机器人的人体意识识别控制装置及方法，包括重心测量系统、力矩传感器、姿态传感器、肌肉张力传感器、控制模块和报警模块；重心测量系统设置在外骨骼机器人的足部构件底部；力矩传感器设置在外骨骼机器人的外骨骼关节；姿态传感器设置在外骨骼机器人的腰部支撑构件内侧；肌肉张力传感器设置在外骨骼机器人的大腿杆件的内侧；控制模块，重心测量系统、力矩传感器、姿态传感器和肌肉张力传感器均与控制模块电性连接；报警模块与控制模块电性连接。本发明能够识别用户的控制意图，快速、精准的识别用户的行走意图并作出迈步响应，提升病患运动能力。
The invention discloses a human consciousness recognition control device and method applied to an exoskeleton robot, comprising a center of gravity measurement system, a torque sensor, an attitude sensor, a muscle tension sensor, a control module and an alarm module; the center of gravity measurement system is arranged on the foot of the exoskeleton robot. The torque sensor is arranged on the exoskeleton joint of the exoskeleton robot; the attitude sensor is arranged on the inner side of the waist support member of the exoskeleton robot; the muscle tension sensor is arranged on the inner side of the thigh rod of the exoskeleton robot; control module, center of gravity measurement system, torque sensor , the posture sensor and the muscle tension sensor are all electrically connected with the control module; the alarm module is electrically connected with the control module. The present invention can identify the user's control intention, quickly and accurately identify the user's walking intention and respond to stepping, thereby improving the patient's exercise ability.
Description
Technical Field
The invention relates to the technical field of exoskeleton robot control systems, in particular to a human consciousness recognition control device and method applied to an exoskeleton robot.
Background
The exoskeleton robot is a wearable mechatronic device, can be worn on limbs of an operator, and provides functions such as protection, body support, rehabilitation training, exercise assistance and the like for the operator. After the paralyzed patient wears the exoskeleton, the paralyzed patient can stand/sit down, walk, go upstairs and downstairs and the like as normal people under the supporting action of the exoskeleton and the power driving action of the exoskeleton, so that the quality and the pleasure of the life of the paralyzed patient can be greatly improved. The exoskeleton technology combines the robot technologies of sensing, control, information fusion, mobile computing and the like, and combines human intelligence and the 'physical strength' of the robot. The exoskeleton robot designed for the paralyzed patient combines biomedical engineering technologies such as biomechanics, gait analysis, sports medicine, rehabilitation engineering and the like to replace the lost lower limb movement function of the paralyzed patient, so that the paralyzed patient can regain normal movement ability.
For paralyzed patients with completely no perception and strength of lower limbs, the exoskeleton robot generally adopts a position control method, which relates to the purpose of acquiring people, so that the purpose is changed into a proper output force of a motor/hydraulic pressure. There are two ways to obtain human intent: directly obtaining the operator intention and indirectly obtaining the operator intention. Among the methods for directly acquiring the operator's intention are from EMG data or the interaction force between a person and a robot, and indirectly acquiring data from exoskeleton joints, predicting the operator's intention and then amplifying the exercise effect.
However, sensors for directly acquiring the operator intention are not mature enough, for example, data noise of EMG and difficulty of modeling and calibration are large, for example, an exoskeleton of Hybrid assisted limbus (HAL5) adopts EMG signals to control a robot, but 2 months of time is required to calibrate the EMG signals, and the indirectly acquired operator intention is easy to make a judgment, that is, the movement intention of a wearer cannot be quickly and accurately acquired automatically.
Therefore, it is an urgent need to solve the problems of the prior art to provide an accurate and fast human consciousness recognition control device and method for exoskeleton robots.
Disclosure of Invention
In view of the above, the present invention provides a human consciousness recognition control device and method applied to an exoskeleton robot, which has solved the technical problems of the background art mentioned above.
In order to achieve the purpose, the invention adopts the following technical scheme:
a human consciousness recognition control device applied to an exoskeleton robot comprises the exoskeleton robot and further comprises:
a center of gravity measurement system disposed at a bottom of a foot member of the exoskeleton robot;
a torque sensor disposed at an exoskeleton joint of the exoskeleton robot;
an attitude sensor disposed inside a lumbar support member of the exoskeleton robot;
a muscle tension sensor disposed inside a thigh lever of the exoskeleton robot;
the gravity center measuring system, the torque sensor, the attitude sensor and the muscle tension sensor are electrically connected with the control module;
and the alarm module is electrically connected with the control module.
By adopting the scheme, the invention has the beneficial effects that:
the gravity center measuring system, the torque sensor, the posture sensor and the muscle tension sensor are combined for use, data of all parts of the lower limb body are detected simultaneously, detected data information is transmitted to the control module for integration and analysis, the control intention of a user can be identified, the walking intention of the user can be identified quickly and accurately, a stepping response is made, and the motion capability of a patient is improved.
Further, the gravity center measuring system comprises a first supporting plate, a first elastic thin plate, a second supporting plate, a second elastic thin plate, a supporting column and four pressure sensors;
the first support plate is mounted at the bottom of the foot member; the first elastic thin plate is fixed at the bottom of the first supporting plate; the second support plate is positioned below the first support plate; the second elastic thin plate is fixed at the top of the second supporting plate; the first elastic thin plate and the second elastic thin plate are connected into a whole through the supporting columns; the four pressure sensors are respectively arranged at four corner ends of the top of the second supporting plate.
Adopt the beneficial effect that above-mentioned further technical scheme produced to be, set up four pressure sensor and be located four angle ends at the pressure-bearing position respectively, structural design is reasonable stable, can obtain accurate detection data, connects through the elasticity sheet metal between first backup pad and the second backup pad simultaneously, because the elasticity sheet metal is very easily out of shape, can make load weight all exert pressure on four pressure sensor, reduces holding power measuring error.
Further, the first supporting plate is mounted at the bottom of the foot member through four pre-tightening screws, and the bottoms of the four pre-tightening screws are respectively abutted to the four pressure sensors.
The beneficial effect that adopts above-mentioned further technical scheme to produce is, can adjust the initial force between pretension screw bottom and the pressure sensor, eliminates because of the negative zero offset of pressure sensor and the control module can not gather the error that the negative voltage formed.
A human consciousness recognition control method applied to an exoskeleton robot comprises the following steps:
1) the gravity center measuring system measures the sole counter force to obtain the gravity center position, so that the gravity center offset direction of the sole is induced, and data are transmitted to the control module; meanwhile, the torque sensor detects the interaction torque between the exoskeleton joint and the human body, transmits data to the control module, and dynamically adjusts the walking posture and the man-machine interaction torque; the gesture sensor detects the motion gesture of the user, transmits data to the control module, and predicts the motion intention of the user through an AI algorithm; the muscle tension sensor collects muscle tension parameters and transmits data to the control module;
2) the control module performs integration analysis on the acquired data to identify the control intention of the user;
3) when any acquired data exceeds or is smaller than the input normal numerical range, the control module drives the alarm module to operate.
By adopting the scheme, the invention has the beneficial effects that:
1) the method for directly acquiring the intention of the operator and the method for indirectly acquiring the intention of the operator are combined, data information acquired by each sensor is comprehensively considered, and is integrated and analyzed, so that the walking intention of the user is rapidly and accurately identified, and a stepping response is made;
2) any one of the detection data is abnormal, an alarm is given out, and the safety is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a human consciousness recognition control device applied to an exoskeleton robot, provided by the invention;
FIG. 2 is a schematic diagram of a gravity center measuring system according to the present invention;
fig. 3 is a flow chart of a human consciousness recognition control method applied to an exoskeleton robot according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 to 3, the embodiment of the present invention discloses a human consciousness recognition control device applied to an exoskeleton robot, including an exoskeleton robot, further including:
the gravity center measuring system 1 is arranged at the bottom of a foot component of the exoskeleton robot;
the torque sensor 2 is arranged on an exoskeleton joint of the exoskeleton robot;
an attitude sensor 3, the attitude sensor 3 being provided inside a lumbar support member of the exoskeleton robot;
the muscle tension sensor 4 is arranged on the inner side of a thigh rod piece of the exoskeleton robot;
the gravity center measuring system 1, the torque sensor 2, the attitude sensor 3 and the muscle tension sensor 4 are electrically connected with the control module;
and the alarm module is electrically connected with the control module.
According to the invention, the gravity center measuring system 1, the moment sensor 2, the attitude sensor 3 and the muscle tension sensor 4 are combined for use, data of each part of the lower limb body are detected simultaneously, and the detected data information is transmitted to the control module for integration and analysis, so that the control intention of a user can be identified, the walking intention of the user can be identified rapidly and accurately, a stepping response is made, and the movement capacity of a patient is improved.
Specifically, the gravity center measuring system 1 includes a first support plate 11, a first elastic thin plate 12, a second support plate 13, a second elastic thin plate 14, a support column 15 and four pressure sensors 16;
the first support plate 11 is mounted at the bottom of the foot member; the first elastic thin plate 12 is fixed at the bottom of the first supporting plate 11; the second support plate 13 is positioned below the first support plate 11; a second elastic sheet 14 is fixed on top of the second support plate 13; the first elastic sheet 12 and the second elastic sheet 14 are connected into a whole through a support pillar 15; four pressure sensors 16 are respectively provided at four corner ends of the top of the second support plate 13.
Specifically, the first support plate 11 is mounted on the bottom of the foot member by four preload screws 17, and the bottoms of the four preload screws 17 are abutted against the four pressure sensors 16, respectively.
The embodiment of the invention also discloses a human body consciousness recognition control method applied to the exoskeleton robot, which comprises the following steps:
1) the pressure sensor 16 of the gravity center measuring system 1 measures the sole reaction force to obtain the gravity center position, so as to sense the sole gravity center offset direction and transmit the data to the control module; meanwhile, the torque sensor 2 detects the interaction torque between the exoskeleton joint and the human body, transmits data to the control module, and dynamically adjusts the walking posture and the man-machine interaction torque; the gesture sensor 3 detects the motion gesture of the user, transmits data to the control module, and predicts the motion intention of the user through an AI algorithm; the muscle tension sensor 4 collects muscle tension parameters and transmits data to the control module;
2) the control module performs integration analysis on the acquired data to identify the control intention of the user;
3) when any acquired data exceeds or is smaller than the input normal numerical range, the control module drives the alarm module to operate.
The method combines a method for directly acquiring the intention of the operator with a method for indirectly acquiring the intention of the operator, comprehensively considers data information acquired by each sensor, integrates and analyzes the data information, quickly and accurately identifies the walking intention of the user and makes a stepping response; and any one detection data can give out an alarm when being abnormal, so that the safety is improved.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (4)
1. A human consciousness recognition control device applied to an exoskeleton robot comprises the exoskeleton robot and is characterized by further comprising:
a center of gravity measurement system disposed at a bottom of a foot member of the exoskeleton robot;
a torque sensor disposed at an exoskeleton joint of the exoskeleton robot;
an attitude sensor disposed inside a lumbar support member of the exoskeleton robot;
a muscle tension sensor disposed inside a thigh lever of the exoskeleton robot;
the gravity center measuring system, the torque sensor, the attitude sensor and the muscle tension sensor are electrically connected with the control module;
and the alarm module is electrically connected with the control module.
2. A human consciousness recognition control device applied to an exoskeleton robot as claimed in claim 1 wherein the gravity center measurement system comprises a first support plate, a first elastic thin plate, a second support plate, a second elastic thin plate, a support column and four pressure sensors;
the first support plate is mounted at the bottom of the foot member; the first elastic thin plate is fixed at the bottom of the first supporting plate; the second support plate is positioned below the first support plate; the second elastic thin plate is fixed at the top of the second supporting plate; the first elastic thin plate and the second elastic thin plate are connected into a whole through the supporting columns; the four pressure sensors are respectively arranged at four corner ends of the top of the second supporting plate.
3. The human body consciousness recognition and control device applied to an exoskeleton robot as claimed in claim 2, wherein the first support plate is mounted on the bottom of the foot member by four pre-tightening screws, and the bottom of the four pre-tightening screws abuts against the four pressure sensors respectively.
4. A human consciousness recognition control method applied to an exoskeleton robot is characterized by comprising the following steps:
1) the gravity center measuring system measures the sole counter force to obtain the gravity center position, so that the gravity center offset direction of the sole is induced, and data are transmitted to the control module; meanwhile, the torque sensor detects the interaction torque between the exoskeleton joint and the human body, transmits data to the control module, and dynamically adjusts the walking posture and the man-machine interaction torque; the gesture sensor detects the motion gesture of the user, transmits data to the control module, and predicts the motion intention of the user through an AI algorithm; the muscle tension sensor collects muscle tension parameters and transmits data to the control module;
2) the control module performs integration analysis on the acquired data to identify the control intention of the user;
3) when any acquired data exceeds or is smaller than the input normal numerical range, the control module drives the alarm module to operate.
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Cited By (1)
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| CN119748414A (en) * | 2025-01-20 | 2025-04-04 | 河北工润能源科技有限责任公司 | Human exoskeleton power assisting device applied to medium and large part replacement |
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