CN113633384A - A systematic approach to autonomous medical robots that can perform multiple types of operations - Google Patents
A systematic approach to autonomous medical robots that can perform multiple types of operations Download PDFInfo
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- CN113633384A CN113633384A CN202110861540.9A CN202110861540A CN113633384A CN 113633384 A CN113633384 A CN 113633384A CN 202110861540 A CN202110861540 A CN 202110861540A CN 113633384 A CN113633384 A CN 113633384A
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- 230000009897 systematic effect Effects 0.000 title claims abstract description 10
- 238000000034 method Methods 0.000 claims abstract description 102
- 230000003902 lesion Effects 0.000 claims description 21
- 238000010801 machine learning Methods 0.000 claims description 21
- 230000036285 pathological change Effects 0.000 claims description 20
- 231100000915 pathological change Toxicity 0.000 claims description 20
- 239000003550 marker Substances 0.000 claims description 19
- 238000002059 diagnostic imaging Methods 0.000 claims description 13
- 238000002591 computed tomography Methods 0.000 claims description 6
- 238000005481 NMR spectroscopy Methods 0.000 claims description 4
- 230000006870 function Effects 0.000 claims description 3
- 201000010099 disease Diseases 0.000 claims description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 2
- 238000001356 surgical procedure Methods 0.000 claims 3
- 238000003384 imaging method Methods 0.000 claims 1
- 238000000926 separation method Methods 0.000 abstract description 2
- 238000012216 screening Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/30—Surgical robots
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/10—Computer-aided planning, simulation or modelling of surgical operations
- A61B2034/101—Computer-aided simulation of surgical operations
- A61B2034/102—Modelling of surgical devices, implants or prosthesis
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Abstract
The invention discloses a systematic method of autonomous medical robots capable of executing various operations. The invention can realize the combination and the separation between various surgical tools and the movable operating arm according to the requirements and realize the automation of various surgical processes.
Description
Technical Field
The invention relates to an autonomous medical robot systematization method capable of executing various operations, belonging to the technical field of robots.
Background
Medical robotic systems are a class of electromechanical systems used in medical procedures. Current surgical robotic systems are either structurally fixed or require manual replacement of surgical tools. For the former medical robot system with fixed structural form, the movable operation arm and the operation tool are not changeable under the normal state, and the function is single. For the latter surgical robot system which needs to replace the surgical tool by manpower, the following three problems exist in the working mode: the first problem is that the working process is complicated, manual intervention is needed, and the automation degree is low; secondly, moving operation arms with different structures are needed for operating different surgical tools, so that the cost is high; and thirdly, the operation is performed manually, the operation precision is low, and human errors are inevitably caused. Therefore, the operation terminal and the motion platform for operating the operation terminal need to be combined according to the operation requirement of the operation process, so that the automation of the operation process is realized, and errors caused by insufficient experience of operators or low operation precision are reduced.
Disclosure of Invention
The invention provides a database for collecting operation process data of doctors to patients and corresponding patient information for treatment to form a subsequent machine learning operation method, medical imaging is carried out on the position of the lesion area of the current patient, a machine learning method is adopted to diagnose the medical imaging result to determine the type of the lesion of the current patient, all the operation process data of the doctors corresponding to the type of the lesion are screened out from the database according to the type of the lesion of the current patient, the type and the number of operation tools used in each step in the operation process of the type are determined, the step with the largest number of operation tools is determined, the number of movable operation arms is equal to the number of the operation tools in the step, the needed operation tools are taken out from an operation tool total library and placed on an operation tool moving platform, all the operation process data of the doctors corresponding to the type of the lesion are screened out, and the operation process data of the doctors are analyzed by adopting the machine learning method to form the operation process data of the doctors The operation method of the surgical tool for determining the type of pathological changes is characterized in that the operation method of the surgical tool of the current patient is determined by combining the information of the current patient including medical images, the mobile operation arm and the surgical tool mobile platform are controlled to reach an operation preparation area, after the mobile operation arm and the surgical tool mobile platform reach the operation preparation area, the mobile operation arm is autonomously connected according to the operation method of the surgical tool of the current patient, the required surgical tool is replaced between the adjacent steps, and the autonomous medical robot system for performing the surgical operation by cooperation of a plurality of mobile operation arms.
In order to achieve the above purpose, the present invention provides a systematic method for autonomous medical robots capable of performing various operations, which comprises a surgical tool library, a surgical tool moving platform, a surgical bed, a plurality of moving operation arms, a positioning device fixed on the moving operation arms, and system software.
The surgical tool total library comprises a surgical tool universal connector surgical tool end, various surgical tools and markers for acquiring the position information of the various surgical tools by a positioning device.
The surgical tool moving platform comprises a moving vehicle capable of placing various surgical tools, a marker for acquiring the position information of the surgical tool moving platform by a positioning device, an automatic navigation system of the surgical tool moving platform and an automatic moving system of the surgical tool moving platform.
The operation table and be used for positioner to acquire the marker of operation table positional information.
The mobile operation arm comprises a mechanical arm, a positioning device fixed on the mobile operation arm, a surgical tool universal connector mobile operation arm end and a marker used for the positioning device to obtain the position information of the mobile operation arm.
The working process comprises
Collecting the operation process data of each doctor to the patient and the corresponding patient information for treatment to form a database of the subsequent machine learning operation method, wherein the information comprises all operation steps of all doctors in the operation process, and operation related information such as the posture, the motion track, the motion state, the patient information and the like of the operation tool in each step;
the method comprises the following steps of performing medical imaging on the part where the lesion area of the patient is located, firstly placing the patient on an operating table, and then automatically moving the operating table with an automatic navigation system and an automatic motion system to perform various examinations such as CT (computed tomography), nuclear magnetic resonance and the like on the patient without manual intervention;
after the examination is finished, diagnosing the medical imaging result by adopting a machine learning method so as to determine the type of the current lesion of the patient;
the system software screens out all the data of the doctor operation process corresponding to the lesion of the type in the database according to the lesion type of the current patient;
after the system software screens out the data of the operation process of the doctor with the pathological changes of the type, the type and the number of the operation tools used in each step in the operation process of the type are determined, the step with the largest number of the operation tools is determined, and the number of the movable operation arms is equal to the number of the operation tools in the step. Determining the type and the number of the needed surgical tools according to the surgical tools needed by the data of the whole surgical operation process in the database, then moving the operation arm to scan the markers in the surgical tool master library through the positioning device to obtain the position information of the surgical tools, and then moving the operation arm end through the surgical tool universal connector at the tail end of the operation arm end to connect the surgical tool universal connector surgical tool end of the needed surgical tools, thereby taking out the needed surgical tools from the surgical tool master library and placing the surgical tools on a surgical tool moving platform;
the system software screens out all doctor operation process data corresponding to the type of pathological changes, analyzes the doctor operation process data by adopting a machine learning method to determine the operation method of the operation tool of the type of pathological changes, and then determines the operation method of the operation tool aiming at the current patient by combining the information of the current patient including medical images;
after the operation method of the surgical tool for the current patient is determined, the system software controls the mobile operation arm and the surgical tool mobile platform to reach an operation preparation area, and the operation bed moves the patient to an operation area, so that the preparation work is completed;
after the preparation work is finished, firstly, the operation arm is moved to scan a marker on the operation tool moving platform through the positioning device to obtain the position information of an operation tool, then, the operation tool universal connector at the tail end of the operation arm is moved to connect the operation tool universal connector of the operation tool needed by the operation tool, after the operation tool is connected, the positioning device scans the marker on the operation table to obtain the position information of the operation area of the patient, then, the operation arm is moved to be independently connected according to the operation method of the operation tool of the current patient, the needed operation tool is replaced between the adjacent steps, and the operation is finished by the cooperation of the plurality of operation arms.
The invention has the advantages that:
(1) medical imaging and disease diagnosis can be automatically performed;
(2) the operation tool can be automatically replaced by moving the operation arm;
(3) various types of operations may be performed;
(4) can realize the automation of the operation.
Drawings
FIG. 1 is a flow chart of the operation of the present invention.
Detailed Description
For better understanding of the objects, technical means, operational procedures and the like of the present invention, the following detailed description of the embodiments of the present invention will be made with reference to the accompanying drawings. The following exemplary description, with reference to the drawings, is merely illustrative of the invention and is not to be construed as limiting the invention.
The invention provides a technical scheme that: the systematic method of autonomous medical robot capable of executing various operations includes operation tool library, operation tool moving platform, operation bed, several movable operation arms, positioning device fixed onto the movable operation arms and system software.
The surgical tool total library comprises a surgical tool universal connector surgical tool end, various surgical tools and markers for acquiring the position information of the various surgical tools by a positioning device.
The surgical tool moving platform comprises a moving vehicle capable of placing various surgical tools, a marker for acquiring the position information of the surgical tool moving platform by a positioning device, an automatic navigation system of the surgical tool moving platform and an automatic moving system of the surgical tool moving platform.
The operating table comprises a marker for acquiring the position information of the operating table by the positioning device.
The mobile operation arm comprises a mechanical arm, a positioning device fixed on the mobile operation arm, a surgical tool universal connector mobile operation arm end and a marker used for the positioning device to obtain the position information of the mobile operation arm.
The working process comprises collecting the operation process data of each doctor to the patient and the corresponding patient information for treatment to form a database of the subsequent machine learning operation method, performing medical imaging to the part of the current patient lesion area, diagnosing the medical imaging result by using the machine learning method to determine the type of the current patient lesion, screening out the operation process data of all the doctors corresponding to the type of lesion in the database according to the type of the current patient lesion, determining the type and the number of the operation tools used in each step in the operation process of the type, determining the step with the largest number of the operation tools, wherein the number of the movable operation arms is equal to the number of the operation tools in the step, taking out the required operation tools from the operation tool total library and placing the operation tools on an operation tool moving platform, screening out the operation process data of all the doctors corresponding to the type of lesion, and analyzing the operation process data of the doctors by using the machine learning method to determine the operation process data of the doctors The operation method of the surgical tool for determining the type of pathological changes is characterized in that the current operation method of the surgical tool for the patient is determined by combining the current patient information including medical images, the mobile operation arm and the surgical tool mobile platform are controlled to reach an operation preparation area, after the mobile operation arm and the surgical tool mobile platform reach the operation preparation area, the mobile operation arm is autonomously connected according to the operation method of the surgical tool for the current patient, the required surgical tool is replaced between the adjacent steps, and the operation is completed by the cooperation of a plurality of mobile operation arms. The invention can realize the combination and separation between the surgical tool and the movable operating arm according to the requirement and realize the automation of the surgical process.
The method comprises the following specific steps: the operation process data of each doctor to the patient and the corresponding patient information for treatment are collected to form a database of the subsequent machine learning operation method, and the information comprises all operation steps of all doctors in the operation process, posture, motion trail, motion state of the operation tool in each step, patient information and other operation related information. The medical imaging is carried out on the part where the pathological change area of the patient is located, the patient is placed on an operating table at first, then the operating table with an automatic navigation system and an automatic motion system automatically moves to carry out various examinations such as CT and nuclear magnetic resonance on the patient, and manual intervention is not needed. And after the examination is finished, diagnosing the medical imaging result by adopting a machine learning method so as to determine the type of the current lesion of the patient. The system software screens out all the doctor operation process data corresponding to the type of the pathological changes of the patient in the database according to the type of the pathological changes of the patient. After the system software screens out the data of the operation process of the doctor with the pathological changes of the type, the type and the number of the operation tools used in each step in the operation process of the type are determined, the step with the largest number of the operation tools is determined, and the number of the movable operation arms is equal to the number of the operation tools in the step. The type and the number of the needed surgical tools are determined according to the surgical tools needed by the data of the whole surgical operation process in the database, then the operation arm is moved to scan the markers in the surgical tool master library through the positioning device to obtain the position information of the surgical tools, and then the operation arm end is moved through the surgical tool universal connector at the tail end of the operation arm end to be connected with the surgical tool universal connector surgical tool end of the needed surgical tools, so that the needed surgical tools are taken out from the surgical tool master library and placed on the surgical tool moving platform. The system software screens out all doctor operation process data corresponding to the type of pathological changes, analyzes the doctor operation process data by adopting a machine learning method to determine the operation method of the surgical tool of the type of pathological changes, and then determines the operation method of the surgical tool aiming at the current patient by combining the information of the current patient including the medical image. After determining the operation method of the surgical tool for the current patient, the system software controls the mobile operation arm and the surgical tool mobile platform to reach an operation preparation area, and the operation bed moves the patient to an operation area, so that the preparation work is completed. After the preparation work is finished, firstly, the operation arm is moved to scan a marker on the operation tool moving platform through the positioning device to obtain the position information of an operation tool, then, the operation tool universal connector at the tail end of the operation arm is moved to connect the operation tool universal connector of the operation tool needed by the operation tool, after the operation tool is connected, the positioning device scans the marker on the operation table to obtain the position information of the operation area of the patient, then, the operation arm is moved to be independently connected according to the operation method of the operation tool of the current patient, the needed operation tool is replaced between the adjacent steps, and the operation is finished by the cooperation of the plurality of operation arms.
Working process
The operation process data of each doctor to the patient and the corresponding patient information for treatment are collected to form a database of the subsequent machine learning operation method, and the information comprises all operation steps of all doctors in the operation process, posture, motion trail, motion state of the operation tool in each step, patient information and other operation related information. The medical imaging is carried out on the part where the pathological change area of the patient is located, the patient is placed on an operating table at first, then the operating table with an automatic navigation system and an automatic motion system automatically moves to carry out various examinations such as CT and nuclear magnetic resonance on the patient, and manual intervention is not needed. And after the examination is finished, diagnosing the medical imaging result by adopting a machine learning method so as to determine the type of the current lesion of the patient. The system software screens out all the doctor operation process data corresponding to the type of the pathological changes of the patient in the database according to the type of the pathological changes of the patient. After the system software screens out the data of the operation process of the doctor with the pathological changes of the type, the type and the number of the operation tools used in each step in the operation process of the type are determined, the step with the largest number of the operation tools is determined, and the number of the movable operation arms is equal to the number of the operation tools in the step. The type and the number of the needed surgical tools are determined according to the surgical tools needed by the data of the whole surgical operation process in the database, then the operation arm is moved to scan the markers in the surgical tool master library through the positioning device to obtain the position information of the surgical tools, and then the operation arm end is moved through the surgical tool universal connector at the tail end of the operation arm end to be connected with the surgical tool universal connector surgical tool end of the needed surgical tools, so that the needed surgical tools are taken out from the surgical tool master library and placed on the surgical tool moving platform. The system software screens out all doctor operation process data corresponding to the type of pathological changes, analyzes the doctor operation process data by adopting a machine learning method to determine the operation method of the surgical tool of the type of pathological changes, and then determines the operation method of the surgical tool aiming at the current patient by combining the information of the current patient including the medical image. After determining the operation method of the surgical tool for the current patient, the system software controls the mobile operation arm and the surgical tool mobile platform to reach an operation preparation area, and the operation bed moves the patient to an operation area, so that the preparation work is completed. After the preparation work is finished, firstly, the operation arm is moved to scan a marker on the operation tool moving platform through the positioning device to obtain the position information of an operation tool, then, the operation tool universal connector at the tail end of the operation arm is moved to connect the operation tool universal connector of the operation tool needed by the operation tool, after the operation tool is connected, the positioning device scans the marker on the operation table to obtain the position information of the operation area of the patient, then, the operation arm is moved to be independently connected according to the operation method of the operation tool of the current patient, the needed operation tool is replaced between the adjacent steps, and the operation is finished by the cooperation of the plurality of operation arms.
Claims (10)
1. The systematic method of autonomous medical robot capable of executing various operations includes operation tool library, operation tool moving platform, operation bed, several movable operation arms, positioning device fixed onto the movable operation arms and system software.
The surgical tool total library comprises a surgical tool universal connector surgical tool end, various surgical tools and markers for acquiring the position information of the various surgical tools by a positioning device.
The surgical tool moving platform comprises a moving vehicle capable of placing various surgical tools, a marker for acquiring the position information of the surgical tool moving platform by a positioning device, an automatic navigation system of the surgical tool moving platform and an automatic moving system of the surgical tool moving platform.
The operating table comprises a marker for acquiring the position information of the operating table by the positioning device.
The mobile operation arm comprises a mechanical arm, a positioning device fixed on the mobile operation arm, a surgical tool universal connector mobile operation arm end and a marker used for the positioning device to obtain the position information of the mobile operation arm.
Characterized in that the working process comprises
Collecting the operation process data of each doctor to the patient and the corresponding patient information for treatment to form a database of the subsequent machine learning operation method, wherein the information comprises all operation steps of all doctors in the operation process, and operation related information such as the posture, the motion track, the motion state, the patient information and the like of the operation tool in each step;
the method comprises the following steps of performing medical imaging on the part where the lesion area of the patient is located, firstly placing the patient on an operating table, and then automatically moving the operating table with an automatic navigation system and an automatic motion system to perform various examinations such as CT (computed tomography), nuclear magnetic resonance and the like on the patient without manual intervention;
after the examination is finished, diagnosing the medical imaging result by adopting a machine learning method so as to determine the type of the current lesion of the patient;
the system software screens out all the data of the doctor operation process corresponding to the lesion of the type in the database according to the lesion type of the current patient;
after the system software screens out the data of the operation process of the doctor with the pathological changes of the type, the type and the number of the operation tools used in each step in the operation process of the type are determined, the step with the largest number of the operation tools is determined, and the number of the movable operation arms is equal to the number of the operation tools in the step. Determining the type and the number of the needed surgical tools according to the surgical tools needed by the data of the whole surgical operation process in the database, then moving the operation arm to scan the markers in the surgical tool master library through the positioning device to obtain the position information of the surgical tools, and then moving the operation arm end through the surgical tool universal connector at the tail end of the operation arm end to connect the surgical tool universal connector surgical tool end of the needed surgical tools, thereby taking out the needed surgical tools from the surgical tool master library and placing the surgical tools on a surgical tool moving platform;
the system software screens out all doctor operation process data corresponding to the type of pathological changes, analyzes the doctor operation process data by adopting a machine learning method to determine the operation method of the operation tool of the type of pathological changes, and then determines the operation method of the operation tool aiming at the current patient by combining the information of the current patient including medical images;
after the operation method of the surgical tool for the current patient is determined, the system software controls the mobile operation arm and the surgical tool mobile platform to reach an operation preparation area, and the operation bed moves the patient to an operation area, so that the preparation work is completed;
after the preparation work is finished, firstly, the operation arm is moved to scan a marker on the operation tool moving platform through the positioning device to obtain the position information of an operation tool, then, the operation tool universal connector at the tail end of the operation arm is moved to connect the operation tool universal connector of the operation tool needed by the operation tool, after the operation tool is connected, the positioning device scans the marker on the operation table to obtain the position information of the operation area of the patient, then, the operation arm is moved to be independently connected according to the operation method of the operation tool of the current patient, the needed operation tool is replaced between the adjacent steps, and the operation is finished by the cooperation of the plurality of operation arms.
2. The method of claim 1, wherein the collection of data from a database of procedure data and corresponding treatment information for each physician on a patient is performed by a person not using the robotic system, or by a person not using the robotic system.
3. The method of claim 1, wherein the surgical procedure includes not only various surgical procedures but also various treatment procedures of other doctors.
4. The method of claim 1, wherein the patient information includes not only basic physical information of the patient but also other information for disease treatment such as medical image information.
5. The systematic method of autonomous medical robots capable of performing various operations as claimed in claim 1, wherein the marker is a black and white two-dimensional code checkerboard marker or other markers for positioning.
6. The systematic approach of autonomous medical robots capable of performing various operations as claimed in claim 1, wherein the mobile manipulator can not only reproduce the posture, motion trajectory and motion state of the surgical tool in each step of all doctors during the surgical operation, but also perform the surgical operation different from the doctor's operation steps and method according to the surgical purpose.
7. The systematic approach of autonomous medical robots capable of performing various operations as claimed in claim 1, wherein the positioning device can be a positioning device such as a positioning camera or other devices with positioning function.
8. The systematic method of autonomous medical robots capable of performing various operations as claimed in claim 1, wherein the region including the lesion region may be a certain region of a human body, or other regions may be medically imaged according to the need of surgery.
9. The method of claim 1, wherein the positioning device is mounted at different positions of the mobile manipulator arm according to specific application.
10. The systematic method of autonomous medical robots capable of performing various operations according to claim 1, wherein the machine learning method for diagnosing the imaging result is a maskrnn machine learning method or other machine learning methods with diagnostic function.
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