CN117672452A - Analysis and control system for human gait by brain-computer interface technology in virtual environment - Google Patents
Analysis and control system for human gait by brain-computer interface technology in virtual environment Download PDFInfo
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- CN117672452A CN117672452A CN202211005870.9A CN202211005870A CN117672452A CN 117672452 A CN117672452 A CN 117672452A CN 202211005870 A CN202211005870 A CN 202211005870A CN 117672452 A CN117672452 A CN 117672452A
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- 238000004458 analytical method Methods 0.000 title claims abstract description 69
- 230000005021 gait Effects 0.000 title claims abstract description 30
- 238000005516 engineering process Methods 0.000 title claims abstract description 15
- 210000003141 lower extremity Anatomy 0.000 claims abstract description 10
- 230000009471 action Effects 0.000 claims description 13
- 230000001133 acceleration Effects 0.000 claims description 12
- 210000002414 leg Anatomy 0.000 claims description 11
- 238000000034 method Methods 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 7
- 210000000689 upper leg Anatomy 0.000 claims description 6
- 210000000544 articulatio talocruralis Anatomy 0.000 claims description 5
- 210000002683 foot Anatomy 0.000 claims description 4
- 210000004556 brain Anatomy 0.000 claims description 3
- 210000003414 extremity Anatomy 0.000 claims description 3
- 210000004394 hip joint Anatomy 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 claims description 3
- 230000008859 change Effects 0.000 description 5
- 230000001276 controlling effect Effects 0.000 description 5
- 230000005484 gravity Effects 0.000 description 4
- 238000012549 training Methods 0.000 description 4
- 238000007405 data analysis Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000036544 posture Effects 0.000 description 2
- 208000024172 Cardiovascular disease Diseases 0.000 description 1
- 210000003423 ankle Anatomy 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 208000026106 cerebrovascular disease Diseases 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000002526 effect on cardiovascular system Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000003238 somatosensory effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000008733 trauma Effects 0.000 description 1
- 239000013585 weight reducing agent Substances 0.000 description 1
- 238000003466 welding Methods 0.000 description 1
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The utility model discloses an analysis and control system for human gait of brain-computer interface technology in a virtual environment, which comprises a brain-computer interface module, a rehabilitation robot module, a sensor module, a camera module, a virtual environment module and a servo control module which are all electrically connected with an analysis host, wherein the servo control module is electrically connected with a treadmill module; the analysis host computer is used for analyzing the information of the brain-computer interface module, the sensor module and the camera module, controlling the rehabilitation robot module and the running machine module to run according to the analysis result, generating an analysis report, and controlling the virtual environment module to display the virtual environment information. The camera module can shoot the gait of the patient from multiple angles, and meanwhile, the gait of the patient is comprehensively analyzed through software in the host by combining the data of the sensor module, so that the problems and the rehabilitation condition of the patient are judged; the lower limbs of the patient are supported by the rehabilitation robot, so that the patient can perform rehabilitation exercise under the real condition.
Description
Technical Field
The utility model relates to the technical field of rehabilitation instruments, in particular to an analysis and control system for human gait in a virtual environment by brain-computer interface technology.
Background
Along with the development of society and the continuous improvement of the level of life and the material condition of people, people also pay more and more attention to the health of themselves and families. Some patients can walk normally through a series of rehabilitation exercises due to trauma, cardiovascular and cerebrovascular diseases or long bedridden time. The traditional rehabilitation process is realized by nurses or families supporting the patients to move downwards, but the method consumes energy and physical strength, can not take correct rehabilitation training postures, has poor rehabilitation effect, and can not timely analyze the rehabilitation condition of the patients to adjust in time. At present, equipment for such rehabilitation also appears, for example, chinese patent application publication No. CN209347037U discloses a multifunctional somatosensory gait analysis training system which comprises a comprehensive evaluation analysis module, a medical bidirectional jogging platform, a top rail weight reduction module, a gait balance analysis module, a scene interaction and posture training module and a surface myoelectricity analysis module which are connected with the comprehensive evaluation analysis module; however, this apparatus is not supported on the legs of the patient, and the running machine is controlled by frequency conversion, which is inconvenient for the patient, for example, the patient who can take one step for a long time is not friendly.
Disclosure of Invention
The utility model provides an analysis and control system for human gait of brain-computer interface technology in a virtual environment, which aims to make up the defects of the prior art.
The utility model is realized by the following technical scheme:
the brain-computer interface technology is used for analyzing and controlling human gait in a virtual environment, and comprises a brain-computer interface module, a rehabilitation robot module, a sensor module, a camera module, a virtual environment module and a servo control module which are all electrically connected with an analysis host, wherein the servo control module is electrically connected with a running machine module; the brain-computer interface module is worn on the head of the patient and used for acquiring brain-computer signals of the patient; the rehabilitation robot module is worn on the lower limb of the patient and is used for receiving an action instruction sent by the analysis host according to the brain electrical signal of the patient and driving the lower limb of the patient to move or moving along the limb of the patient according to the instruction sent by the analysis host; the camera module is used for shooting the gait of the patient from a plurality of angles and transmitting the gait back to the analysis host, the virtual environment module is used for providing a virtual environment for the patient, and the servo control module is used for receiving the instruction of the analysis host and controlling the running machine to run; the sensor module is used for monitoring foot sole pressure, shoulder tension and acceleration data of legs of a patient in the rehabilitation process and sending the foot sole pressure, shoulder tension and acceleration data to the analysis host; the analysis host analyzes the information of the brain-computer interface module, the sensor module and the camera module, controls the rehabilitation robot module and the running machine module to operate according to analysis results, generates an analysis report, and is also used for controlling the virtual environment module to display virtual environment information.
The running machine module comprises a running machine provided with a rear vertical frame and a front vertical frame, two second cross beams are arranged between the rear vertical frame and the front vertical frame, a tension sensor is fixedly arranged on each second cross beam, and the tension sensor is connected with a waistcoat through a pull rope.
The rehabilitation robot module consists of a hip joint exoskeleton, a thigh exoskeleton, a shank exoskeleton, an ankle joint exoskeleton and a sole exoskeleton, wherein acceleration sensors are installed on the thigh exoskeleton, the shank exoskeleton and the ankle joint exoskeleton, and sole pressure sensors are installed on the sole exoskeleton.
The camera module comprises a first camera fixedly mounted on the support, and the first camera is opposite to the running machine.
The camera module comprises a second camera installed on the rear vertical frame and a third camera installed on the front vertical frame.
The second camera and the third camera are installed in a central symmetry mode.
The analysis host computer comprises a display, a mouse, a keyboard and a printer which are electrically connected with the workstation.
The analysis host computer is also used for carrying out mode selection, wherein the mode selection comprises an active rehabilitation mode and a passive rehabilitation mode.
The utility model has the following technical effects:
the camera module can shoot the gait of the patient from multiple angles, and simultaneously combines the sole pressure data, the acceleration speed sensor data and the tension sensor data on the rehabilitation robot, and comprehensively analyzes the gait of the patient through the host to judge the problems and the rehabilitation condition of the patient; the lower limbs of the patient are supported by the rehabilitation robot, so that the patient can perform rehabilitation movement under the real condition; the camera module is connected with the running machine module, and the host machine analyzes leg movements of patients shot by the camera and sends control commands to the servo control module to control running of the running machine, so that the running machine module can adapt to the requirements of patients in different conditions; the brain-computer interface module and the rehabilitation robot can be used for assisting a patient in rehabilitation exercise.
Drawings
The utility model is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic structural view of the present utility model.
Fig. 2 is a schematic structural view of the treadmill module and the rehabilitation robot module.
In the figure, the device comprises a 1-running machine, a 2-handrail, a 3-rear vertical frame, a 4-sole exoskeleton, a 5-thigh exoskeleton, a 6-hip exoskeleton, a 7-front vertical frame, an 8-bracket, a 9-first beam, a 10-first camera, a 11-display screen, a 12-second beam, a 13-stay rope, a 14-waistcoat and a 15-second camera.
Detailed Description
The following is only a specific embodiment of the present utility model, but the scope of the present utility model is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the technical scope of the present utility model should be included in the scope of the present utility model.
Words describing the directional relationship of "front", "rear", "inner", "outer", etc. in the present utility model are merely for convenience of description of the embodiments, and are not to be construed as limiting the utility model. The terms "first," "second," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance. The fixed connection mode comprises, but is not limited to, welding, screwing, clamping, interference fit and integrated forming.
Fig. 1 and 2 illustrate an embodiment of the present utility model. The embodiment provides an analysis and control system for human gait by brain-computer interface technology under a virtual environment, which comprises a brain-computer interface module, a rehabilitation robot module, a sensor module, a camera module, a virtual environment module and a servo control module which are all electrically connected with an analysis host, wherein the servo control module is electrically connected with a treadmill module.
The brain-computer interface module is worn on the head of the patient and used for acquiring brain-computer signals of the patient and sending the brain-computer signals to the analysis host;
the rehabilitation robot module is worn on the lower limb of a patient, can support the patient, can receive an action instruction sent by an analysis host according to the brain electrical signal of the patient, drives the lower limb of the patient to move, and can also move along with the limb of the patient according to the instruction sent by the analysis host.
The camera module is used for shooting the gait of the patient from a plurality of angles and sending the shot image information to the analysis host.
The virtual environment module is used for providing a virtual environment for a patient.
The servo control module is used for receiving the instruction of the analysis host computer and controlling the running machine to run.
The analysis host analyzes the information of the brain-computer interface module, the sensor module and the camera module, controls the rehabilitation robot module and the running machine module to operate according to the analysis result, and generates an analysis report through the analysis of the acquired data; and the virtual environment module is also used for controlling the virtual environment module to display the virtual environment information.
The sensor module comprises a tension sensor, a pressure sensor and an acceleration sensor, and is used for monitoring data such as sole pressure, shoulder tension, acceleration of legs and the like of a patient in the rehabilitation process and sending the data to the analysis host.
The analysis host comprises a display, a mouse, a keyboard and a printer, wherein the display, the mouse, the keyboard and the printer are electrically connected with the workstation, the workstation is used for data analysis, automatic instruction generation and the like, the display is used for displaying information needed to be seen by medical staff, the mouse and the keyboard are used for inputting manual commands such as parameter setting, mode selection and the like, and the printer is used for printing paper analysis reports. The mode selection includes an active rehabilitation mode and a passive rehabilitation mode.
As shown in fig. 2, the running machine module comprises a running machine 1, a gantry-shaped rear vertical frame 3 and a front vertical frame 7 are fixedly arranged on the running machine 1, two second cross beams 12 are arranged between the rear vertical frame 3 and the front vertical frame 7, two ends of each second cross beam 12 are fixedly connected with the tops of the rear vertical frame 3 and the front vertical frame 7 respectively, and a gap is reserved between the two second cross beams 12. And the two second cross beams 12 are fixedly provided with tension sensors, the tension sensors are connected with the waistcoat 14 through stay ropes 13, and the connection points of the stay ropes 13 of the two tension sensors and the waistcoat 14 are respectively positioned at the left shoulder and the right shoulder of the waistcoat. The waistcoat 14 is worn on the patient and is fixed to the patient by being matched with the stay cord 13.
Handrails 2 are also installed on two sides of the running machine 1.
The rehabilitation robot module consists of a hip joint exoskeleton 6, a thigh exoskeleton 5, a shank exoskeleton, an ankle joint exoskeleton and a sole exoskeleton 4; acceleration sensors are mounted on the thigh exoskeleton 5, the shank exoskeleton, and the ankle exoskeleton, and sole pressure sensors are mounted on the sole exoskeleton 4. The acceleration sensor is used for detecting the movement condition of each part of the patient when the legs move, the sole pressure sensor is used for sensing the pressure change of each part of the sole when the legs move, and the change of the center of gravity of the sole is analyzed.
The sole pressure sensor is also matched with the tension sensor, and the analysis host analyzes the change of the gravity center of the human body in the movement process through the data analysis of the sole pressure sensor and the tension sensor; the analysis host computer also can analyze the skew of patient's backbone and whole upper body in the motion process through the data analysis tension sensor, is convenient for discover patient's joint or the problem that exists and correct in time.
The virtual environment module comprises a support 8, the support 8 is positioned right in front of the running machine, a display screen 11 is arranged at the top of the support, and the display screen 11 can display virtual environment information or the action of rehabilitation training, so that a patient can conveniently follow the exercise.
The camera module comprises a first camera 10 fixedly mounted on the support 8, the first camera 10 facing the treadmill, i.e. facing the patient, for taking gait video of the patient from the front. And also comprises a second camera 15 mounted on the rear vertical frame 3 and a third camera mounted on the front vertical frame 7. The second camera 15 and the third camera are installed in a central symmetry mode. Namely, the second camera 15 photographs the patient from the rear left, and the third camera photographs the patient from the front right; or the second camera 15 shoots the patient from the left front, the third camera shoots the patient from the right rear, and the three groups of cameras shoot from different angles, so that gait information of different angles of the patient is acquired, and the analysis is more accurate.
The support 8 in this embodiment may be fixedly mounted on the running machine 1 or may be separate. The first camera 10 in this embodiment is mounted on the first cross member 9 of the bracket 8 and is located below the display screen 11.
When the active rehabilitation mode is selected, the patient does not need to wear the brain-computer interface module, and the rehabilitation robot automatically follows the leg movements of the patient. The patient can follow the action on the display screen and also can walk by oneself, and when the patient walks, the camera module can catch patient's shank action, and analysis host computer analysis gait judges stride frequency automatically regulated treadmill's functioning speed.
When the passive rehabilitation mode is selected, the patient needs to wear the brain-computer interface module. The brain-computer interface module acquires relevant brain-computer signals according to prompts of the display screen, sends the relevant brain-computer signals to the analysis host, the analysis host judges the action corresponding to the signals through analysis of the brain-computer signals, then converts the action into a computer action command, then sends the action command to the rehabilitation robot, and the rehabilitation robot drives the lower limbs of the patient to complete the action. The camera captures the action of the lower limbs of the patient and sends the action to the analysis host computer, and the running speed of the running machine is automatically adjusted by judging the stride frequency.
In the rehabilitation process, the camera captures the leg movements of a patient, the acceleration sensor is used for detecting the movement conditions of all parts of the patient when the legs move, the sole pressure sensor is used for sensing the pressure changes of all parts of the sole when the legs move, the tension sensor is used for sensing the movement of the shoulders of the patient when the patient moves, the analysis host analyzes the change of the center of gravity of the sole, the change of the center of gravity of the human body, the gait and the like according to the data, and gives an analysis report.
Claims (8)
1. A brain-computer interface technology is to analysis, control system of human gait under the virtual environment, characterized by that: the device comprises a brain-computer interface module, a rehabilitation robot module, a sensor module, a camera module, a virtual environment module and a servo control module which are all electrically connected with an analysis host, wherein the servo control module is electrically connected with a treadmill module; the brain-computer interface module is worn on the head of the patient and used for acquiring brain-computer signals of the patient; the rehabilitation robot module is worn on the lower limb of the patient and is used for receiving an action instruction sent by the analysis host according to the brain electrical signal of the patient and driving the lower limb of the patient to move or moving along the limb of the patient according to the instruction sent by the analysis host; the camera module is used for shooting the gait of the patient from a plurality of angles and transmitting the gait back to the analysis host, the virtual environment module is used for providing a virtual environment for the patient, and the servo control module is used for receiving the instruction of the analysis host and controlling the running machine to run; the sensor module is used for monitoring foot sole pressure, shoulder tension and acceleration data of legs of a patient in the rehabilitation process and sending the foot sole pressure, shoulder tension and acceleration data to the analysis host; the analysis host analyzes the information of the brain-computer interface module, the sensor module and the camera module, controls the rehabilitation robot module and the running machine module to operate according to analysis results, generates an analysis report, and is also used for controlling the virtual environment module to display virtual environment information.
2. The brain-computer interface technology according to claim 1, wherein the human gait analysis and control system in the virtual environment is characterized in that: the running machine module comprises a running machine (1) provided with a rear vertical frame (3) and a front vertical frame (7), two second cross beams (12) are arranged between the rear vertical frame (3) and the front vertical frame (7), a tension sensor is fixedly arranged on each second cross beam (12), and the tension sensor is connected with a waistcoat (14) through a pull rope (13).
3. The brain-computer interface technology according to claim 1, wherein the human gait analysis and control system in the virtual environment is characterized in that: the rehabilitation robot module consists of a hip joint exoskeleton (6), a thigh exoskeleton (5), a shank exoskeleton, an ankle joint exoskeleton and a sole exoskeleton (4), wherein acceleration sensors are arranged on the thigh exoskeleton (5), the shank exoskeleton and the ankle joint exoskeleton, and sole pressure sensors are arranged on the sole exoskeleton (4).
4. The brain-computer interface technology according to claim 2, wherein the human gait analysis and control system in the virtual environment is characterized in that: the camera module comprises a first camera (10) fixedly installed on the support (8), and the first camera (10) is opposite to the running machine.
5. The brain-computer interface technology according to claim 4, wherein the human gait analysis and control system in the virtual environment is characterized in that: the camera module comprises a second camera (15) arranged on the rear vertical frame (3) and a third camera arranged on the front vertical frame (7).
6. The brain-computer interface technology according to claim 5, wherein the human gait analysis and control system in the virtual environment is characterized in that: the second camera (15) and the third camera are installed in a central symmetry mode.
7. The brain-computer interface technology according to any one of claims 1 to 6, wherein the human gait analysis and control system in the virtual environment is characterized in that: the analysis host computer comprises a display, a mouse, a keyboard and a printer which are electrically connected with the workstation.
8. The brain-computer interface technology according to any one of claims 1 to 6, wherein the human gait analysis and control system in the virtual environment is characterized in that: the analysis host computer is also used for carrying out mode selection, wherein the mode selection comprises an active rehabilitation mode and a passive rehabilitation mode.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211005870.9A CN117672452A (en) | 2022-08-22 | 2022-08-22 | Analysis and control system for human gait by brain-computer interface technology in virtual environment |
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| CN202211005870.9A CN117672452A (en) | 2022-08-22 | 2022-08-22 | Analysis and control system for human gait by brain-computer interface technology in virtual environment |
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109199786A (en) * | 2018-07-26 | 2019-01-15 | 北京机械设备研究所 | A kind of lower limb rehabilitation robot based on two-way neural interface |
| CN114366556A (en) * | 2021-12-31 | 2022-04-19 | 华南理工大学 | Multi-mode training control system and method for lower limb rehabilitation |
| WO2024011958A1 (en) * | 2022-07-14 | 2024-01-18 | 香港理工大学 | Control method, device, and system for rehabilitation training |
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- 2022-08-22 CN CN202211005870.9A patent/CN117672452A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109199786A (en) * | 2018-07-26 | 2019-01-15 | 北京机械设备研究所 | A kind of lower limb rehabilitation robot based on two-way neural interface |
| CN114366556A (en) * | 2021-12-31 | 2022-04-19 | 华南理工大学 | Multi-mode training control system and method for lower limb rehabilitation |
| WO2024011958A1 (en) * | 2022-07-14 | 2024-01-18 | 香港理工大学 | Control method, device, and system for rehabilitation training |
Non-Patent Citations (2)
| Title |
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| 岳海波;: "步态康复训练机器人研究现状与趋势", 科技展望, no. 19, 10 July 2017 (2017-07-10) * |
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