CN113925738A - Hand finger nerve rehabilitation training method and device - Google Patents

Hand finger nerve rehabilitation training method and device Download PDF

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CN113925738A
CN113925738A CN202111010989.0A CN202111010989A CN113925738A CN 113925738 A CN113925738 A CN 113925738A CN 202111010989 A CN202111010989 A CN 202111010989A CN 113925738 A CN113925738 A CN 113925738A
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chair
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hand
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邵明
刘静
谭红愉
李远清
颜智
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Affiliated Brain Hospital of Guangzhou Medical University
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    • 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
    • A61H1/00—Apparatus for passive exercising; Vibrating apparatus; Chiropractic devices, e.g. body impacting devices, external devices for briefly extending or aligning unbroken bones
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Abstract

The invention belongs to the technical field of medical instruments and discloses a hand finger nerve rehabilitation training method and a device. The microprocessor unit is connected with a PID motion controller of the training chair through a transmission line, the training chair is provided with four movable wheels, and each movable wheel is provided with a wheel lock. The training chair is provided with a placing box, and a cylindrical part, a square part and a circular part are placed in the placing box. The device solves the problem of poor stability of the existing device by arranging 4 fixed wheel locks, has the advantage of good stability, and realizes the movement of the training chair by applying cranial nerve conduction and PID technology.

Description

Hand finger nerve rehabilitation training method and device
Technical Field
The invention belongs to the technical field of medical instruments, and particularly relates to a hand finger nerve rehabilitation training method and device.
Background
At present, the medical apparatus refers to instruments, equipment, appliances, in-vitro diagnostic reagents and calibrators, materials and other similar or related articles directly or indirectly applied to human body, including required computer software, the utility is mainly obtained by physical means and the like, not by pharmacological, immunological or metabolic means, or is only assisted by the means, so as to diagnose, prevent, monitor, treat or relieve diseases; diagnosis, monitoring, treatment, mitigation, or functional compensation of injury; examination, replacement, regulation or support of a physiological structure or physiological process; support or maintenance of life; controlling pregnancy; by examining a sample from a human body, information is provided for medical or diagnostic purposes.
Present hand finger rehabilitation training device does not mostly consider the special situation who uses the disease, most direct placement is subaerial, there is not fixed part, and can not remove, the condition that the disease can not freely walk about has been ignored, and present device perfection is not high, do not come perfect device with the help of other recovery parts, can not guarantee the training, and present device is manual operation mostly, need the personnel of hospital to accompany, if the condition that hospital personnel staff is not enough appears, can delay the rehabilitation training of disease, and the rehabilitation training that does not have medical personnel's accompany the lower patient not only the security can not be ensured, and training efficiency, the standardization of training action all can very big decline, the practicality of hand finger rehabilitation training device has been reduced.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) the existing device has poor stability and low integrity, is not considered thoroughly, and cannot ensure the safety in the use process and the training recovery effectiveness.
(2) The existing training device needs medical care personnel to accompany, if special conditions occur, patients cannot repair and train themselves, even if the existing training device can not ensure safety, training efficiency and the standard of training actions are greatly reduced.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a hand finger nerve rehabilitation training method and device.
The invention is realized in this way, a hand finger nerve rehabilitation training method, which comprises:
the EOG signal sensor unit acquires brain signal information of a patient, and a plurality of sensing points are arranged on five fingers of the sensing training glove to acquire the real-time state of the fingers of the hand of the patient;
the microprocessor unit transmits data to a PID motion controller of the training chair, the PID motion controller controls the training chair to move, and wheel locks arranged on four movable wheels on the training chair are used for protecting the safety of a patient;
a patient sits on the training chair, the head of the patient wears an electrode cap, the hands of the patient wear sensing training gloves, the sensing training gloves begin to perform hand and finger training on the patient according to the internal set training action, and sensing points on the sensing training gloves are responsible for collecting neurons of the fingers of the hands and monitoring the neurons of the fingers in real time;
when the sensing training gloves drive patients to conduct hand and finger training, the pull ropes on the outer sides of different finger sleeves are driven to wind through the miniature speed reducing motors at the tail ends of the sensing training gloves respectively, so that bending actions of different fingers are driven, the finger sleeves can be driven to reset and straighten through the springs between joint fixing plates of the finger sleeves through the reverse rotation of the miniature speed reducing motors, and the next bending training is prepared to be conducted repeatedly;
when the patient needs to move to train the next step, the EOG signal sensor unit on the electrode cap collects brain signals of the patient, transmits the brain signals to the microprocessor unit for analysis, and combines an online camera on the inner wall of a room to realize the movement of the training chair for the next training;
when the training chair moves, the patient thinks of the destination, and the electroencephalogram signals are analyzed after reaching the microprocessor unit to obtain three-dimensional coordinates of the destination;
meanwhile, an online camera is called to obtain the picture information of the current patient position, and the acquired image is used for positioning the obstacles around the patient by adopting an image processing method;
generating candidate destinations and path planning tracks according to information of the obstacles, performing path planning by adopting an A-algorithm to generate a shortest optimal path, calculating the position difference between the current position of the training chair and the optimal path of the destinations by a microprocessor unit, taking the position difference as the feedback of a PID path tracking algorithm, and calculating the reference angular velocity and linear velocity by the PID path tracking algorithm;
inputting the reference angular velocity and the linear velocity into a PID motion controller in the training chair, adjusting a control signal of the training chair, and controlling the training chair to travel to a destination in real time;
in the PID path tracking process, the motion process of the training chair is established as follows:
Figure BDA0003238484020000031
wherein, (X, y) is the position of the actual environment of the training chair, v is the speed of the training chair, theta is the included angle between the advancing direction of the training chair and the X axis of the coordinate, and the differential form of the position error of the training chair obtained according to the positions (X, y, theta) and (v, omega) of the training chair is as follows:
Figure BDA0003238484020000032
further obtaining:
Figure BDA0003238484020000033
Figure BDA0003238484020000041
the control law is as follows:
Figure BDA0003238484020000042
wherein c is1，c2Are all constants;
substituting the control law equation into the equation to obtain:
Figure BDA0003238484020000043
the reference angular velocity and the linear velocity are input into a PID motion controller in the training chair, and the PID motion control model is as follows:
inputting a preset angular velocity omega and a linear velocity v, calculating a preset deviation and an actual deviation according to a feedback result, and converting the deviation into a coordinate system of the training chair;
continuously adjusting corresponding coordinates through a preset angular velocity omega and a preset linear velocity v, wherein the deviation of a coordinate system is as follows:
Figure BDA0003238484020000044
in the formula (x)d，yd，θd) To preset coordinates, (x)r，yr，θr) As actual coordinates, (x)d-xr，yd-yr，θd-θr) For coordinate deviations, the final path is solved for the appropriate (v, ω) satisfies:
limt→∞Xe＝limt→∞Ye＝limt→∞θe＝0。
further, the method comprises the steps of calling an online camera to obtain picture information of the current patient position, and positioning the acquired image on barriers around the patient by adopting an image processing method, wherein the specific process comprises the following steps:
using an online camera to acquire picture information of the current patient position, and performing cutting, gray level and filtering processing;
after the picture information is processed, determining the projection of the template and determining the projection of the subgraph in the picture;
and determining the relation between the template and the projection in the subgraph by an FFT method, determining a corresponding function, and finding out the coordinate point with the maximum correlation.
Further, the determining the projection of the subgraph in the picture specifically comprises the following steps:
determining a pixel point (i, j) in a picture, regarding the pixel point as a starting point, performing accumulated projection on the pixel by using the column data with the length of M, and performing projection model in a new matrix of the position (i, j) corresponding to the pixel as follows:
Figure BDA0003238484020000051
further, the gray processing process of the acquired picture information of the current patient position is as follows:
converting an image on a picture of the current patient position into a gray image;
after the gray level image conversion is completed, determining the arithmetic mean value of the gray level image;
and performing binarization processing on the gray level image by taking the arithmetic average value as a threshold value.
Further, the specific process of filtering the acquired picture information of the current patient position is as follows:
determining the gray value of each pixel point of the image with the gray processing completed;
and (4) sequencing the gray levels, and selecting a gray level intermediate value to replace the data to be processed.
Another object of the present invention is to provide a hand and finger nerve rehabilitation training device for implementing the hand and finger nerve rehabilitation training method, the hand and finger nerve rehabilitation training device including:
an electrode cap;
EOG signal sensor units are arranged above and on the left side and the right side of the electrode cap, the electrode cap is connected with the microprocessor unit through a transmission line, the microprocessor unit is connected with the sensing training glove through the transmission line, and a plurality of sensing points are arranged on the five fingers of the sensing training glove;
joint fixing plates are arranged at joint connecting positions outside five finger sleeves of the sensing training glove, a through hole is formed in the middle of each joint fixing plate, a pull rope penetrates through each through hole, the upper end of each pull rope is fixedly connected with the joint fixing plate located at the uppermost end of each finger sleeve, a spring is sleeved on the outer side of each pull rope between every two adjacent joint fixing plates, and the lower end of each pull rope is wound on the outer side of an output shaft of the corresponding miniature speed reducing motor;
five miniature gear motors are arranged and are respectively fixed on the inner side of the lower end of the sensing training glove.
Furthermore, the microprocessor unit is connected with a PID motion controller of the training chair through a transmission line, the training chair is provided with four movable wheels, and each movable wheel is provided with a wheel lock.
Further, be provided with on the training chair and place the case, place incasement portion and placed cylindrical part, square part, ring shape part.
Further, a roller shaft is arranged in the middle of the joint fixing plate through a rotating shaft, and the outer side of the roller shaft is in contact with the pull rope.
By combining all the technical schemes, the invention has the advantages and positive effects that: the device solves the problem of poor stability of the existing device by arranging 4 fixed wheel locks, has the advantage of good stability, realizes the movement of the training chair by applying cranial nerve conduction and PID technology, increases some parts, ensures the effect of the whole recovery training, breaks away from the dependence on workers, helps patients to train by using the sensing gloves and the training chair in the whole course, ensures the efficiency and the standard of action, is convenient for users, and improves the practicability and the safety of the hand finger nerve recovery training device.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a hand finger nerve rehabilitation training device according to an embodiment of the present invention.
In the figure: 1. an electrode cap; 2. an EOG signal sensor unit; 3. a transmission wire; 4. a microprocessor unit; 5. sensing a training glove; 6. a sensing point; 7. a training chair; 8. a PID motion controller; 9. a movable wheel; 10. wheel lock training chair.
FIG. 2 is a schematic structural diagram of a recovery training component according to an embodiment of the present invention.
In the figure: 11. a cylindrical part; 12. a cube part; 13. a circular ring shaped part.
FIG. 3 is a schematic structural diagram of a sensory training glove according to an embodiment of the present invention.
In the figure: 14. finger cots; 15. a joint fixing plate; 16. pulling a rope; 17. a spring; 18. a miniature speed reduction motor; 19. and (4) a roll shaft.
Fig. 4 is a schematic diagram of the movement principle of the training chair provided by the embodiment of the invention.
Fig. 5 is a flowchart of a method for positioning obstacles around a patient by using an image processing method for an acquired image according to an embodiment of the present invention.
Fig. 6 is a flowchart of a method for performing gray processing on acquired image information of a current patient position according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a hand finger nerve rehabilitation training method and a device thereof, and the invention is described in detail with reference to the accompanying drawings.
As shown in fig. 1, the finger nerve rehabilitation training device provided by the embodiment of the present invention includes: the device comprises an electrode cap 1, an EOG signal sensor unit 2, a transmission wire 3, a microprocessor unit 4, a sensing training glove 5, a sensing point 6, a training chair 7, a PID motion controller 8, a movable wheel 9, a wheel lock training chair 10, a cylindrical part 11, a cube part 12 and a circular part 13.
EOG signal sensor units 2 are arranged above and on the left side and the right side of the electrode cap 1, the electrode cap 1 is connected with a microprocessor unit 2 through a transmission line 3, the microprocessor unit 2 is connected with a sensing training glove 5 through the transmission line 3, and a plurality of sensing points 6 are arranged on five fingers of the sensing training glove 5; the microprocessor unit 2 is connected with a PID motion controller 8 of a training chair 7 through a transmission line 3, the training chair 7 is provided with four movable wheels 9, and each movable wheel is provided with a wheel lock 10. Meanwhile, the training chair 7 is provided with a placing box, and a cylindrical part 11, a square part 12 and a circular part 13 are placed in the placing box.
The EOG signal sensor unit 2 collects brain signal information of a patient, a plurality of sensing points 6 are arranged on five fingers of a sensing training glove 5 to obtain the real-time state of the fingers of the patient, the microprocessor unit 2 transmits data to a PID motion controller 8 of a training chair 7, the PID motion controller 8 controls the training chair 7 to move, and wheel locks 10 arranged on four movable wheels 9 on the training chair 7 ensure the safety of the patient; the patient sits on the training chair 7, the electrode cap 1 is worn on the head, the sensing training gloves 5 are worn on the hands by workers, the sensing training gloves 5 begin to conduct hand finger training on the patient according to the internal set training action, the sensing points 6 on the sensing training gloves 5 are responsible for collecting neurons of the hand fingers, and real-time monitoring is conducted on the finger neurons. When sensing training gloves drive the disease and carry out the hand finger training, drive the stay cord in the different finger stall outsides respectively through the terminal a plurality of miniature gear motor of sensing training gloves and twine to the crooked action that the realization drove different fingers, through miniature gear motor's reversal, the spring between the joint fixed plate through the finger stall can drive the finger stall and reset and straighten, prepares the repeated crooked training that carries on next. When the patient needs to move to train for the next step, the EOG signal sensor unit 2 on the electrode cap 1 collects brain signals of the patient, transmits the brain signals to the microprocessor unit 2 for analysis, and combines an online camera on the inner wall of a room to realize the movement of the training chair 7 to train for the next step.
As shown in fig. 2, the recovery training part comprises a cylindrical part 11, a cube part 12 and a circular ring part 13, three parts with different sizes and shapes are used, so that the hand nerves are trained in an all-around manner, the hand nerves can be promoted to form memory points, and taking is controlled, so that the hand nerves of patients can be recovered more quickly.
As shown in fig. 3, joint fixing plates 15 are arranged at joint connecting positions outside five finger stalls of the sensing training glove, a through hole is formed in the middle of each joint fixing plate 15, a pull rope 16 penetrates through each through hole, the upper end of each pull rope 16 is fixedly connected with the joint fixing plate 15 located at the uppermost end of each finger stall 14, a spring 17 is sleeved outside each pull rope between every two adjacent joint fixing plates 15, and the lower end of each pull rope 16 is wound outside an output shaft of the corresponding miniature speed reduction motor 18; five miniature speed reducing motors 18 are arranged, and the five miniature speed reducing motors 18 are respectively fixed on the inner side of the lower end of the sensing training glove 5. The joint fixing plate 15 is provided with a roller shaft 19 through a rotating shaft, and the outer side of the roller shaft 19 is in contact with the pull rope 16.
As shown in fig. 4, when the training chair 7 moves, the patient thinks of the destination, the electroencephalogram signal is analyzed after reaching the microprocessor unit 2 to obtain the three-dimensional coordinates of the destination, and meanwhile, the online camera is called to obtain the picture information of the current position of the patient, and the acquired image is used for positioning the obstacles around the patient by adopting an image processing method. Generating candidate destinations and path planning tracks according to the information of the obstacles, performing path planning by adopting an A-algorithm to generate a shortest optimal path, calculating the position difference between the current position of the training chair 7 and the optimal path of the destination by the microprocessor unit 2, taking the position difference as the feedback of a PID path tracking algorithm, and calculating the angular velocity and linear velocity of reference by the PID path tracking algorithm. And inputting the reference angular velocity and the linear velocity into a PID motion controller 8 in the training chair, so as to adjust the control signal of the training chair 7 and control the training chair 7 to travel to the destination in real time.
In the PID path tracking process provided by the embodiment of the invention, the motion process of establishing the training chair is as follows:
Figure BDA0003238484020000091
wherein, (X, y) is the position of the actual environment of the training chair, v is the speed of the training chair, theta is the included angle between the advancing direction of the training chair and the X axis of the coordinate, and the differential form of the position error of the training chair obtained according to the positions (X, y, theta) and (v, omega) of the training chair is as follows:
Figure BDA0003238484020000092
further obtaining:
Figure BDA0003238484020000101
the control law is as follows:
Figure BDA0003238484020000102
wherein c is1，c2Are all constants;
substituting the control law equation into the equation to obtain:
Figure BDA0003238484020000103
the reference angular velocity and the linear velocity provided by the embodiment of the invention are input into a PID motion controller 8 in the training chair, and the PID motion control model is as follows:
inputting a preset angular velocity omega and a linear velocity v, calculating a preset deviation and an actual deviation according to a feedback result, and converting the deviation into a coordinate system of the training chair;
continuously adjusting corresponding coordinates through a preset angular velocity omega and a preset linear velocity v, wherein the deviation of a coordinate system is as follows:
Figure BDA0003238484020000111
in the formula (x)d，yd，θd) To preset coordinates, (x)r，yr，θr) As actual coordinates, (x)d-xr，yd-yr，θd-θr) For coordinate deviations, the final path is solved for the appropriate (v, ω) satisfies:
limt→∞Xe＝limt→∞Ye＝limt→∞θe＝0。
the device overcomes the defects of poor stability, low integrity and careless consideration of the existing device, and ensures the safety in the use process and the training recovery effect. Meanwhile, the problem that the existing training device needs medical care personnel to accompany and additionally recover training is solved, the patient personnel who cannot walk can train by moving the training chair, the safety is guaranteed, the training efficiency is improved, and the standard of the training action is greatly improved.
As shown in fig. 5, in the embodiment of the present invention, an internet camera is invoked to obtain picture information of a current patient position, and an image processing method is adopted to position an obstacle around a patient on an acquired image, where the specific process is as follows:
s101: using an online camera to acquire picture information of the current patient position, and performing cutting, gray level and filtering processing;
s102: after the picture information is processed, determining the projection of the template and determining the projection of the subgraph in the picture;
s103: and determining the relation between the template and the projection in the subgraph by an FFT method, determining a corresponding function, and finding out the coordinate point with the maximum correlation.
In the embodiment of the invention, the projection of the subgraph in the picture is determined, and the specific process is as follows:
determining a pixel point (i, j) in the picture, regarding the pixel point as a starting point, performing accumulated projection on the pixel by using the column data with the length of M, and performing projection model on a position (i, j in a new matrix of the pixel) corresponding to the pixel as follows:
Figure BDA0003238484020000121
as shown in fig. 6, in the embodiment of the present invention, the gray processing process of the acquired picture information of the current patient position includes:
s201: converting an image on a picture of the current patient position into a gray image;
s202: after the gray level image conversion is completed, determining the arithmetic mean value of the gray level image;
s203: and performing binarization processing on the gray level image by taking the arithmetic average value as a threshold value.
The specific process of filtering the acquired picture information of the current patient position in the embodiment of the invention is as follows:
determining the gray value of each pixel point of the image with the gray processing completed;
and (4) sequencing the gray levels, and selecting a gray level intermediate value to replace the data to be processed.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.

Claims (10)

1. A hand and finger nerve rehabilitation training method is characterized by comprising the following steps:
the EOG signal sensor unit acquires brain signal information of a patient, and a plurality of sensing points are arranged on five fingers of the sensing training glove to acquire the real-time state of the fingers of the hand of the patient;
the microprocessor unit transmits data to a PID motion controller of the training chair, the PID motion controller controls the training chair to move, and wheel locks arranged on four movable wheels on the training chair are used for protecting the safety of a patient;
a patient sits on the training chair, the head of the patient wears an electrode cap, the hands of the patient wear sensing training gloves, the sensing training gloves begin to perform hand and finger training on the patient according to the internal set training action, and sensing points on the sensing training gloves are responsible for collecting neurons of the fingers of the hands and monitoring the neurons of the fingers in real time;
when the sensing training gloves drive patients to conduct hand and finger training, the pull ropes on the outer sides of different finger sleeves are driven to wind through the miniature speed reducing motors at the tail ends of the sensing training gloves respectively, so that bending actions of different fingers are driven, the finger sleeves can be driven to reset and straighten through the springs between joint fixing plates of the finger sleeves through the reverse rotation of the miniature speed reducing motors, and the next bending training is prepared to be conducted repeatedly;
when the patient needs to move to train the next step, the EOG signal sensor unit on the electrode cap collects brain signals of the patient, transmits the brain signals to the microprocessor unit for analysis, and combines an online camera on the inner wall of a room to realize the movement of the training chair for the next training;
when the training chair moves, the patient thinks of the destination, and the electroencephalogram signals are analyzed after reaching the microprocessor unit to obtain three-dimensional coordinates of the destination; and inputting the reference angular velocity and the linear velocity into a PID motion controller in the training chair, adjusting a control signal of the training chair, and controlling the training chair to travel to a destination in real time.
2. The method for rehabilitation training of the nerves of the fingers of the hand as claimed in claim 1, wherein when the training chair moves, the online camera is simultaneously called to obtain the picture information of the current position of the patient, and the acquired image is processed by an image processing method to realize the positioning of the obstacles around the patient;
generating candidate destinations and path planning tracks according to information of the obstacles, performing path planning by adopting an A-algorithm to generate a shortest optimal path, calculating the position difference between the current position of the training chair and the optimal path of the destinations by a microprocessor unit, taking the position difference as the feedback of a PID path tracking algorithm, and calculating the reference angular velocity and linear velocity by the PID path tracking algorithm;
in the PID path tracking process, the motion process of the training chair is established as follows:
Figure FDA0003238484010000021
wherein, (X, y) is the position of the actual environment of the training chair, v is the speed of the training chair, theta is the included angle between the advancing direction of the training chair and the X axis of the coordinate, and the differential form of the position error of the training chair obtained according to the positions (X, y, theta) and (v, omega) of the training chair is as follows:
Figure FDA0003238484010000022
further obtaining:
Figure FDA0003238484010000023
the control law is as follows:
Figure FDA0003238484010000031
wherein c is1，c2Are all constants;
substituting the control law equation into the equation to obtain:
Figure FDA0003238484010000032
the reference angular velocity and the linear velocity are input into a PID motion controller in the training chair, and the PID motion control model is as follows:
inputting a preset angular velocity omega and a linear velocity v, calculating a preset deviation and an actual deviation according to a feedback result, and converting the deviation into a coordinate system of the training chair;
continuously adjusting corresponding coordinates through a preset angular velocity omega and a preset linear velocity v, wherein the deviation of a coordinate system is as follows:
Figure FDA0003238484010000033
in the formula (x)d，yd，θd) To preset coordinates, (x)r，yr，θr) As actual coordinates, (x)d-xr，yd-yr，θd-θr) For coordinate deviations, the final path is solved for the appropriate (v, ω) satisfies:
limt→∞Xe＝limt→∞Ye＝limt→∞θe＝0。
3. the method for rehabilitation training of the nerves of the fingers of the hand as claimed in claim 2, wherein the step of calling the web camera to acquire the picture information of the current position of the patient and the step of positioning the obstacles around the patient by using the acquired image processing method comprises the following specific steps:
using an online camera to acquire picture information of the current patient position, and performing cutting, gray level and filtering processing;
after the picture information is processed, determining the projection of the template and determining the projection of the subgraph in the picture;
and determining the relation between the template and the projection in the subgraph by an FFT method, determining a corresponding function, and finding out the coordinate point with the maximum correlation.
4. The method for rehabilitation training of the nerves of the fingers of the hand as claimed in claim 3, wherein the projection of the subgraph in the picture is determined by the following specific process:
determining a pixel point (i, j) in a picture, regarding the pixel point as a starting point, performing accumulated projection on the pixel by using the column data with the length of M, and performing projection model in a new matrix of the position (i, j) corresponding to the pixel as follows:
Figure FDA0003238484010000041
5. the rehabilitation training method for the nerves of the fingers of the hand as claimed in claim 3, wherein the gray processing process of the acquired image information of the current patient position is as follows:
converting an image on a picture of the current patient position into a gray image;
after the gray level image conversion is completed, determining the arithmetic mean value of the gray level image;
and performing binarization processing on the gray level image by taking the arithmetic average value as a threshold value.
6. The method for rehabilitation training of the nerves of the fingers according to claim 3, wherein the specific process of filtering the acquired image information of the current patient position is as follows:
determining the gray value of each pixel point of the image with the gray processing completed;
and (4) sequencing the gray levels, and selecting a gray level intermediate value to replace the data to be processed.
7. A hand and finger nerve rehabilitation training device for implementing the hand and finger nerve rehabilitation training method according to any one of claims 1 to 6, wherein the hand and finger nerve rehabilitation training device is provided with:
an electrode cap;
EOG signal sensor units are arranged above and on the left side and the right side of the electrode cap, the electrode cap is connected with the microprocessor unit through a transmission line, the microprocessor unit is connected with the sensing training glove through the transmission line, and a plurality of sensing points are arranged on the five fingers of the sensing training glove;
joint fixing plates are arranged at joint connecting positions outside five finger sleeves of the sensing training glove, a through hole is formed in the middle of each joint fixing plate, a pull rope penetrates through each through hole, the upper end of each pull rope is fixedly connected with the joint fixing plate located at the uppermost end of each finger sleeve, a spring is sleeved on the outer side of each pull rope between every two adjacent joint fixing plates, and the lower end of each pull rope is wound on the outer side of an output shaft of the corresponding miniature speed reducing motor;
five miniature gear motors are arranged and are respectively fixed on the inner side of the lower end of the sensing training glove.
8. The hand finger nerve rehabilitation training device of claim 7, wherein the microprocessor unit is connected to the PID motion controller of the training chair via a transmission line, the training chair has four movable wheels, and each movable wheel is provided with a wheel lock.
9. The hand finger nerve rehabilitation training device of claim 7, wherein the training chair is provided with a placing box, and a cylindrical part, a square part and a circular part are placed inside the placing box.
10. The hand finger nerve rehabilitation training device of claim 7, wherein a roller is arranged in the middle of the joint fixing plate through a rotating shaft, and the outer side of the roller is in contact with the pull rope.
CN202111010989.0A 2021-08-31 2021-08-31 Hand finger nerve rehabilitation training method and device Pending CN113925738A (en)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6454681B1 (en) * 1998-01-05 2002-09-24 Thomas Brassil Hand rehabilitation glove
JP2011036494A (en) * 2009-08-13 2011-02-24 Ryozaburo Namikawa Rehabilitation aid
US20120029399A1 (en) * 2009-04-09 2012-02-02 Yoshiyuki Sankai Wearable type movement assisting apparatus
CN202355552U (en) * 2011-11-03 2012-08-01 黑龙江省小儿脑性瘫痪防治疗育中心 Walk exercising rehabilitation device for cerebral palsy patients
CN104083258A (en) * 2014-06-17 2014-10-08 华南理工大学 Intelligent wheel chair control method based on brain-computer interface and automatic driving technology

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6454681B1 (en) * 1998-01-05 2002-09-24 Thomas Brassil Hand rehabilitation glove
US20120029399A1 (en) * 2009-04-09 2012-02-02 Yoshiyuki Sankai Wearable type movement assisting apparatus
JP2011036494A (en) * 2009-08-13 2011-02-24 Ryozaburo Namikawa Rehabilitation aid
CN202355552U (en) * 2011-11-03 2012-08-01 黑龙江省小儿脑性瘫痪防治疗育中心 Walk exercising rehabilitation device for cerebral palsy patients
CN104083258A (en) * 2014-06-17 2014-10-08 华南理工大学 Intelligent wheel chair control method based on brain-computer interface and automatic driving technology

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