CN111407416B - Tremor elimination method and system for vascular intervention surgical robot system - Google Patents
Tremor elimination method and system for vascular intervention surgical robot system Download PDFInfo
- Publication number
- CN111407416B CN111407416B CN202010257572.3A CN202010257572A CN111407416B CN 111407416 B CN111407416 B CN 111407416B CN 202010257572 A CN202010257572 A CN 202010257572A CN 111407416 B CN111407416 B CN 111407416B
- Authority
- CN
- China
- Prior art keywords
- tremor
- slave
- signal
- equipment
- acceleration
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 206010044565 Tremor Diseases 0.000 title claims abstract description 128
- 230000008030 elimination Effects 0.000 title claims abstract description 50
- 238000003379 elimination reaction Methods 0.000 title claims abstract description 50
- 238000000034 method Methods 0.000 title claims abstract description 34
- 230000002792 vascular Effects 0.000 title abstract description 27
- 230000001133 acceleration Effects 0.000 claims abstract description 90
- 238000006073 displacement reaction Methods 0.000 claims description 105
- 210000004204 blood vessel Anatomy 0.000 claims description 13
- 238000001914 filtration Methods 0.000 claims description 9
- 238000005516 engineering process Methods 0.000 claims description 8
- 238000009795 derivation Methods 0.000 claims description 7
- 238000001356 surgical procedure Methods 0.000 claims description 6
- 230000006378 damage Effects 0.000 claims description 5
- 230000008569 process Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 description 17
- 241000282414 Homo sapiens Species 0.000 description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000009471 action Effects 0.000 description 4
- 239000012636 effector Substances 0.000 description 3
- 238000012935 Averaging Methods 0.000 description 2
- 206010049565 Muscle fatigue Diseases 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000003116 impacting effect Effects 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000013152 interventional procedure Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- 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
- A61B34/37—Master-slave robots
-
- 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
- A61B34/70—Manipulators specially adapted for use in surgery
- A61B34/75—Manipulators having means for prevention or compensation of hand tremors
-
- 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
- A61B34/70—Manipulators specially adapted for use in surgery
- A61B34/76—Manipulators having means for providing feel, e.g. force or tactile feedback
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- 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
- A61B2034/303—Surgical robots specifically adapted for manipulations within body lumens, e.g. within lumen of gut, spine, or blood vessels
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Surgery (AREA)
- Life Sciences & Earth Sciences (AREA)
- Robotics (AREA)
- Biomedical Technology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Animal Behavior & Ethology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Manipulator (AREA)
Abstract
A tremor elimination method and system aiming at a vascular intervention surgical robot system mainly comprise a physiological tremor elimination strategy and a stress tremor elimination strategy; the strategy for eliminating the stress tremor mainly comprises the identification and compensation of the stress tremor caused by tension, wherein the identification is mainly from the perspective of safe collision force, and safe acceleration is indirectly obtained by utilizing Newton's second law; the real-time acceleration and the safe acceleration are compared to achieve the purpose of identifying and compensating the stress tremor; the strategy has very strong practicability and generalization performance in the field of high-precision medical instruments operated by hands, and has simple structure and easy realization.
Description
Technical Field
The invention belongs to the technical field of medical robots, in particular to a tremor elimination method and a system for a vascular intervention surgical robot system, which can indirectly identify physiological tremor of human beings caused by tension from the perspective of safe contact force and achieve the function of eliminating the tremor, and the application scene is mainly in the field of master-slave medical robots operated by human beings.
Background
With the rapid development of telemedicine technology, more and more master-slave surgical robot systems are put into use. The most frequently used and most rapidly developed robot system is a master-slave type vascular interventional surgery robot system. The master-slave vascular interventional surgical robot system has the working mode that: the main end operation equipment of the master-slave type blood vessel intervention operation robot system is operated by a doctor, the main end operation equipment acquires displacement signals of hands of the doctor through a linear displacement sensor, the displacement signals at the moment are analog signals, the displacement signals are transmitted to a central processing unit through an analog interface, the central processing unit internally converts the analog signals into digital signals in a self-running mode, the slave end operation equipment receives the displacement signals transmitted by the central processing unit through a digital interface, the received displacement signals are digital signals converted and completed by the central processing unit, the displacement signals at the moment are transmitted to a stepping motor installed on the slave end operation equipment through the digital interface, the stepping motor receives the displacement signals and then drives the slave end operation equipment to displace, and the operation is carried out. However, since the master-end operation device of the master-slave vascular interventional surgical robot system needs to be operated by a human hand, the inevitable problem is that the motion signal acquisition device at the master end acquires the slight tremor of the human hand while acquiring the normal motion of the human hand, and the slight tremor is expressed on the slave-end operation device. This subtle tremor can often cause fatal injury to the patient during vascular interventional procedures where accuracy is critical. But the technology for eliminating the hand tremor of the main end of a minimally invasive surgical robot system is still a blank field, and in order to solve the technical problem, the invention provides a tremor elimination strategy specially aiming at the vascular intervention surgical robot system, regular physiological tremor is identified and eliminated by the frequency and amplitude of the known physiological tremor, the safe acceleration is obtained by utilizing the safe contact force through the Newton's second law, and the stress tremor caused by tension is identified and eliminated by measuring the acceleration of the hand action in real time and comparing the measured acceleration with the safe acceleration.
Disclosure of Invention
The invention aims to provide a tremor elimination method for a vascular intervention surgical robot system, which can make up for the defects of the prior art and is a method which is simple to operate, easy to realize and capable of effectively eliminating tremor.
The technical scheme adopted by the invention is as follows: a tremor elimination method for a vascular intervention surgical robot system is characterized by comprising two parts of regular physiological tremor recognition and elimination and stress tremor recognition and elimination caused by tension; the regular physiological tremor is caused by muscle fatigue due to long operation time, and the tremor in the form presents a sinusoidal state with the frequency of 8-12 Hz and the amplitude of about 50 μm; the stress tremor caused by tension is caused by the inevitable tension during the operation, and in this case, the human hand generates a stress tremor which is difficult to identify because of no regularity.
The regular physiological tremor identification and elimination method is characterized in that the tremor is identified and eliminated by utilizing the tremor rule, and specifically comprises the following steps:
(1) acquiring a displacement signal of a doctor hand by a linear displacement sensor, wherein the acquired signal is a time domain signal, performing Fourier transform on the signal, converting the signal from the time domain signal into a frequency domain signal, and obtaining the frequency distribution of the original time domain signal;
(2) because the physiological tremor rule is mainly embodied in frequency and presents a frequency form of 8-12 Hz, the frequency domain signal obtained in the step (1) is filtered by an ideal filter technology;
in the step (2), the ideal filter technology is used for filtering the signal, specifically: the ideal filter is used for filtering out signals with specified frequency by setting the signals with the specified frequency to be 0, setting all the signals with the frequency between 8 Hz and 12Hz in the signals to be 0, and setting all the signals with other frequencies to be 1, so that the aims of identifying and filtering physiological tremor are fulfilled.
(3) And (3) performing Fourier inversion on the frequency signal obtained in the step (2) and filtered out the physiological tremor, converting the frequency signal into a time domain signal again, transmitting the time domain signal to a stepping motor arranged on the slave end surgical equipment, and driving the slave end surgical equipment to move by a driving motor to perform surgery.
The identification and elimination of stress tremor caused by stress specifically comprises the following steps:
(1) placing the contact end of the force sensor at the end point of the displacement from the end surgical device, and colliding with the pressure sensor when moving from the end to the place where the force measuring device is installed, thereby obtaining a collision force F;
(2) in order to improve the data accuracy, the collision force of the slave-end surgical equipment moving under three random accelerations is measured by the force measuring equipment;
and (3) selecting three random accelerations in the step (2), wherein the three random accelerations are respectively 1 cm/s, 2 cm/s and 4 cm/s.
(3) According to Newton's second law F ═ Ma, three masses can be obtained under three different accelerations, and the M coefficient of the slave surgical equipment, namely the mass parameter in the Newton's second law, is obtained by averaging the three masses;
(4) the safety force threshold value of the slave end operation device is 120mn, when the force of the slave end contacting the blood vessel exceeds 120mn, the blood vessel is at risk of being punctured, and the safe acceleration of the motion of the slave end operation device can be obtained by substituting the M coefficient obtained in the step (3) into F ═ Ma through Newton's second law;
(5) acquiring a displacement signal of the main-end operating equipment as a time-domain signal by using a linear displacement sensor, and obtaining the displacement signal after physiological tremor is eliminated after the physiological tremor elimination strategy shown in fig. 2, wherein the displacement signal at the moment is the time-domain signal; the 1 microsecond displacement signal is subjected to second-order derivation, and the real-time acceleration of the motion of the main-end operation equipment can be obtained;
(6) during the advancing of the catheter from the end-effector, if the catheter does not contact the vessel wall, the following steps are not performed, and the following steps (7) - (8) are continued only when the vessel wall is contacted;
the judging mode of whether the catheter contacts the vessel wall in the step (6) is as follows: measuring the real-time acceleration of the slave-end surgical equipment through an incremental photoelectric encoder, and when the real-time acceleration of the slave-end surgical equipment is reduced, proving that the catheter starts to touch the blood vessel wall, starting to enter the steps (7) - (8), otherwise, returning to the step (5);
(7) comparing the real-time acceleration of the motion of the main-end operation equipment obtained in the step (5) with the safe acceleration obtained in the step (4); if the acceleration is greater than the safe acceleration, the tremor belongs to dangerous tremor, and if the slave surgical equipment continues to move at the same acceleration, the force generated by collision between the slave surgical equipment and the vessel wall after the slave surgical equipment pushes the catheter into the vessel can possibly puncture the vessel to harm the life safety of the patient, and the displacement at the moment is judged to be dangerous stress tremor;
(8) and (3) eliminating the dangerous tremor obtained in the step (7), and if the displacement signal of 1 microsecond is judged as a dangerous signal according to the judgment result in the step (7), the displacement signal of 1 microsecond cannot be transmitted to the slave end surgical equipment and drives the motor to displace, and the dangerous stress tremor is filtered in a mode that the dangerous signal is directly abandoned and is not transmitted to the slave end surgical equipment.
A system for realizing regular physiological tremor identification and elimination comprises a master end operation device, a slave end operation device and a central controller, and is characterized in that the system is composed of a linear displacement sensor, a stepping motor and an incremental photoelectric encoder; the linear displacement sensor is used for acquiring hand motion signals of a doctor; the stepping motor drives the slave end operation equipment to displace so as to achieve the purpose of completing the operation; the incremental photoelectric encoder is used for receiving a motion signal of the slave surgical equipment; the central controller is used for receiving the displacement signals acquired by the linear displacement sensor through the analog signal interface, and transmitting the tremor-removed signals to the stepping motor on the slave surgical equipment for driving through the digital signal interface after the defibrillation treatment; the control signals between the slave end operation equipment and the central controller are transmitted in two directions; and the motion signals between the main-end operation equipment and the central controller are transmitted in two directions.
The linear displacement sensor is a TP-0200-.
The stepping motor is an ARM24SAK-H100 type stepping motor produced by Orientalmotor.
The incremental photoelectric encoder is a GTH08-OC-RAG2500Z1-2M incremental photoelectric encoder.
The central controller employs an Arduino DUE microprocessor.
A system for realizing the recognition and elimination of stress tremor caused by tension comprises a main end operation device, a slave end operation device, a medical catheter and a central controller, and is characterized in that the system consists of a linear displacement sensor, a force measuring device and a stepping motor; the linear displacement sensor is used for obtaining linear displacement data of the master end operation equipment and the slave end operation equipment; the force measuring equipment consists of a pressure sensor and a digital display; the pressure sensor is used for measuring the collision force of the slave surgical equipment and displaying the information of the collision force on the digital display; the stepping motor is used for driving the catheter for the instrument to move.
The linear displacement sensor and the linear displacement sensor in the system for identifying and eliminating regular physiological tremor are the same device.
The force measuring device is a force measuring device produced by Contronix.
The stepping motor is an ARM24SAK-H100 type stepping motor for driving the medical catheter to advance.
The working principle of the invention is as follows: regular physiological tremor is identified and eliminated by utilizing the tremor rule, and the physiological tremor rule is mainly reflected in frequency and presents in a form of 8-12 Hz. The main method for identifying the law is to perform Fourier transform on the collected displacement signal of the main-end operator, convert the signal from a time domain signal to a frequency domain signal, the frequency domain signal can represent the frequency distribution of the time domain signal, and then all signals of 8-12 Hz are set to be 0 and all signals of other frequencies are set to be 1 through an ideal filter, so that the physiological tremor can be identified and filtered.
For stress tremor caused by stress, the main way of identification is based on the safety force of the catheter contacting the vessel wall and the newton's second law, which has been derived from existing studies, three quantities of which are force F, mass M and acceleration a, we need to derive a safety acceleration from the safety touch force and mass M from the end-surgical device, by comparing the real-time acceleration with the safety acceleration; from a surgical safety standpoint, the force of the end-effector impacting the vessel wall after advancing the catheter into the vessel has a safe threshold of 120 mn. When the collision force is larger than the threshold value, the blood vessel is possibly punctured to harm the life safety of a patient, according to the safety force threshold value of the catheter contacting the blood vessel wall and Newton's second law in the known technology, the safety acceleration is obtained, the motion speed of the main end operation equipment is measured by using the linear displacement sensor, the real-time motion speed is compared with the safety acceleration, the time interval for reading the linear displacement sensor is set to be 1 microsecond in a central processing unit Arduino DUE, 1 microsecond is the minimum interval for reading data by the Arduino DUE, the minimum acquisition interval is adopted to improve the accuracy of acquiring the hand motion of a doctor, after the displacement signal of 1 microsecond is acquired, the displacement signal of 1 microsecond is subjected to secondary derivation to obtain the real-time acceleration of the doctor operating the main end operator within 1 microsecond, and the acceleration of 1 microsecond is compared with the safety acceleration, if the acceleration is greater than the safe acceleration, the vibration is identified as unsafe chatter, the 1 microsecond displacement information is not transmitted to the slave-end surgical equipment, if the acceleration is less than the safe acceleration, the motion is within the safe acceleration range, the safe normal operation is considered, the 1 microsecond displacement information is transmitted to the slave-end surgical equipment, the stepping motor is driven to move, and the dangerous chatter is identified and eliminated in the mode.
A force-measuring device manufactured by Contronix, the device comprising a pressure sensor and a digital display. The propulsion acceleration of the slave-end surgical equipment is set to be a known fixed value by using a mode that an Arduino DUE microprocessor outputs regular PWM waves, the slave-end surgical equipment propels and collides with a force sensor under the condition of known acceleration, real-time collision force is displayed on a digital display, and M of the slave-end surgical equipment can be calculated by using the real-time collision force and the known acceleration through Newton's second law. In order to realize the strategy, the collected displacement data needs to be processed to obtain an analog voltage value through a TP-0200-. And linear displacement data of the master-end device and the slave-end device are obtained (see fig. 5).
The invention has the advantages that: the recognition and elimination of stress tremor and physiological tremor caused by manual operation in the system are realized; stress tremor caused by tension can be removed at the same time under the condition of removing regular physiological tremor; the medical robot system has higher safety and improves the success rate of the operation by eliminating the tremor; has higher practicability and research value in the field of medical robots.
Drawings
Fig. 1 is a hardware overall framework diagram of a tremor elimination method for a vascular intervention surgical robotic system according to the present invention.
FIG. 2 is a schematic flow chart of a regular physiological tremor elimination method in the tremor elimination method for a vascular interventional surgical robot system according to the present invention.
FIG. 3 is a schematic flow chart of a stress tremor elimination method caused by stress in the tremor elimination method of the vascular interventional surgical robot system according to the present invention.
Fig. 4 is a schematic diagram of a specific implementation principle of recognizing stress tremor caused by tension in a tremor elimination method for a vascular intervention surgical robot system according to the present invention.
Fig. 5 is a schematic diagram of an implementation manner of processing motion data in a tremor elimination method for a vascular intervention surgical robot system according to the present invention.
Detailed Description
Example (b): a tremor elimination method for a vascular intervention surgical robot system is characterized by comprising two parts of identification and elimination of regular physiological tremor and identification and elimination of stress tremor caused by tension, which are respectively shown in fig. 2 and fig. 3; the regular physiological tremor is caused by muscle fatigue due to long operation time, and the tremor in the form presents a sinusoidal state with the frequency of 8-12 Hz and the amplitude of about 50 μm; the stress tremor caused by tension is caused by the inevitable tension during the operation, and in this case, the human hand generates a stress tremor which is difficult to identify because of no regularity.
The regular physiological tremor is identified and eliminated by utilizing the tremor rule, and as shown in fig. 2, the method specifically comprises the following steps:
(1) the linear displacement sensor is used for acquiring displacement signals of the hands of a doctor, the acquired signals are time-domain signals, in order to ensure the acquisition accuracy, the minimum acquisition interval of the central processing unit is 1 microsecond, and the smaller the used acquisition interval is, the higher the accuracy of the acquired displacement signals is; carrying out Fourier transform on the signal, converting the signal from a time domain signal into a frequency domain signal, and obtaining the frequency distribution of the original time domain signal; acquiring 1 microsecond displacement information for eliminating physiological tremor, and performing secondary derivation on the displacement information in a subsequent strategy for eliminating stress tremor to obtain real-time acceleration; the time domain signal and the frequency domain signal are opposite to each other in signal form and can be converted into each other, and the analog signal and the digital signal are opposite to each other in signal form and can be converted into each other;
(2) because the physiological tremor rule is mainly embodied in frequency and presents a frequency form of 8-12 Hz, the frequency domain signal obtained in the step (1) is filtered by an ideal filter technology;
in the step (2), the ideal filter technology is used for filtering the signal, specifically: the ideal filter is used for filtering out signals with specified frequency by setting the signals with the specified frequency to be 0, setting all the signals with the frequency between 8 Hz and 12Hz in the signals to be 0, and setting all the signals with other frequencies to be 1, so that the aims of identifying and filtering physiological tremor are fulfilled.
(3) And (3) performing Fourier inversion on the frequency signal obtained in the step (2) and filtered out the physiological tremor, converting the frequency signal into a time domain signal again, transmitting the time domain signal to a stepping motor arranged on the slave end surgical equipment, and driving the slave end surgical equipment to move by a driving motor to perform surgery.
The identification and elimination of stress tremor caused by stress, as shown in fig. 3, specifically comprises the following steps:
(1) placing the contact end of the force sensor at the end point of the displacement from the end surgical device, and colliding with the pressure sensor when moving from the end to the place where the force measuring device is installed, thereby obtaining a collision force F;
(2) in order to improve the data accuracy, the collision force of the slave-end surgical equipment moving under three random accelerations is measured by the force measuring equipment;
and (3) selecting three random accelerations in the step (2), wherein the three random accelerations are respectively 1 cm/s, 2 cm/s and 4 cm/s.
(3) According to Newton's second law F ═ Ma, three masses can be obtained under three different accelerations, and the M coefficient of the slave surgical equipment, namely the mass parameter in the Newton's second law, is obtained by averaging the three masses;
(4) the safety force threshold value of the slave end operation device is 120mn, when the force of the slave end contacting the blood vessel exceeds 120mn, the blood vessel is at risk of being punctured, and the safe acceleration of the motion of the slave end operation device can be obtained by substituting the M coefficient obtained in the step (3) into F ═ Ma through Newton's second law;
(5) acquiring a displacement signal of the main-end operating equipment as a time-domain signal by using a linear displacement sensor, and obtaining the displacement signal after physiological tremor is eliminated after the physiological tremor elimination strategy shown in fig. 2, wherein the displacement signal at the moment is the time-domain signal; the 1 microsecond displacement signal is subjected to second-order derivation, and the real-time acceleration of the motion of the main-end operation equipment can be obtained;
(6) during the advancing of the catheter from the end-effector, if the catheter does not contact the vessel wall, the following steps are not performed, and the following steps (7) - (8) are continued only when the vessel wall is contacted;
the judging mode of whether the catheter contacts the vessel wall in the step (6) is as follows: measuring the real-time acceleration of the slave-end surgical equipment through an incremental photoelectric encoder, and when the real-time acceleration of the slave-end surgical equipment is reduced, proving that the catheter starts to touch the blood vessel wall, starting to enter the steps (7) - (8), otherwise, returning to the step (5);
(7) comparing the real-time acceleration of the motion of the main-end operation equipment obtained in the step (5) with the safe acceleration obtained in the step (4); if the acceleration is greater than the safe acceleration, the tremor belongs to dangerous tremor, and if the slave surgical equipment continues to move at the same acceleration, the force generated by collision between the slave surgical equipment and the vessel wall after the slave surgical equipment pushes the catheter into the vessel can possibly puncture the vessel to harm the life safety of the patient, and the displacement at the moment is judged to be dangerous stress tremor;
(8) and (3) eliminating the dangerous tremor obtained in the step (7), and if the displacement signal of 1 microsecond is judged as a dangerous signal according to the judgment result in the step (7), the displacement signal of 1 microsecond cannot be transmitted to the slave end surgical equipment and drives the motor to displace, and the dangerous stress tremor is filtered in a mode that the dangerous signal is directly abandoned and is not transmitted to the slave end surgical equipment.
A system for realizing regular physiological tremor identification and elimination is shown in figure 1 and comprises a main end operation device, a slave end operation device and a central controller, and is characterized in that the system is composed of a linear displacement sensor, a stepping motor and an incremental photoelectric encoder; the linear displacement sensor is used for acquiring hand motion signals of a doctor; the stepping motor drives the slave end operation equipment to displace so as to achieve the purpose of completing the operation; the incremental photoelectric encoder is used for receiving a motion signal of the slave surgical equipment; the central controller is used for receiving the displacement signals acquired by the linear displacement sensor through the analog signal interface, and transmitting the tremor-removed signals to the stepping motor on the slave surgical equipment for driving through the digital signal interface after the defibrillation treatment; the control signals between the slave end operation equipment and the central controller are transmitted in two directions; and the motion signals between the main-end operation equipment and the central controller are transmitted in two directions.
The linear displacement sensor is a TP-0200-.
The stepping motor is an ARM24SAK-H100 type stepping motor produced by Orientalmotor.
The incremental photoelectric encoder is a GTH08-OC-RAG2500Z1-2M incremental photoelectric encoder.
The central controller employs an Arduino DUE microprocessor.
A system for realizing the recognition and elimination of stress tremor caused by tension comprises a main end operation device, a slave end operation device, a medical catheter and a central controller, as shown in figure 4, and is characterized in that the system consists of a linear displacement sensor, a force measuring device and a stepping motor; the linear displacement sensor is used for obtaining linear displacement data of the master end operation equipment and the slave end operation equipment; the force measuring equipment consists of a pressure sensor and a digital display; the pressure sensor is used for measuring the collision force of the slave surgical equipment and displaying the information of the collision force on the digital display; the stepping motor is used for driving the catheter for the instrument to move.
The linear displacement sensor and the linear displacement sensor in the system for identifying and eliminating regular physiological tremor are the same device.
The force measuring device is a force measuring device produced by Contronix.
The stepping motor is an ARM24SAK-H100 type stepping motor for driving the medical catheter to advance.
The present invention will be described in further detail with reference to the following embodiments, which are illustrative only and not limiting, and the scope of the present invention is not limited thereby.
A tremor elimination method for a vascular intervention surgical robot system specifically comprises the following steps:
(1) obtaining the M coefficient of the mobile end of the slave end operation equipment for implementing the strategy;
(2) according to the mode shown in fig. 4, the contact end of the force sensor is placed at the terminal point of the movable end of the surgical equipment, and the contact end of the force sensor is collided when the movable end moves to the terminal point, so that collision force is obtained;
(3) the slave surgical device is measured by force sensors to move the tip at three different sets of accelerations: 1 cm/sec, 2 cm/sec, 4 cm/sec, measuring the impact force during movement, and randomly selecting three groups of accelerations only to increase the data accuracy;
(4) under the condition that three groups of accelerations and collision forces which are artificially set are known, an M coefficient can be obtained according to Newton's second law;
(5) after the M coefficient is obtained, the safety force threshold value 120mn of the known data is obtained through previous research, and the safety acceleration of the moving end of the slave end surgical equipment is calculated in a mode that the acceleration can be obtained under the condition of known force and mass M through Newton's second law;
(6) the linear displacement sensor 2 is used for acquiring displacement data of the hands of a doctor, the acceleration of movement is obtained in a secondary derivation mode, and the frequency data of physiological tremor is obtained by performing Fourier transform on signals;
(7) under the condition of frequency distribution of a known physiological tremor law, firstly, the motion data can process displacement data according to a strategy shown in fig. 2, the physiological tremor is identified and eliminated according to a known frequency range of 8-12 Hz, the principle mode for identifying the law is to perform Fourier transformation on an acquired displacement signal of a main-end operator, the signal is converted into a frequency domain signal from a time domain signal, the frequency domain signal can represent the frequency distribution of the time domain signal, all signals of 8-12 Hz are set to be 0 through an ideal filter, all signals of other frequencies are set to be 1, and the physiological tremor can be identified and filtered through the method.
(8) After physiological tremor is eliminated, displacement data enter a strategy shown in fig. 3, the motion speed of the master-end operation equipment is measured by using a linear displacement sensor, the real-time motion speed is compared with a safe acceleration, if the acceleration is greater than the safe acceleration, the 1 microsecond displacement information is not transmitted to the slave-end operation equipment, if the acceleration is less than the safe acceleration, the 1 microsecond displacement information is transmitted to the slave-end operation equipment and drives a motor to move, and dangerous tremor is identified and eliminated in such a way;
(9) after elimination by the strategy of fig. 2 and 3, physiological tremor and stress tremor are identified and filtered out.
The following is a further description of the drawings:
FIG. 1 is a hardware overall framework diagram of a tremor elimination method for a vascular interventional surgical robotic system according to the present invention; which comprises the following steps: an Arduino DUE microprocessor, a TP-0200-101-411-102-type linear displacement sensor, a slave-end surgical device, a GTH08-OC-RAG2500Z1-2M incremental photoelectric encoder and a master-end operator.
FIG. 2 is a schematic flow chart of a regular physiological tremor elimination method in the tremor elimination method for a vascular interventional surgical robot system according to the present invention; firstly, displacement signals are collected through a linear displacement sensor on main-end surgical equipment, the collected displacement signals are transmitted to a central processing unit through an analog interface, Fourier analysis is carried out on the signals in the central processing unit to convert time domain signals into frequency domain signals, an ideal filter is used for filtering, the displacement signals after physiological tremor is filtered are obtained through Fourier inverse transformation, and the displacement signals at the moment are transmitted to the next strategy.
FIG. 3 is a schematic flow chart of the stress tremor elimination method caused by stress in the tremor elimination method of the vascular interventional surgical robot system according to the present invention; firstly, signals output from the strategy of fig. 2 are received, the process of transmitting signals between the two strategies is completely finished in the central processing unit, then whether the catheter contacts with the vascular wall is judged through whether the acceleration measured by the incremental photoelectric encoder arranged at the moving end of the slave operation equipment changes, the strategy is mainly aimed at the condition that the catheter touches the vascular wall, the strategy is not executed under the non-contact condition, the calculation burden of the central processing unit can be reduced, the real-time acceleration is mainly measured through the incremental encoder, if the acceleration changes, the obstruction force is received, if the acceleration of the moving end of the slave operation equipment changes, the resistance when the catheter contacts with the vascular wall is received, and if the catheter contacts with the vascular wall, the strategy is continuously executed. And performing secondary derivation on the displacement data of the main-end manipulator measured by the linear displacement sensor to obtain real-time acceleration, comparing the measured acceleration of the main-end manipulator with the safe acceleration, if the measured acceleration is smaller than the safe acceleration, indicating that the action is safe, otherwise, judging that the action is unsafe, and if the action is safe, transmitting the displacement signal to the slave-end surgical equipment as a control signal of the stepping motor to drive the stepping motor to perform displacement so as to achieve the purpose of completing the surgery.
Fig. 4 is a schematic diagram illustrating a method for calculating a threshold of a safe acceleration in a tremor elimination method of a robot system for vascular intervention surgery according to the present invention. The acceleration of the slave-end surgical equipment is set through the central processing unit, the force sensor is used for measuring the collision force under the set acceleration, and finally the mass coefficient M of the slave-end surgical equipment is obtained through a Newton's second law formula. A safe acceleration threshold is then derived from the mass coefficient M of the end-use surgical device, and a known safe force threshold using Newton's second law.
Fig. 5 is a schematic diagram of an implementation manner of processing motion data in a tremor elimination method for a vascular intervention surgical robot system according to the present invention. The slave-end surgical equipment carrying the catheter is driven by the stepping motor to displace, the real-time acceleration of the slave-end surgical equipment is measured by the incremental photoelectric encoder arranged on the stepping motor, and the real-time acceleration of the slave-end surgical equipment is transmitted to the central processing unit for processing. The linear displacement sensor is used for measuring the displacement of the operating equipment at the main end operated by the hands of the doctor and transmitting a displacement signal to the central processing unit for processing.
Although the embodiments of the present invention and the accompanying drawings are disclosed for illustrative purposes, those skilled in the art will appreciate that: various substitutions, changes and modifications are possible without departing from the spirit and scope of the invention and the appended claims, and therefore the scope of the invention is not limited to the disclosure of the embodiments and the accompanying drawings.
Claims (7)
1. A system for realizing regular physiological tremor identification and elimination comprises a master end operation device, a slave end operation device and a central controller, and is characterized in that the system is composed of a linear displacement sensor, a stepping motor and an incremental photoelectric encoder; the linear displacement sensor is used for acquiring hand motion signals of a doctor; the stepping motor drives the slave end operation equipment to displace so as to achieve the purpose of completing the operation; the incremental photoelectric encoder is used for receiving a motion signal of the slave surgical equipment; the central controller is used for receiving the displacement signals acquired by the linear displacement sensor through the analog signal interface, and transmitting the tremor-removed signals to the stepping motor on the slave surgical equipment for driving through the digital signal interface after the defibrillation treatment; the control signals between the slave end operation equipment and the central controller are transmitted in two directions; the motion signals between the main end operation equipment and the central controller are transmitted in two directions;
the tremor elimination method for realizing the system for regular physiological tremor identification and elimination comprises the following steps:
(1) acquiring a displacement signal of a doctor hand by a linear displacement sensor, wherein the acquired signal is a time domain signal, performing Fourier transform on the signal, converting the signal from the time domain signal into a frequency domain signal, and obtaining the frequency distribution of the original time domain signal;
(2) because the physiological tremor rule is mainly embodied in frequency and presents a frequency form of 8-12 Hz, the frequency domain signal obtained in the step (1) is filtered by an ideal filter technology;
(3) and (3) performing Fourier inversion on the frequency domain signal obtained in the step (2) and filtered out the physiological tremor, converting the frequency domain signal into a time domain signal again, transmitting the time domain signal to a stepping motor arranged on the slave end surgical equipment, and driving the slave end surgical equipment to move by a driving motor to perform surgery.
2. The system according to claim 1, wherein the step (2) utilizes an ideal filter technique to filter out signals, specifically: the ideal filter is used for filtering out signals with specified frequency by setting the signals with the specified frequency to be 0, setting all the signals with the frequency between 8 Hz and 12Hz in the signals to be 0, and setting all the signals with other frequencies to be 1, so that the aims of identifying and filtering physiological tremor are fulfilled.
3. The system for achieving regular physiological tremor identification and elimination of claim 1, wherein the linear displacement sensor is the linear displacement sensor of TP-0200-; the stepping motor is an ARM24SAK-H100 type stepping motor produced by Orientalmotor; the incremental photoelectric encoder is a GTH08-OC-RAG2500Z1-2M incremental photoelectric encoder; the central controller employs an Arduino DUE microprocessor.
4. A system for realizing the recognition and elimination of stress tremor caused by tension comprises a main end operation device, a slave end operation device, a medical catheter and a central controller, and is characterized in that the system consists of a linear displacement sensor, a force measuring device and a stepping motor; the linear displacement sensor is used for obtaining linear displacement data of the master end operation equipment and the slave end operation equipment; the force measuring equipment consists of a pressure sensor and a digital display; the pressure sensor is used for measuring the collision force of the slave surgical equipment and displaying the information of the collision force on the digital display; the stepping motor is used for driving the catheter for the instrument to move;
the tremor elimination method of the system for realizing recognition and elimination of stress tremor caused by tension comprises the following steps:
placing a contact end of a force sensor at the displacement endpoint of a slave-end surgical device, and colliding with a pressure sensor when the slave-end surgical device moves to a position where a force measuring device is installed, so as to obtain a collision force F;
secondly, in order to improve the data accuracy, the collision force of the slave-end surgical equipment moving under three random accelerations during movement is measured through force measuring equipment;
thirdly, according to Newton's second law F = Ma, three masses can be obtained under three different accelerations, and the M coefficient of the slave surgical equipment, namely the mass parameter in the Newton's second law, is obtained by calculating the average value of the three masses;
the safety force threshold value of the slave end operation equipment is 120mn, when the force of the slave end contacting the blood vessel exceeds 120mn, the blood vessel has the risk of being punctured, and the M coefficient obtained in the step (III) is substituted into F = Ma through Newton's second law, so that the safe acceleration of the motion of the slave end operation equipment can be obtained;
acquiring a displacement signal of the main-end operating equipment as a time domain signal by a linear displacement sensor, and obtaining the displacement signal after physiological tremor is eliminated after a physiological tremor elimination strategy, wherein the displacement signal is the time domain signal; obtaining the real-time acceleration of the motion of the main-end operation equipment by second-order derivation of the displacement signal;
sixthly, in the process of driving the catheter to move forwards by the end operation equipment, if the catheter does not contact the blood vessel wall, the following step is not executed, and the following step is executed again only when the catheter contacts the blood vessel wall;
seventhly, comparing the real-time acceleration of the movement of the main end operation equipment obtained in the fifth step with the safe acceleration obtained in the fourth step; if the acceleration is greater than the safe acceleration, the tremor belongs to dangerous tremor, and if the slave surgical equipment continues to move at the same acceleration, the force generated by collision between the slave surgical equipment and the vessel wall after the slave surgical equipment pushes the catheter into the vessel can possibly puncture the vessel to harm the life safety of the patient, and the displacement at the moment is judged to be dangerous stress tremor;
and (e) eliminating the dangerous tremor obtained in the step (c), and according to the judgment result in the step (c), if the displacement signal is judged to be a dangerous signal, the displacement signal cannot be transmitted to the slave surgical equipment and drives the motor to displace, and the dangerous stress tremor is filtered by directly abandoning the dangerous signal and not transmitting the dangerous signal to the slave surgical equipment.
5. The system for realizing the recognition and elimination of stress tremor caused by tension according to claim 4, wherein the random acceleration of three of the steps (II) is selected from three accelerations, which are 1 cm/sq.s, 2 cm/sq.s and 4 cm/sq.s.
6. The system for realizing the recognition and the elimination of stress tremor caused by tension according to claim 4, wherein the judgment of whether the catheter contacts the vessel wall in the step (c) is as follows: measuring the real-time acceleration of the slave surgical equipment by an incremental photoelectric encoder, and when the real-time acceleration of the slave surgical equipment is reduced, proving that the catheter starts to touch the vessel wall, and entering the step (c) - (b), otherwise, returning to the step (c).
7. The system for recognizing and eliminating stress tremor caused by stress according to claim 4, wherein the linear displacement sensor is the linear displacement sensor of TP-0200-; the force measuring device is a force measuring device produced by Contronix; the stepping motor is an ARM24SAK-H100 type stepping motor for driving the medical catheter to advance.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010257572.3A CN111407416B (en) | 2020-04-03 | 2020-04-03 | Tremor elimination method and system for vascular intervention surgical robot system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010257572.3A CN111407416B (en) | 2020-04-03 | 2020-04-03 | Tremor elimination method and system for vascular intervention surgical robot system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111407416A CN111407416A (en) | 2020-07-14 |
| CN111407416B true CN111407416B (en) | 2021-02-26 |
Family
ID=71486473
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010257572.3A Active CN111407416B (en) | 2020-04-03 | 2020-04-03 | Tremor elimination method and system for vascular intervention surgical robot system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111407416B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113103205B (en) * | 2021-04-16 | 2023-04-11 | 山东大学 | Control method and system for inhibiting tail end vibration of master-slave robot mechanical arm |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0980672A1 (en) * | 1998-08-18 | 2000-02-23 | Hiroshi Matsumoto | Diagnostic system and method for coronary artery disease |
| US6053886A (en) * | 1997-08-12 | 2000-04-25 | Medtek Devices, Inc. | Switch apparatus for operating an evacuator |
| WO2005089830A2 (en) * | 2004-03-22 | 2005-09-29 | Smart Medical Solutions B.V. | Catheter and method for use of such a catheter for removing a stenosis from a vessel |
| CN101612043A (en) * | 2009-08-04 | 2009-12-30 | 中国科学院合肥物质科学研究院 | The wearable type human arm tremor detects and suppresses robot and method for suppressing tremor thereof |
| CN104546246A (en) * | 2015-01-04 | 2015-04-29 | 苏州英络医疗器械有限公司 | Vascular stent conveying system and conveying method thereof |
| CN107684459A (en) * | 2017-09-30 | 2018-02-13 | 天津理工大学 | Blood vessel intervention operation robot manipulation's security early warning system and method based on LabView |
| CN108366838A (en) * | 2015-10-16 | 2018-08-03 | 医疗显微器具股份公司 | Robotic surgery component |
| CN109308521A (en) * | 2018-08-27 | 2019-02-05 | 广东工业大学 | A kind of quaternary SerComm degree study filtering method for eliminating Physiological tremor |
| CN109730779A (en) * | 2019-03-07 | 2019-05-10 | 天津理工大学 | A kind of blood vessel intervention operation robotic catheter seal wire cooperative control system and method |
| CN209713130U (en) * | 2017-09-30 | 2019-12-03 | 天津理工大学 | A kind of safety early warning system of blood vessel intervention operation operation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| NL1025780C2 (en) * | 2004-03-22 | 2005-09-26 | Smart Medical Solutions B V | Catheter and method for using such a catheter for removing a stenosis from a vessel. |
-
2020
- 2020-04-03 CN CN202010257572.3A patent/CN111407416B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6053886A (en) * | 1997-08-12 | 2000-04-25 | Medtek Devices, Inc. | Switch apparatus for operating an evacuator |
| EP0980672A1 (en) * | 1998-08-18 | 2000-02-23 | Hiroshi Matsumoto | Diagnostic system and method for coronary artery disease |
| WO2005089830A2 (en) * | 2004-03-22 | 2005-09-29 | Smart Medical Solutions B.V. | Catheter and method for use of such a catheter for removing a stenosis from a vessel |
| CN101612043A (en) * | 2009-08-04 | 2009-12-30 | 中国科学院合肥物质科学研究院 | The wearable type human arm tremor detects and suppresses robot and method for suppressing tremor thereof |
| CN104546246A (en) * | 2015-01-04 | 2015-04-29 | 苏州英络医疗器械有限公司 | Vascular stent conveying system and conveying method thereof |
| CN108366838A (en) * | 2015-10-16 | 2018-08-03 | 医疗显微器具股份公司 | Robotic surgery component |
| CN107684459A (en) * | 2017-09-30 | 2018-02-13 | 天津理工大学 | Blood vessel intervention operation robot manipulation's security early warning system and method based on LabView |
| CN209713130U (en) * | 2017-09-30 | 2019-12-03 | 天津理工大学 | A kind of safety early warning system of blood vessel intervention operation operation |
| CN109308521A (en) * | 2018-08-27 | 2019-02-05 | 广东工业大学 | A kind of quaternary SerComm degree study filtering method for eliminating Physiological tremor |
| CN109730779A (en) * | 2019-03-07 | 2019-05-10 | 天津理工大学 | A kind of blood vessel intervention operation robotic catheter seal wire cooperative control system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111407416A (en) | 2020-07-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| AU2019295378B2 (en) | Detecting collisions of robot arms | |
| CN111407416B (en) | Tremor elimination method and system for vascular intervention surgical robot system | |
| CN104337666A (en) | Multi-muscle collaborative myoelectricity feedback rehabilitation training system and method | |
| CN114311031B (en) | Master-slave end delay test method, system, storage medium and equipment for surgical robot | |
| CN109910057B (en) | Collision test method and system for rehabilitation robot | |
| CN109521880B (en) | Teleoperation robot system and method based on mixed bioelectricity signal driving | |
| CN105892676B (en) | Human-computer interaction device, system and method of wire feeding mechanism for vascular intervention operation | |
| Phan et al. | Capacitive skin sensors for robot impact monitoring | |
| CN111383763B (en) | Knee joint movement information processing method, device, equipment and storage medium | |
| Zhang et al. | Upper limb motion capturing and classification for unsupervised stroke rehabilitation | |
| Marbán et al. | Haptic feedback in surgical robotics: Still a challenge | |
| Peng et al. | sEMG-based torque estimation for robot-assisted lower limb rehabilitation | |
| CN112043384B (en) | External force prediction system of fracture reduction robot | |
| CN107198508B (en) | Recovery degree sequencing method and combined interactive training system | |
| Taghavi et al. | Online dynamic time warping algorithm for human-robot imitation | |
| CN111383733B (en) | Motion monitoring and correcting method, device, equipment and storage medium based on knee joint motion signals | |
| CN113171177B (en) | Human-computer interaction control method and system capable of capturing breakthrough sensation of lumbar puncture tissue layer | |
| Hussein et al. | Detection of electrocardiogram QRS complex based on modified adaptive threshold | |
| CN115154847A (en) | Operation device and force measuring method for slender medical instrument | |
| CN115990060A (en) | Surgical robot slave-end operation device, pressure detection device and data processing method | |
| EP2979628B1 (en) | Vascular viscoelasticity evaluation device, vascular viscoelasticity evaluation method, and program | |
| Chen et al. | A novel clamping mechanism for circumferential force feedback device of the vascular interventional surgical robot | |
| Duchemin et al. | Robotized skin harvesting | |
| Gopal et al. | Tremor acquisition and reduction for robotic surgical applications | |
| Nakaya et al. | A practical approach for recognition of hand gesture and distinction of its singularity |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220104 Address after: 518112 801-806, building 12, China Hisense innovation industry city, No. 12, Ganli Sixth Road, gankeng community, Jihua street, Longgang District, Shenzhen, Guangdong Province Patentee after: Shenzhen Aibo medical robot Co.,Ltd. Address before: 300384 No. 391 Binshui West Road, Xiqing District, Tianjin Patentee before: TIANJIN University OF TECHNOLOGY |
|
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: 518112 801-806, building 12, China Hisense innovation industry city, No. 12, Ganli Sixth Road, gankeng community, Jihua street, Longgang District, Shenzhen, Guangdong Province Patentee after: Shenzhen Aibo Hechuang Medical Robot Co.,Ltd. Address before: 518112 801-806, building 12, China Hisense innovation industry city, No. 12, Ganli Sixth Road, gankeng community, Jihua street, Longgang District, Shenzhen, Guangdong Province Patentee before: Shenzhen Aibo medical robot Co.,Ltd. |