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CN116153154B - A control method for anesthesia needle positioning device - Google Patents

A control method for anesthesia needle positioning device Download PDF

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Publication number
CN116153154B
CN116153154B CN202211571599.5A CN202211571599A CN116153154B CN 116153154 B CN116153154 B CN 116153154B CN 202211571599 A CN202211571599 A CN 202211571599A CN 116153154 B CN116153154 B CN 116153154B
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pressure
data
channel
intelligent processing
pressure sensing
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CN116153154A (en
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黄闻晶
张智峰
吴冬冬
童睿
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Zhejiang Institute Of Science And Innovation New Materials
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Zhejiang Institute Of Science And Innovation New Materials
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    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
    • G09B9/00—Simulators for teaching or training purposes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
    • G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
    • G01L5/16—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes for measuring several components of force
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Educational Administration (AREA)
  • Educational Technology (AREA)
  • Inking, Control Or Cleaning Of Printing Machines (AREA)
  • Force Measurement Appropriate To Specific Purposes (AREA)

Abstract

本发明公开了一种麻醉进针定位装置的控制方法，该方法基于麻醉进针定位装置，麻醉进针定位装置包括平台机构、压力感应机构、编码器机构、打印机构和智能处理机构，压力感应机构、编码器机构和打印机构分别设置于平台机构，压力感应机构、编码器机构和打印机构分别与智能处理机构连接，本发明压力感应组件感应滚轮行经棘突及棘突间隙的受力情况，实现不同组织对滚轮力的反馈，智能处理机构得到实时的压力数据，编码器将记录边轮的转动次数转换成电信号传输至智能处理机构，智能处理机构将实时压力数据和实时移动距离数据拟合，智能处理机构根据曲线自动计算出最佳的进针位置，智能处理机构控制打印头移动至目标位置进行标记。

The present invention discloses a control method for an anesthesia needle positioning device. The method is based on the anesthesia needle positioning device. The anesthesia needle positioning device includes a platform mechanism, a pressure sensing mechanism, an encoder mechanism, a printing mechanism and an intelligent processing mechanism. The pressure sensing mechanism, the encoder mechanism and the printing mechanism are respectively arranged on the platform mechanism. The pressure sensing mechanism, the encoder mechanism and the printing mechanism are respectively connected to the intelligent processing mechanism. The pressure sensing component of the present invention senses the force of the roller passing through the spinous process and the spinous process gap, so as to realize the feedback of the roller force by different tissues. The intelligent processing mechanism obtains real-time pressure data. The encoder converts the number of rotations of the recording edge wheel into an electrical signal and transmits it to the intelligent processing mechanism. The intelligent processing mechanism fits the real-time pressure data and the real-time moving distance data. The intelligent processing mechanism automatically calculates the best needle insertion position according to the curve. The intelligent processing mechanism controls the print head to move to the target position for marking.

Description

Control method of anesthesia needle insertion positioning device
Technical Field
The invention belongs to the field of medical appliances, and relates to a control method of an anesthetic needle insertion positioning device.
Background
Epidural anesthesia puncture devices are widely used clinically as medical instruments for surgical anesthesia. When simulating an epidural anesthesia, a physician needs to select the appropriate anesthesia needle insertion site. The anesthetic needle insertion position is generally selected from the gap between lumbar vertebrae L2, L3 or the gap between lumbar vertebrae L3, L4. At present, in the simulation operation, a doctor usually adopts two methods to position two gaps, namely firstly, the doctor touches the sacrum of the human body model, then touches the spinous processes of the lumbar vertebrae upwards along the sacrum, sequentially confirms each lumbar vertebra, selects the position needing to be inserted into a needle after confirming the lumbar vertebra, marks the position by a pen, secondly, the doctor stands on the back of the human body model, opens the thumb and the index finger, presses the index finger on the upper limit of the ilium, presses the thumb to the spine in parallel, finds the spinal gap by pressing up and down, and marks the spinal gap by the pen.
Both the above methods are based on the needle insertion position selected by the doctor's touch sense, and the needle insertion position method selected by the doctor's touch sense sometimes causes the problem of low puncture precision because the needle insertion position is not centered enough or the optimal puncture gap cannot be selected, and in addition, the bone may be pricked or deviate from the puncture direction in the puncture process, and finally the epidural anesthesia simulation operation fails.
Disclosure of Invention
The invention provides a control method of an anesthesia needle inserting positioning device, which aims to overcome the defects of the prior art.
In order to achieve the aim, the invention adopts the following technical scheme that the method for controlling the anesthesia needle insertion positioning device is based on the anesthesia needle insertion positioning device, and comprises a platform mechanism, a pressure sensing mechanism, an encoder mechanism, a printing mechanism and an intelligent processing mechanism, wherein the pressure sensing mechanism, the encoder mechanism and the printing mechanism are respectively arranged on the platform mechanism, and the pressure sensing mechanism, the encoder mechanism and the printing mechanism are respectively connected with the intelligent processing mechanism, and the method comprises the following specific steps of:
Step 1, preprocessing an anesthesia needle insertion positioning device, wherein the preprocessing comprises confirming the running states of a pressure sensing mechanism, an encoder mechanism, a printing mechanism and an intelligent processing mechanism;
Step 2, the anesthesia needle insertion positioning device moves along the lumbar surface of the human model spine, the pressure sensing mechanism collects real-time pressure data, and the encoder mechanism collects real-time moving distance data and transmits the real-time moving distance data to the intelligent processing mechanism;
Step 3, after the intelligent processing mechanism processes the data, fitting the data to form a pressure fluctuation curve, and obtaining a target position according to the fitted pressure fluctuation curve;
And 4, controlling the printing head to move to the target position by the intelligent processing mechanism, printing marks on the body surface of the target position by the printing head, and ending the step.
Further, the pressure sensing mechanism comprises three groups of pressure sensing assemblies, the three groups of pressure sensing assemblies are respectively divided into a first channel, a second channel and a third channel, the first channel and the third channel are positioned in the middle of lumbar vertebrae, and the first channel and the third channel are positioned on two sides of the second channel.
Further, the step 3 includes the following steps:
Step 3.1, the intelligent processing mechanism receives the real-time pressure data output by the three groups of pressure detection modules in the step 2 to form corresponding pressure data sets F1 Ti、F2Ti and F3 Ti;
The real-time pressure data set collected by the first channel is set as F1 Ti, the real-time pressure data set collected by the second channel is set as F2 Ti, the real-time pressure data set collected by the third channel is set as F3 Ti,F1Ti＝(F1 i,Ti)、F2Ti＝(F2i,Ti) and F3 Ti＝(F3i,Ti), F represents a pressure value, T represents a sampling time, and i represents an aggregation number;
Step 3.2, the pressure data sets F1 Ti、F2Ti and F3 Ti are processed by a normalization function, and the pressure data sets are respectively obtained after the processing And
Step 3.3, the intelligent processing mechanism receives real-time moving distance data acquired by the encoder mechanism in the step2 and pressure data processed in the step 3.2, and fits a 3D image;
step 3.4, kalman filtering the pressure data image and the 3D image;
And 3.5, the intelligent processing mechanism samples the data filtered in the step 3.4, a pressure fluctuation curve is formed by fitting, and a target position is obtained according to the fitted pressure fluctuation curve.
Further, in the step 3.2
In the formulas (1) - (3), prF ti_list is the data list of the pressure data set F1 Ti, prF ti_list is the data list of the pressure data set F2 Ti, prF3ti_list is the data list of the pressure data set F3 Ti, prF ti_list.max () is the data maximum value of the pressure data set F1 Ti, prF ti_list.max () is the data maximum value of the pressure data set F2 Ti, prF ti_list.max () is the data maximum value of the pressure data set F3 Ti, and α is the weight coefficient of the spring 1233 in the three sets of pressure sensing members 12.
Further, the formula for fitting the 3D image in the step 3.3 is:
in the formula (4), N represents the first, second, and third channels, Y represents the position distances in the distribution directions of the first, second, and third channels, and D represents the pressing distance of the roller 126.
Further, the calculation formula of the kalman filter in the step 3.4 includes:
X(k,k-1)=AX(k-1)+BU(k)....................(5);
In the formula (5), k represents the current time, k-1 represents the last time, X (k-1) represents the last state optimum result of the system, X (k, k-1) represents the result of the current state of the system predicted by the last state optimum result of the system, A and B are system parameters, A and B are set as matrixes, U (k) represents the control quantity of the system at the current time, A, B and U (k) are set as set values, and U (k) can be set as 0, namely
No control amount;
Covariance calculation formula corresponding to X (k, k-1):
P(k,k-1)=AP(k-1)AT+Q.......................(6);
In the formula (6), P (k, k-1) is covariance corresponding to X (k, k-1), P (k-1) is covariance corresponding to X (k-1), A T is transposed matrix of A, Q is covariance of system process, and Q is set value not changed along with system state change;
From the formulas (5) and (6), the formula (7) is obtained,
X(k)=X(k,k-1)+K(k)[Z(k)-HX(k,k-1)]....................(7)
In the formula (7), X (K) is an optimal estimated value at the moment K, K (K) is a Kalman gain, In the formula (4), H is a parameter of a measurement system, for a multi-measurement system, H is set as a matrix, H T is a transposed matrix of H, R is covariance of system measurement, H, R is a set value, Z (k) is a system measurement value, and Z (k) is a set value;
covariance calculation formula corresponding to X (k):
P(k)=[I-K(k)H]P(k,k-1)........................(9);
In the formula (9), P (k) is a covariance corresponding to X (k), where I is set as a matrix and I is a set value.
Further, α=0.9 in the step 3.2.
Further, the pressure sensing mechanism further comprises a back plate and a transverse moving assembly, the pressure sensing assembly is arranged on the back plate through the transverse moving assembly, and the transverse moving assembly controls the pressure sensing assembly to synchronously move inwards or outwards.
Further, the pressure sensing assembly comprises a vertical plate, a pressure detection module, a pressure conduction module and an elastic module, wherein the pressure detection module and the pressure conduction module are arranged on the vertical plate, the pressure detection module comprises a sensor, the vertical plate is provided with a sensor mounting seat, the sensor is arranged on the sensor mounting seat, the sensor faces the pressure conduction module, and the sensor is connected with the intelligent processing mechanism.
Further, the pressure detection module comprises a sensor, the vertical plate is provided with a sensor mounting seat, the sensor is arranged on the sensor mounting seat, the sensor faces the pressure conduction module, and the sensor is connected with the intelligent processing mechanism.
In summary, the invention has the following advantages:
1) The intelligent processing mechanism automatically calculates the optimal needle inserting position according to the curve, controls the printing head to move to the target position for marking, accurately positions the needle inserting position of the anesthesia outside the hard film in the simulation practice process, improves the accuracy of the needle inserting point of anesthesia, shortens the confirmation time of the needle inserting point, has high intelligent degree, and is used for simulating the positioning reaction speed and the positioning accuracy of the needle inserting point of anesthesia.
2) According to the invention, the pressure sensing assemblies synchronously move inwards or outwards through the transverse moving assemblies, so that the distance between adjacent pressure sensing assemblies is adjusted, and the pressure sensing assemblies are moved to proper positions.
3) The invention is provided with the elastic module, and the adjusting nut of the elastic module can compress or loosen the spring, so that the prestress of the roller is increased or reduced.
4) The limiting block is arranged, and the sliding range of the lower sliding block is limited by the limiting block, so that the roller support frame is prevented from sliding downwards, and the spring is continuously compressed downwards, so that larger elastic stress is applied to the roller.
5) The platform mechanism is provided with the registering block, the spring force of the pressure sensing assembly is balanced with the self gravity of the device through the registering block, the platform mechanism is provided with a plurality of groups of side wheels, the side wheels provide stable supporting force for the device, and meanwhile, the resistance of the device in the pushing process can be reduced.
Drawings
Fig. 1 is a front view of the device of the present invention.
Fig. 2 is a rear view of the device of the present invention.
Fig. 3 is a front view of the pressure sensing mechanism of the present invention.
Fig. 4 is a right side view of the pressure sensing mechanism of the present invention.
Fig. 5 is a rear view of the pressure sensing mechanism of the present invention.
Fig. 6 is an assembled front view of the platform mechanism, encoder mechanism and printing mechanism of the present invention.
FIG. 7 is an assembled side view of the platform mechanism, encoder mechanism, and printing mechanism of the present invention.
Fig. 8 is a flow chart of the anesthetic needle insertion positioning method according to the invention.
Figure 9 is a schematic view of a lumbar vertebra in a manikin of the present invention.
FIG. 10 is a graph of pressure data for channel one, channel two, and channel three of the present invention.
Fig. 11 is a 3D image fitted with the travel distance data and the pressure data of the present invention.
FIG. 12 is a graph of the pressure data of FIG. 10 after Kalman filtering.
Fig. 13 is a 3D image of fig. 11 after kalman filtering.
Fig. 14 is a graph of pressure fluctuations of the present invention.
The pressure sensing mechanism 1, the platform mechanism 2, the encoder mechanism 3, the printing mechanism 4, the back plate 10, the traversing assembly 11, the pressure sensing assembly 12, the traversing rail 110, the through cavity 101, the traversing block 111, the bearing block 112, the knob 114, the screw 113, the adjusting plate 115, the sensor mount 120, the sensor 121, the conducting block 122, the roller support 124, the stopper 125, the roller 126, the vertical plate 127, the vertical rail 128, the upper slider 1221, the lower slider 1241, the adjusting nut 1231, the screw 1232, the spring 1233, the registration block 21, the armrest 22, the side wheel frame 23, the side wheel 24, the encoder 31, the encoder mounting plate 32, the coupler 33, the print head 41, and the printing rail 42 are identified in the figure.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
All directional indications (such as up, down, left, right, front, rear, lateral, longitudinal) in embodiments of the present invention are merely used to explain the relative positional relationship, movement, etc. between the components in a particular pose, and if the particular pose changes, the directional indication changes accordingly.
For reasons of installation errors, the parallel relationship referred to in the embodiments of the present invention may be an approximately parallel relationship, and the perpendicular relationship may be an approximately perpendicular relationship.
Embodiment one:
As shown in fig. 1-7, an anesthesia needle insertion positioning device comprises a platform mechanism 2, a pressure sensing mechanism 1, an encoder mechanism 3, a printing mechanism 4 and an intelligent processing mechanism, wherein the pressure sensing mechanism 1, the encoder mechanism 3 and the printing mechanism 4 are respectively arranged on the platform mechanism 2, and the pressure sensing mechanism 1, the encoder mechanism 3 and the printing mechanism 4 are respectively connected with the intelligent processing mechanism.
The pressure sensing mechanism 1 comprises a back plate 10, a transverse moving assembly 11 and a pressure sensing assembly 12, wherein the pressure sensing assembly 12 is arranged on the back plate 10 through the transverse moving assembly 11, the transverse moving assembly 11 comprises transverse sliding rails 110, transverse sliding blocks 111, bearing seats 112, knobs 114, screws 113 and adjusting plates 115, the transverse sliding blocks 111 and the adjusting plates 115 are fixedly arranged on the pressure sensing assembly 12, the transverse sliding rails 110 and the bearing seats 112 are fixedly arranged on two side surfaces of the back plate 10, the transverse sliding rails 110 face the pressure sensing assembly 12, the transverse sliding blocks 111 are arranged on the transverse sliding rails 110, the transverse sliding blocks 111 are in sliding connection with the transverse sliding rails 110, preferably, the transverse sliding rails 110 are arranged in two, the two transverse sliding rails 110 are perpendicular to the length direction of the back plate and are distributed up and down along the length direction of the back plate, and the length direction of the back plate is the x direction in fig. 1, so that the stability of connection with the pressure sensing assembly 12 and the transverse moving stability of the pressure sensing assembly 12 are guaranteed.
The back plate 10 is provided with a through cavity 101, the adjusting plate 115 penetrates through the cavity 101, the screw 113 is rotationally connected with the bearing seat 112, two ends of the screw 113 are fixedly connected with the knob 114, the screw 113 is in threaded connection with the adjusting plate 115, preferably, the adjusting plate 115 is provided with two pieces, the two adjusting plates 115 are symmetrically arranged on two sides of the bearing seat 112, the screw 113 is provided with threads with opposite rotation directions, the adjusting plate 115 is arranged on the threads with opposite rotation directions of the screw 113, and any knob 114 is rotated to enable the two adjusting plates 115 to synchronously move inwards or outwards.
The pressure sensing components 12 are arranged in multiple groups, preferably as shown in fig. 1, the pressure sensing components 12 are arranged in three groups, the three groups of pressure sensing components 12 are distributed along the transverse array of the width direction of the back plate 10, the width direction of the back plate 10 is the y direction in fig. 1, the pressure sensing components 12 positioned in the middle are fixedly arranged on the back plate 10, the pressure sensing components 12 positioned at two sides are fixedly arranged on the transverse sliding blocks 111, and the distance between the pressure sensing components 12 positioned in the middle is synchronously adjusted through the transverse sliding components 11.
The pressure sensing component 12 comprises a vertical plate 127, a pressure detection module, a pressure conduction module and an elastic module, wherein the pressure detection module and the pressure conduction module are arranged on the vertical plate 127, the pressure detection module, the elastic module and the pressure conduction module are distributed along the length direction of the vertical plate 127, the length direction of the vertical plate 127 is the x direction in fig. 1, the vertical plate 127 is provided with a vertical sliding rail 128, the vertical sliding rail 128 is distributed along the length direction of the vertical plate 127, and the stress of the pressure conduction module is conducted to the pressure detection module through the elastic module.
The pressure detection module comprises a sensor 121, a vertical plate 127 is provided with a sensor mounting seat 120, the sensor 121 is arranged on the sensor mounting seat 120, the sensor 121 faces the pressure conduction module, the sensor 121 is connected with the intelligent processing mechanism, the sensor 121 converts received force data into electric signals and transmits the electric signals to the intelligent processing mechanism, and the intelligent processing mechanism obtains real-time pressure data.
The pressure conduction module comprises a conduction block 122 and a roller support 124, the conduction block 122 is opposite to the sensor 121, the sensor 121 is used for detecting the pressure conducted by the conduction block 122, the conduction block 122 and the roller support 124 are connected through an elastic module, the conduction block 122 is provided with an upper sliding block 1221, the upper sliding block 1221 is arranged on a vertical sliding rail 128, the upper sliding block 1221 is in sliding connection with the vertical sliding rail 128, the roller support 124 is provided with a lower sliding block 1241, the lower sliding block 1241 is arranged on the vertical sliding rail 128, the lower end of the roller support 124 is provided with a roller 126, and the upper end of the roller support 124 is connected with the conduction block 122 through the elastic module.
The elastic module includes an adjusting nut 1231, a screw rod 1232 and a spring 1233, the screw rod 1232 is connected with the conducting block 122 and the roller support 124, the spring 1233 is sleeved on the screw rod 1232, the adjusting nut 1231 is arranged on the screw rod 1232, in this embodiment, the spring 1233 is located between the adjusting nut 1231 and the roller support 124, and the adjusting nut 1231 is rotated to compress or loosen the spring 1233, so that the prestress of the roller 126 is increased or reduced.
The stopper 125 is set at the lower end of the vertical plate 127, and the stopper 125 is located at the lower end of the limiting vertical slide rail 128 to limit the sliding range of the lower slide block 1241, so as to block the roller support 124 from sliding downwards, and the spring is compressed downwards continuously to apply larger elastic stress to the roller 126.
In the implementation process of the pressure sensing component 12, when the roller 126 contacts with the body surface and rolls, and the roller 126 rolls to the soft tissue position of the human body model, under the action of the elastic force of the elastic module, the roller 126 sags, at this time, the conduction block 122 moves downwards, the stress of the sensor 121 is reduced, the reading of the sensor is also reduced, when the roller 126 rolls to the bone tissue position of the human body model, the roller 126 is jacked up by the bone tissue of the human body model to move upwards, the spring 1233 is further compressed, the elastic force is increased, the conduction block 122 moves upwards, the stress of the sensor 121 is increased, and the reading of the sensor is also increased.
The platform mechanism 2 is a carrier of the pressure sensing mechanism 1, the encoder mechanism 3 and the printing mechanism 4 and comprises an upper end face and a lower end face, the lower end face is opposite to the body surface, the upper end face of the platform mechanism 2 is provided with a registration block 21 and an armrest 22, the registration block 21 is positioned at two ends of the platform mechanism 2 according to the visual angle of fig. 1 so as to ensure the balance of the platform mechanism 2, the registration block 21 is used for adding a counterweight to balance the spring force of the pressure sensing assembly 12 with the self gravity of the device, the number of the registration blocks 21 is increased or decreased according to actual needs, the armrest 22 is provided with two armrests 22 positioned at two sides of the platform mechanism 2 so as to facilitate taking and placing the device, the lower end face of the platform mechanism 2 is provided with an edge wheel frame 23 and an edge wheel 24, the edge wheel frame 23 is arranged at two sides of the platform mechanism 2, the edge wheel frame 23 is arranged at the edge wheel frame 23, and one group of edge wheel frame 23 is preferably provided with two groups of edge wheels 24, and the edge wheel 24 provides stable supporting force for the device, and meanwhile the resistance of the pushing process of the device can be reduced.
The encoder mechanism 3 sets up the lower terminal surface at the platform mechanism 2, the encoder mechanism 3 includes encoder 31, encoder mounting panel 32 and shaft coupling 33, encoder mounting panel 32 sets up in the lower terminal surface of platform mechanism 2, encoder 31 sets up in encoder mounting panel 32, encoder 31 passes through shaft coupling 33 with the axis of rotation of arbitrary side wheel 24 to be connected, drive encoder 31 synchronous rotation through shaft coupling 33 when side wheel 24 rotates, encoder 31 records the number of times of rotation of side wheel 24, encoder 31 is connected with intelligent processing mechanism, encoder 31 converts the number of times of rotation of record side wheel 24 into electric signal transmission to intelligent processing mechanism, intelligent processing mechanism obtains the real-time travel distance of device.
The printing mechanism 4 is arranged on the lower end face of the platform mechanism 2, the printing mechanism 4 comprises a printing head 41 and a printing track 42, the printing track 42 is arranged on the lower end face of the platform mechanism 2 along the y direction, the printing head 41 is arranged on the printing track 42 and can slide along the printing track 42, the printing head 41 is connected with the intelligent processing mechanism, the intelligent processing mechanism controls the printing head 41 to slide on the printing track 42 until reaching a target position for printing, the printing head 41 directly prints a needle-inserting mark on a body surface, and therefore the function of accurately positioning the needle-inserting position for epidural anesthesia is achieved, the printing head 41 is connected with the intelligent processing mechanism, and the intelligent processing mechanism controls the printing head 41 to move to the target position and marks.
The intelligent processing mechanism combines the real-time pressure data and the real-time moving distance to obtain the distance between the spinous processes, and the maximum distance between the spinous processes is used as the needle insertion target position.
In the implementation process of the embodiment, an operator holds the armrest 22, places the device on the back of the mannequin, mediates the traversing assembly 11, separates three rollers 26 of the three groups of pressure sensing assemblies 12 to proper distances, pushes the device, the three groups of pressure sensing assemblies 12 record three groups of real-time pressure data respectively, an encoder records the real-time rotation times of the side wheel so as to obtain real-time moving distance data of the device, an intelligent processing mechanism fits the real-time pressure data with the real-time moving distance data to form a pressure fluctuation curve changing along with the distance, the intelligent processing mechanism automatically calculates the optimal needle feeding position, namely the target position, and when the device is pushed on the back of the person again, the intelligent processing mechanism controls the printing assembly to move to the target position, and marks are printed on the target position.
As shown in fig. 8-14, the application further provides a control method of an anesthesia needle insertion positioning device, the method is based on the anesthesia needle insertion positioning device, the anesthesia needle insertion positioning device comprises a platform mechanism 2, a pressure sensing mechanism 1, an encoder mechanism 3, a printing mechanism 4 and an intelligent processing mechanism, the pressure sensing mechanism 1, the encoder mechanism 3 and the printing mechanism 4 are respectively arranged on the platform mechanism 2, and the pressure sensing mechanism 1, the encoder mechanism 3 and the printing mechanism 4 are respectively connected with the intelligent processing mechanism, and the method comprises the following specific steps:
Step 1, preprocessing an anesthesia needle insertion positioning device, wherein the preprocessing comprises confirming the running states of a pressure sensing mechanism 1, an encoder mechanism 3, a printing mechanism 4 and an intelligent processing mechanism;
step 2, the anesthesia needle insertion positioning device moves along the lumbar surface of the subject spine, such as the lumbar surface of the human model spine (body surface for short), the pressure sensing mechanism 1 collects real-time pressure data, and the encoder mechanism 3 collects real-time moving distance data;
the anesthetic needle insertion positioning device is only used for identifying the lumbar vertebra of a human body model, wherein the total lumbar vertebra of the human body model is 5 knots, as shown in fig. 9, the upper parts of the anesthetic needle insertion positioning device are respectively L1, L2, L3, L4, L5 and L1, the thoracic vertebra is arranged above the anesthetic needle insertion positioning device, the structure of the anesthetic needle insertion positioning device is similar to that of the lumbar vertebra, the sacrum is arranged behind the L5, the sacrum is a large bone with a triangular shape, and in the embodiment, the roller 126 sequentially passes through the spinous processes of the lumbar vertebrae L5-L1, and the pressure sensing mechanism 1 acquires a data curve with at least 5 complete peaks.
Before the anesthesia needle-inserting positioning device is used, the waist of the human body model is bent, so that the lumbar vertebra of the spinal column of the human body model is protruded backwards, the spinous processes of all the lumbar vertebrae can keep larger spacing, and the anesthesia needle-inserting positioning device can better identify the spinous process clearance;
The pressure sensing mechanism 1 comprises three groups of pressure sensing assemblies 12, wherein the contact positions of the rollers 126 of the three groups of pressure sensing assemblies 12 and the body surface are different, and the waist of the human body model is bent when the anesthesia needle inserting positioning device moves, so that the deformation degrees of springs 1233 of elastic modules in the three groups of pressure sensing assemblies 12 are different, the real-time pressure data detected by the pressure detection modules of the three groups of pressure sensing assemblies 12 are different, the three groups of pressure sensing assemblies 12 are respectively divided into a first channel, a second channel and a third channel for convenience of explanation and distinction, the first channel and the third channel are positioned in the center of lumbar vertebrae, the first channel and the third channel are positioned at two sides of the second channel, the real-time pressure data acquired by the first channel, the second channel and the third channel and the real-time moving distance data acquired by the encoder mechanism 3 are transmitted to the intelligent processing mechanism for data processing.
Step 3, after the intelligent processing mechanism processes the data, fitting the data to form a pressure fluctuation curve, and obtaining a target position according to the fitted pressure fluctuation curve;
And 4, controlling the printing head to move to the target position by the intelligent processing mechanism, printing marks on the body surface of the target position by the printing head, and ending the step.
Step 3 the step of data fitting includes:
Step 3.1, the intelligent processing mechanism receives the real-time pressure data output by the three groups of pressure detection modules in the step 2 to form corresponding pressure data sets F1 Ti、F2Ti and F3 Ti;
The real-time pressure data set collected by the first channel is set as F1 Ti, the real-time pressure data set collected by the second channel is set as F2 Ti, the real-time pressure data set collected by the third channel is set as F3 Ti,F1Ti＝(F1 i,Ti)、F2Ti＝(F2i,Ti) and F3 Ti＝(F3i,Ti), F represents a pressure value, T represents a sampling time, and i represents an aggregation number;
Step 3.2, the pressure data sets F1 Ti、F2Ti and F3 Ti are processed by a normalization function, and the pressure data sets are respectively obtained after the processing And
Equation (1) -equation (3) prF ti_list is the data list of the pressure dataset F1 Ti, prF2ti_list is the data list of the pressure dataset F2 Ti, prF3ti_list is the data list of the pressure dataset F3 Ti, prF1ti_list.max () is the data maximum of the pressure dataset F1 Ti, prF2ti_list.max () is the data maximum of the pressure dataset F2 Ti, prF3ti_list.max () is the data maximum of the pressure dataset F3 Ti, α is the weight coefficient of the spring 1233 in the three sets of pressure sensing elements 12, α=0.9;
from pressure data sets AndObtaining pressure data images of the first channel, the second channel and the third channel, which are shown in fig. 10, wherein the pressure data change curve of the first channel is represented by a curve represented by a sensor1, the pressure data change curve of the second channel is represented by a curve represented by a sensor2, and the pressure data change curve of the third channel is represented by a curve represented by a sensor3 in fig. 10;
Step 3.3, the intelligent processing mechanism receives the real-time moving distance data collected by the encoder mechanism 3 in the step 2 and the pressure data processed in the step 3.2, fits a 3D image to obtain a 3D image shown in fig. 11, wherein the X coordinate in the 3D image is the moving distance data collected by the encoder mechanism 3, the Y coordinate is the distance between three groups of rollers 126, the D coordinate is the pressing distance of the rollers 126,
Fitting the 3D image to the calculated formula:
in the formula (4), N represents a first channel, a second channel, and a third channel, Y is a position distance in a distribution direction of the first channel, the second channel, and the third channel, for example, n=1 is the first channel, As shown in the figure, the present embodiment sets the position of the first channel in the direction as the origin, that is, y2=0, where the first channel and the third channel are on both sides of the second channel, Y1 and Y3 are positive and negative values, respectively, and D represents the pressing distance of the roller 126;
step 3.4, kalman filtering the pressure data image and the 3D image;
calculation formula of Kalman filtering:
X(k,k-1)=AX(k-1)+BU(k)....................(5)
In the formula (5), k represents the current time, k-1 represents the last time, X (k-1) represents the last state optimal result of the system, X (k, k-1) represents the result of the current state of the system predicted by the last state optimal result of the system, a and B are system parameters, a and B are set as matrices, U (k) represents the control quantity of the system at the current time, A, B and U (k) are set values, and U (k) can be set to 0, i.e. no control quantity;
Covariance calculation formula corresponding to X (k, k-1):
P(k,k-1)=AP(k-1)AT+Q.......................(6)
In the formula (6), P (k, k-1) is covariance corresponding to X (k, k-1), P (k-1) is covariance corresponding to X (k-1), A T is transposed matrix of A, Q is covariance of system process, and Q is set value not changed along with system state change;
From the formulas (5) and (6), the formula (7) is obtained,
X(k)=X(k,k-1)+K(k)[Z(k)-HX(k,k-1)]....................(7)
In the formula (7), X (K) is an optimal estimated value at the moment K, K (K) is a Kalman gain, In the formula (4), H is a parameter of a measurement system, for a multi-measurement system, H is set as a matrix, H T is a transposed matrix of H, R is covariance of system measurement, H, R is a set value, Z (k) is a system measurement value, and Z (k) is a set value;
covariance calculation formula corresponding to X (k):
P(k)=[I-K(k)H]P(k,k-1)........................(9)
in the formula (9), P (k) is covariance corresponding to X (k), wherein I is set as a matrix, I is a set value, and for a single-model single-measurement system, i=1, the autoregressive operation of the kalman filter is realized through the formula (9).
The pressure data image and the 3D image are filtered according to the formulas (5) - (9), so that the image is smoother after Kalman filtering, the burr is obviously reduced, and whether the spinal spinous process or the noise is easier to distinguish is easy to distinguish.
Step 3.5, the intelligent processing mechanism samples the data filtered in the step 3.4, a pressure fluctuation curve is formed by fitting, and a target position is obtained according to the fitted pressure fluctuation curve;
Based on the same sampling time T, the intelligent processing mechanism acquires the pressure average value of the first channel, the second channel and the third channel corresponding to the 3D image Y=0 plane after filtering in the step 3.4, obtains a data set (F i,di) corresponding to the pressure data and the distance data, forms a pressure fluctuation curve which changes along with the distance as shown in figure 14,
Wherein, the F i is the pressure average value of the first channel, the second channel and the third channel under the same sampling time T, d i is the moving distance data acquired by the encoder mechanism 3 under the same sampling time T, the pressure peak value of the pressure fluctuation curve is set to be F pN, the corresponding distance of the pressure peak value is set to be d pN,Δd＝dpN+1-dpN, Δd represents the peak distance, and N represents the sequence number of the peaks.
In this embodiment, the roller 126 sequentially passes through the spinous processes of the lumbar vertebrae L5-L1, and the pressure sensing mechanism 1 collects a data curve with at least 5 complete peaks, since the spinal cord end of the manikin is at the lower edge of L1 and the upper edge of L2. In order to reduce the risk of injury to the spinal cord of the model during the simulation, the epidural puncture is selected to avoid puncturing the spinous process gaps of L1-L2, so in this embodiment, the number N is 4, the spinous process gaps between L5-L2 and L5-L2 correspond to lumbar vertebrae L5-L2, respectively, the spinous process gap at the target position is set to D, D pN+1 corresponding to d=Δd Max,ΔdMax, and D pN are the moving positions of the printing mechanism 4.
In the step 4, the intelligent processing mechanism controls the printing head to move between d pN+1 and d pN corresponding to the delta d Max in the step 3.5, and the printing head prints marks on the body surface of the human model at the target position.
It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

Claims (7)

1.一种麻醉进针定位装置的控制方法,其特征在于：该方法基于麻醉进针定位装置，麻醉进针定位装置包括平台机构、压力感应机构、编码器机构、打印机构和智能处理机构，压力感应机构、编码器机构和打印机构分别设置于平台机构，压力感应机构、编码器机构和打印机构分别与智能处理机构连接，所述压力感应机构包括三组压力感应组件，三组压力感应组件分别分为通道一、通道二、通道三，通道二位于腰椎骨中央，通道一和通道三位于通道二的两侧，具体步骤为：1. A control method for an anesthesia needle positioning device, characterized in that: the method is based on the anesthesia needle positioning device, the anesthesia needle positioning device includes a platform mechanism, a pressure sensing mechanism, an encoder mechanism, a printing mechanism and an intelligent processing mechanism, the pressure sensing mechanism, the encoder mechanism and the printing mechanism are respectively arranged on the platform mechanism, the pressure sensing mechanism, the encoder mechanism and the printing mechanism are respectively connected to the intelligent processing mechanism, the pressure sensing mechanism includes three groups of pressure sensing components, the three groups of pressure sensing components are respectively divided into channel one, channel two, and channel three, channel two is located in the center of the lumbar vertebra, and channel one and channel three are located on both sides of channel two, and the specific steps are: 步骤1：麻醉进针定位装置预处理，包括确认压力感应机构、编码器机构、打印机构和智能处理机构的运行状态；Step 1: Preprocessing of the anesthesia needle positioning device, including confirming the operating status of the pressure sensing mechanism, the encoder mechanism, the printing mechanism and the intelligent processing mechanism; 步骤2：麻醉进针定位装置沿人体模型脊柱的腰椎部表面移动，压力感应机构采集实时的压力数据以及编码器机构采集实时的移动距离数据传输至智能处理机构；Step 2: The anesthesia needle positioning device moves along the surface of the lumbar vertebrae of the human body model spine, and the pressure sensing mechanism collects real-time pressure data and the encoder mechanism collects real-time movement distance data and transmits them to the intelligent processing mechanism; 步骤3：智能处理机构处理数据后，数据拟合形成压力波动曲线，根据拟合后的压力波动曲线得到目标位置；Step 3: After the intelligent processing mechanism processes the data, the data is fitted to form a pressure fluctuation curve, and the target position is obtained according to the fitted pressure fluctuation curve; 所述步骤3包括以下步骤：The step 3 comprises the following steps: 步骤3.1：智能处理机构接收步骤2三组压力检测模块输出的实时的压力数据形成对应的压力数据集F1Ti、F2Ti和F3Ti；Step 3.1: The intelligent processing mechanism receives the real-time pressure data output by the three groups of pressure detection modules in step 2 to form corresponding pressure data sets F1 Ti , F2 Ti and F3 Ti ; 通道一采集的实时的压力数据集设为F1Ti、通道二采集的实时的压力数据集设为F2Ti、通道三采集的实时的压力数据集设为F3Ti，F1Ti＝(F1i，Ti)、F2Ti＝(F2i，Ti)和F3Ti＝(F3i，Ti)，F表示压力值，T表示采样时间,i表示集合数；The real-time pressure data set collected by channel one is set to F1 Ti , the real-time pressure data set collected by channel two is set to F2 Ti , and the real-time pressure data set collected by channel three is set to F3 Ti , F1 Ti = (F1 i , T i ), F2 Ti = (F2 i , T i ) and F3 Ti = (F3 i , T i ), F represents the pressure value, T represents the sampling time, and i represents the number of sets; 步骤3.2：压力数据集F1Ti、F2Ti和F3Ti通过归一化函数处理，处理后分别得到压力数据集和 Step 3.2: The pressure data sets F1 Ti , F2 Ti and F3 Ti are processed by the normalization function to obtain the pressure data sets and 步骤3.3：智能处理机构接收步骤2中编码器机构采集实时的移动距离数据结合步骤3.2处理后的压力数据，拟合3D图像；Step 3.3: The intelligent processing mechanism receives the real-time moving distance data collected by the encoder mechanism in step 2 and combines it with the pressure data processed in step 3.2 to fit the 3D image; 步骤3.4：卡尔曼滤波过滤压力数据图像和3D图像；Step 3.4: Kalman filter filters the pressure data image and the 3D image; 步骤3.5：智能处理机构对步骤3.4滤波后的数据进行采样，拟合形成压力波动曲线，根据拟合后的压力波动曲线得到目标位置；Step 3.5: The intelligent processing mechanism samples the data filtered in step 3.4, fits it to form a pressure fluctuation curve, and obtains the target position according to the fitted pressure fluctuation curve; 步骤4：智能处理机构控制打印头移动至目标位置，打印头在目标位置的体表打印标记，结束步骤。Step 4: The intelligent processing mechanism controls the print head to move to the target position, and the print head prints a mark on the body surface at the target position, and the step ends. 2.根据权利要求1所述的一种麻醉进针定位装置的控制方法，其特征在于：所述步骤3.2中2. The control method of the anesthesia needle positioning device according to claim 1, characterized in that: in step 3.2 式(1)-式(3)中prF1Ti_list为压力数据集F1Ti的数据列表，prF2Ti_list为压力数据集F2Ti的数据列表，prF3Ti_list为压力数据集F3Ti的数据列表，prF1Ti_list.max()为压力数据集F1Ti的数据最大值，prF2Ti_list.max()为压力数据集F2Ti的数据最大值，prF3Ti_list.max()为压力数据集F3Ti的数据最大值，α为三组压力感应组件中弹簧的权重系数；压力感应组件包括立板、压力检测模块、压力传导模块以及弹性模块，压力检测模块和压力传导模块设置于立板，压力检测模块、弹性模块以及压力传导模块沿立板的长度方向分布，压力传导模块的受力通过弹性模块传导至压力检测模块，压力传导模块包括传导块和滚轮支撑架，传导块与传感器相对，传感器用于检测传导块传导的压力，滚轮支撑架下端设置有滚轮，弹性模块包括调节螺母、螺杆和弹簧,螺杆与传导块和滚轮支撑架连接，弹簧套设在螺杆，调节螺母设置于螺杆。In formula (1) to formula (3), prF1 Ti_list is the data list of the pressure data set F1 Ti , prF2 Ti_list is the data list of the pressure data set F2 Ti , prF3 Ti_list is the data list of the pressure data set F3 Ti , prF1 Ti_list.max () is the maximum value of the data of the pressure data set F1 Ti , prF2 Ti_list.max () is the maximum value of the data of the pressure data set F2 Ti , and prF3 Ti_list.max() is the maximum value of the data of the pressure data set F3 Ti . Ti is the maximum value of the data, α is the weight coefficient of the spring in the three groups of pressure sensing components; the pressure sensing component includes a vertical plate, a pressure detection module, a pressure conduction module and an elastic module, the pressure detection module and the pressure conduction module are arranged on the vertical plate, the pressure detection module, the elastic module and the pressure conduction module are distributed along the length direction of the vertical plate, the force of the pressure conduction module is transmitted to the pressure detection module through the elastic module, the pressure conduction module includes a conduction block and a roller support frame, the conduction block is opposite to the sensor, the sensor is used to detect the pressure conducted by the conduction block, a roller is arranged at the lower end of the roller support frame, the elastic module includes an adjusting nut, a screw and a spring, the screw is connected to the conduction block and the roller support frame, the spring is sleeved on the screw, and the adjusting nut is arranged on the screw. 3.根据权利要求2所述的一种麻醉进针定位装置的控制方法，其特征在于：所述步骤3.3中拟合3D图像的计算式为：3. The control method of the anesthesia needle positioning device according to claim 2, characterized in that: the calculation formula for fitting the 3D image in step 3.3 is: 式(4)中，N表示通道一、通道二、通道三，Y为通道一、通道二和通道三分布方向的位置距离，D表示滚轮的下压距离。In formula (4), N represents channel 1, channel 2, and channel 3, Y represents the position distance of channel 1, channel 2, and channel 3 in the distribution direction, and D represents the pressing distance of the roller. 4.根据权利要求1所述的一种麻醉进针定位装置的控制方法，其特征在于：所述步骤3.4中卡尔曼滤波过滤的计算式包括：4. The control method of the anesthesia needle positioning device according to claim 1, characterized in that: the calculation formula of the Kalman filter in step 3.4 includes: X(k，k-1)＝AX(k-1)+BU(k)....................(5)；X(k,k-1)=AX(k-1)+BU(k)............(5); 式(5)中，k表示当前时刻，k-1表示上一次时刻，X(k-1)表示系统上一状态最优结果，X(k，k-1)表示利用系统上一状态最优结果预测的系统当前状态的结果，A和B为系统参数，对于多模型系统，A和B设为矩阵，U(k)表示当前时刻对系统的控制量，A、B以及U(k)为设定值，U(k)可设为0，即没有控制量；In formula (5), k represents the current moment, k-1 represents the previous moment, X(k-1) represents the optimal result of the previous state of the system, X(k, k-1) represents the result of the current state of the system predicted by the optimal result of the previous state of the system, A and B are system parameters, for multi-model systems, A and B are set as matrices, U(k) represents the control amount of the system at the current moment, A, B and U(k) are set values, and U(k) can be set to 0, that is, there is no control amount; X(k，k-1)对应的协方差计算式：The covariance calculation formula corresponding to X(k, k-1) is: P(k，k-1)＝AP(k-1)AT+Q.......................(6)；P(k,k-1)=AP(k-1)A T +Q.............(6); 式(6)中，P(k，k-1)为X(k，k-1)对应的协方差，P(k-1)为X(k-1)对应的协方差，AT为A的转置矩阵，Q为系统过程的协方差，Q为设定值不随系统状态变化而变化；In formula (6), P(k, k-1) is the covariance corresponding to X(k, k-1), P(k-1) is the covariance corresponding to X(k-1), A T is the transposed matrix of A, Q is the covariance of the system process, and Q is the set value that does not change with the system state; 根据式(5)和式(6)，得到式(7)，According to formula (5) and formula (6), we get formula (7): X(k)＝X(k，k-1)+K(k)[Z(k)-HX(k，k-1)]....................(7)X(k)＝X(k,k-1)+K(k)[Z(k)-HX(k,k-1)].............(7) 式(7)中，X(k)为k时刻最优的估算值，K(k)为卡尔曼增益， 式(4)中H为测量系统的参数，对于多测量系统，H设为矩阵，HT为H的转置矩阵，R为系统测量的协方差，H、R为设定值；Z(k)为系统测量值，Z(k)为设定值；In formula (7), X(k) is the optimal estimated value at time k, K(k) is the Kalman gain, In formula (4), H is the parameter of the measurement system. For a multi-measurement system, H is set as a matrix, H T is the transposed matrix of H, R is the covariance of the system measurement, H and R are the set values; Z(k) is the system measurement value, and Z(k) is the set value; X(k)对应的协方差计算式：The covariance calculation formula corresponding to X(k) is: P(k)＝[I-K(k)H]P(k，k-1)........................(9)；P(k)=[I-K(k)H]P(k,k-1)........................(9); 式(9)中，P(k)为X(k)对应的协方差，其中I设为矩阵，I为设定值。In formula (9), P(k) is the covariance corresponding to X(k), where I is set as a matrix and I is a set value. 5.根据权利要求2所述的一种麻醉进针定位装置的控制方法，其特征在于：5. The control method of the anesthesia needle positioning device according to claim 2, characterized in that: 所述步骤3.2中α＝0.9。In the step 3.2, α=0.9. 6.根据权利要求1所述的一种麻醉进针定位装置的控制方法，其特征在于：6. The control method of the anesthesia needle positioning device according to claim 1, characterized in that: 所述压力感应机构还包括背板和横移组件，压力感应组件通过横移组件设置于背板，横移组件控制压力感应组件同步向内或向外运动。The pressure sensing mechanism also includes a back plate and a transverse movement component. The pressure sensing component is arranged on the back plate through the transverse movement component, and the transverse movement component controls the pressure sensing component to move synchronously inward or outward. 7.根据权利要求1所述的一种麻醉进针定位装置的控制方法，其特征在于：7. The control method of the anesthesia needle positioning device according to claim 1, characterized in that: 所述压力感应组件包括立板、压力检测模块、压力传导模块以及弹性模块，压力检测模块和压力传导模块设置于立板，压力检测模块包括传感器，立板设置传感器安装座，传感器设置于传感器安装座，传感器面向压力传导模块，传感器与智能处理机构连接。The pressure sensing component includes a vertical plate, a pressure detection module, a pressure conduction module and an elastic module. The pressure detection module and the pressure conduction module are arranged on the vertical plate. The pressure detection module includes a sensor. The vertical plate is provided with a sensor mounting seat. The sensor is arranged on the sensor mounting seat. The sensor faces the pressure conduction module. The sensor is connected to the intelligent processing mechanism.
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