CN115424700B

CN115424700B - Low temperature plasma system for treatment of common skin diseases

Info

Publication number: CN115424700B
Application number: CN202211335520.9A
Authority: CN
Inventors: 常华梅; 时贞平
Original assignee: Jiangsu Rongzheng Pharmaceutical Technology Co ltd
Current assignee: Jiangsu Rongzheng Pharmaceutical Technology Co ltd
Priority date: 2022-10-28
Filing date: 2022-10-28
Publication date: 2023-02-17
Anticipated expiration: 2042-10-28
Also published as: CN115424700A

Abstract

The embodiment of the specification provides a low-temperature plasma system for treating common skin diseases and an implementation method thereof, wherein the system comprises: a plasma generating module for generating plasma; the plasma emission module is used for emitting plasma; the moving module is used for carrying and moving the plasma emission module; the control module is used for: acquiring patient data of an object to be processed; determining data to be processed based on patient data of an object to be processed, wherein the data to be processed comprises a position to be processed; determining a moving path of the moving module based on the position to be processed; and controlling the moving module to move along the moving path so as to perform plasma processing on the position to be processed.

Description

Low temperature plasma system for treatment of common skin diseases

Technical Field

The present disclosure relates to the field of plasma technology, and more particularly, to a low temperature plasma system for treating common skin diseases and a method for implementing the same.

Background

The skin is contacted with the outside, so that bacteria, infectious fungi and the like are easy to breed to cause skin diseases, such as acne, chilblain, psoriasis, dermatitis and the like. At present, many studies show that the plasma can effectively sterilize and remove biological membranes, cause apoptosis to inhibit tumors, accelerate blood coagulation of wounds of living bodies to promote wound healing and the like, and can effectively treat skin diseases.

Based on the excellent performance of plasma gas in treating skin diseases, it is desirable to provide a low-temperature plasma system for treating common skin diseases and a realization method thereof, which can treat a treated part in a targeted manner with high efficiency by accurately controlling plasma jet.

Disclosure of Invention

One of the embodiments of the present specification provides a low temperature plasma system for common skin disease treatment, the system comprising: a plasma generating module for generating plasma; the plasma emission module is used for emitting plasma; the moving module is used for carrying and moving the plasma emission module; the control module is used for: acquiring patient data of an object to be processed; determining data to be processed based on patient data of an object to be processed, wherein the data to be processed comprises a position to be processed; determining a moving path of the moving module based on the position to be processed; and controlling the moving module to move along the moving path so as to perform plasma processing on the position to be processed.

One of the embodiments of the present specification provides a method for implementing a low-temperature plasma system, which is performed based on any one of the above low-temperature plasma systems for common skin disease treatment, and the method includes: acquiring patient data of an object to be processed; determining data to be processed based on patient data of an object to be processed, wherein the data to be processed comprises a position to be processed; determining a moving path of the moving module based on the position to be processed; and controlling the moving module to move along the moving path so as to perform plasma processing on the position to be processed.

One of the embodiments of the present specification provides a low temperature plasma device for common skin disease treatment, which includes a processor for executing the implementation method of the low temperature plasma system described in any one of the above.

One of the embodiments of the present specification provides a computer-readable storage medium storing computer instructions, and when the computer instructions in the storage medium are read by a computer, the computer executes the implementation method of the low-temperature plasma system as described in any one of the above.

Drawings

The present description will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and in these embodiments like numerals are used to indicate like structures, wherein:

FIG. 1 is a schematic diagram of an exemplary configuration of a low temperature plasma system for common dermatologic treatment, according to some embodiments of the present description;

FIG. 2 is a flow diagram of an exemplary implementation of a low temperature plasma system, according to some embodiments described herein;

FIG. 3 is an exemplary flow diagram illustrating the determination of data to be processed according to some embodiments of the present description;

FIG. 4 is an exemplary structural diagram of an image recognition model according to some embodiments of the present description;

FIG. 5 is an exemplary flow diagram illustrating determining a movement path of a movement module according to some embodiments of the present description.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "apparatus", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not to be taken in a singular sense, but rather are to be construed to include a plural sense unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

Fig. 1 is an exemplary schematic structural diagram of a low temperature plasma system for common skin condition treatment, according to some embodiments shown herein. The low temperature plasma system 100 according to the embodiments of the present disclosure will be described in detail below. It should be noted that the following examples are only for explaining the present specification, and do not constitute a limitation to the present specification. For example, the low temperature plasma system may also be used in sterilization, disinfection, therapy, and other application scenarios.

The plasma is a highly ionized gas cloud generated by the action of a strong electromagnetic field, mainly composed of various active substances such as electrons, ions, atoms, molecules, free radicals and the like, and is a new substance form except solid, liquid and gas. It will be appreciated that the total number of positive charges and the number of negative charges in the plasma are numerically equal. With the development of the plasma as a sterilization technology, the plasma can be deeply cleaned and efficiently sterilized, and meanwhile, the advantages of small skin irritation, convenient use and the like of the low-temperature plasma are rapidly developed in clinical medical treatment, so that the plasma can be widely applied to the field of treatment of biological epidermis.

As shown in fig. 1, a low temperature plasma system 100 for common skin disease treatment includes a plasma generation module 110, a plasma emission module 120, a movement module 130, and a control module 140.

The plasma generation module 110 may refer to a device for generating plasma, for example, the plasma generation module 110 may be a plasma generator, such as an arc plasma generator, a power frequency arc plasma generator, a high frequency induction plasma generator, a low pressure plasma generator, a combustion plasma generator, and the like.

In some embodiments, the plasma generation module 110 is used to generate a plasma. In some embodiments, the plasma generation module 110 may be connected with the plasma emission module 120 and deliver plasma to the treatment site of the object to be treated through the plasma emission module 120 to perform skin treatment on the treatment site. For details of the object to be processed and the position to be processed, reference may be made to the description of other contents of the present specification, for example, fig. 2.

In some embodiments, the plasma generation module 110 may be a low temperature plasma generator for generating a low temperature plasma. The low-temperature plasma has a temperature ranging from 4 ℃ to 200 ℃, can realize sterilization at a lower temperature such as body temperature, and is beneficial to operators and patients while being applied to the treatment of skin diseases.

The operating parameters of the plasma generation module 110 may include on and off, power, etc. of the plasma generation module 110.

The plasma emission module 120 may refer to a device that emits plasma generated by plasma to a position to be processed of an object to be processed. In some embodiments, the plasma emission module 120 may be used to emit plasma. In some embodiments, the plasma emission module 120 may include a delivery device (not shown in fig. 1) that delivers the plasma, and/or a spray device (not shown in fig. 1) that sprays the plasma to the location to be treated.

In some embodiments, the delivery device may refer to a device for delivering plasma. In some embodiments, the delivery device is connected to the plasma generation module 110 at one end and to the injection device at the other end. The delivery device may include a blower, air pump, or the like.

In some embodiments, the injection device may be used to inject plasma to a portion to be treated of an object to be treated. The spray device may be a spray head. In some embodiments, an injection device may be coupled to the delivery device for injecting the low temperature plasma gas. In some embodiments, the spraying device can be divided into different types such as large size, medium size and small size according to the volume of the spraying device so as to meet the requirements of different spraying areas. For example, for larger area ejection areas, a large size ejection head may be used. In some embodiments, the injection device may be configured to be movable, allowing fine adjustment of the position to be treated during treatment.

The operating parameters of the plasma emission module 120 may include operating parameters of the delivery device and/or the injection device. The working parameters of the conveying device can comprise the power and the opening and closing of the conveying device, and the working parameters of the spraying device can comprise the model, the operation intensity, the emission duration, the movement and the like of the spraying device. For details on the operating parameters of the plasma emission module 120, reference may be made to the description elsewhere in this specification, for example, the contents of the processing parameters of fig. 3. In some embodiments, multiple sprays are required at the treatment site based on the severity of the skin condition, and thus the spray device may be turned on and off multiple times during a treatment session. For details of the number of processes, reference may be made to the description of other contents of this specification, for example, fig. 4.

The moving module 130 may refer to a device that moves the plasma emission module 120. The moving module 130 may be provided with a pulley to facilitate movement.

In some embodiments, the moving module 130 is used to mount and move the plasma emitter module 120. In some embodiments, the movement module 130 may be mechanically coupled to the plasma emission module 120, for example, by pinning, screwing, and securing the plasma emission module 120 to the movement module. In some embodiments, the movement of the plasma emission module 120 may be driven by the movement of the moving module 130, such that the injection device of the plasma emission module 120 is aligned with the position to be processed.

The operating parameters of the movement module 130 may include a movement path, a movement speed, and the like. For details of the moving path, reference may be made to the description of the rest of the description, for example, fig. 2.

The control module 140 may control various modules in the low temperature plasma system 100 for common skin disease treatment. For example, the control module 140 may be used to control the plasma generation module 110, the plasma emission module 120, control the operating parameters of the movement module 130, and the like. For example, the control module 140 may control the power and on and off of the delivery device. For another example, the control module 140 may control a moving speed, a moving path, and the like of the moving module 130. The control module 140 may be implemented by a computing device having a processing chip.

In some embodiments, the control module 140 may be configured to: acquiring patient data of an object to be processed; determining data to be processed based on patient data of an object to be processed, wherein the data to be processed comprises a position to be processed; determining a moving path of the moving module based on the position to be processed; and controlling the moving module to move along the moving path so as to perform plasma processing on the position to be processed. Details regarding plasma processing may be found in the description elsewhere in this specification, e.g., fig. 2.

It should be appreciated that the low temperature plasma system 100 for common skin condition treatment shown in fig. 1 may be implemented in various ways.

It should be noted that the above description of the low temperature plasma system 100 for common skin treatment is merely for convenience of description and should not be construed as limiting the scope of the present disclosure to the illustrated embodiments. It will be appreciated by those skilled in the art that, having the benefit of the teachings of this apparatus, any combination of modules or configuration of subsystems with other modules may be used without departing from such teachings.

FIG. 2 is a flow diagram of an exemplary implementation of a low temperature plasma system, according to some embodiments described herein. In some embodiments, the process 200 may be performed by the control module 140. The process 200 may include the following steps:

step 210, obtaining patient data of the object to be processed.

The object to be treated may refer to an organism, e.g., a human, an animal, etc., having a skin disease.

The patient data may refer to data relating to skin diseases of the subject to be treated. In some embodiments, the patient data may include text data, patient image data captured by a camera, and the like. The text data may be text information input by a user. The patient data can be input by a user or acquired by connecting a camera.

In some embodiments, the patient data includes time of illness, last treatment data, type of skin condition, location, and the like. The types of skin diseases may include bacterial skin diseases (e.g., acne, whelk), allergic skin diseases (e.g., urticaria, angioedema, drug eruption, contact dermatitis, etc.), fungal skin diseases (e.g., tinea pedis, tinea corporis, tinea cruris, onychomycosis, etc.), viral skin diseases (e.g., verruca vulgaris, herpes simplex, herpes zoster, chicken pox, etc.), insect bite dermatitis (including papular urticaria, cryptoptera dermatitis, and scabies), solar skin diseases (solar skin diseases including solar dermatitis, sunburn, polymorphous solar eruption), and the like. The site of the skin disorder may be a body site where the skin disorder is located, for example, a face, a neck, four limbs, and the like.

Step 220, determining data to be processed based on the patient data of the object to be processed, wherein the data to be processed comprises a position to be processed.

The data to be processed may refer to data related to the location to be processed. In some embodiments, the pending data may include a pending location, a severity of the pending location, and the like. For details on the severity of the location to be processed, reference may be made to the description elsewhere in this specification, for example, fig. 4.

The location to be treated may be the specific location on the body where the skin disease wound is located. For example, the location to be treated may be the left ankle, the second joint of the middle finger of the left hand, etc. In some embodiments, the to-be-processed location may include a plurality.

In some embodiments, the control module may perform text parsing based on the text information to obtain the data to be processed. For example, the control module may obtain the user's pending data based on a text parsing of the last treatment data.

In some embodiments, the control module may perform image recognition processing on patient data of a subject to be processed to determine data to be processed. For details of image recognition, reference may be made to the description of other contents of this specification, for example, fig. 3.

Based on the position to be processed, a moving path of the moving module is determined 230.

The movement path may refer to a processing path of the movement module to a position to be processed when performing the treatment. In some embodiments, the moving path of the moving module may refer to a path along which the injection device of the plasma emission module performs injection. For example, for the position to be processed A, B, the injection path may be from the position to be processed a to the position to be processed B.

In some embodiments, the control module may determine a starting point of the moving path at a position to be processed closest to the current position of the plasma emission module, then use the position to be processed closest to the starting point as a second point of the moving path, then determine a position to be processed closest to the second point in the same direction (e.g., leftward or rightward) as a third point, sequentially label the positions to be processed, and determine the moving path according to the labels.

In some embodiments, the control module may determine a shortest path traversing each node with each to-be-processed position as a node; the movement path of the mobile module is determined based on the shortest path. For details on determining a moving path based on a shortest path, reference may be made to the description of the rest of this specification, for example, fig. 5.

And step 240, controlling the moving module to move along the moving path so as to perform plasma processing on the position to be processed.

In some embodiments, the control module 140 may generate a control instruction based on the movement path and then control the movement module to move according to the movement path based on the control instruction.

Plasma treatment may refer to a therapeutic process performed on a site to be treated. In some embodiments, the plasma treatment may be performed based on a process parameter. The process parameters may refer to operating parameters of the plasma emission module 120 when processing an object to be processed. For details of the processing parameters, reference may be made to the description elsewhere in this specification, for example, fig. 3. In some embodiments, the control module 140 may, after determining the processing parameter, process the location to be processed based on the processing parameter.

By automatically determining a treatment scheme based on the characteristics of a part to be treated in some embodiments of the present description, the plasma skin disease treatment system is intelligentized, and the treatment accuracy and efficiency are improved.

FIG. 3 is an exemplary flow diagram illustrating the determination of data to be processed according to some embodiments of the present description. In some embodiments, the process 300 may be performed by the control module 140. As shown in fig. 3, the process 300 may include the following steps:

step 310, performing image recognition processing based on the patient data of the object to be processed, and determining the position to be processed. The patient data may be image data. The related description of the data to be processed and the patient data can be referred to the related description of fig. 2.

In some embodiments, the control module 140 may perform image recognition processing on the patient data of the object to be processed based on the image recognition model to obtain the location to be processed. The relevant description of the image recognition model can be found in fig. 4 and its related description.

In some embodiments, the control module 140 may further perform image recognition processing on the patient data of the object to be processed based on a neural network algorithm, so as to obtain the data to be processed. Such as convolutional neural network algorithms.

For example, the affected area of a certain object to be processed is located on the face and hand of the object, and the image data of the corresponding part can be used as the affected data to perform image recognition processing, and the content of the obtained data to be processed may be "the position to be processed a is located on the face and the position to be processed B is located on the hand". Further description of the pending position may be found in relation to fig. 2.

And 320, determining a processing parameter corresponding to the position to be processed based on the position to be processed.

The process parameter may refer to an operation parameter, such as operation intensity, of the plasma emission module 120 when the object to be processed is processed. The operation intensity of the plasma emission module 120 may include a gas flow rate when the plasma emission module 120 emits the gas containing plasma, and an emission time period. For example, the content of a certain process parameter may be "gas flow is 0.1m ³ And/s, the transmission time is 30s ".

In some embodiments, the processing parameters may be data in the form of vectors. For example, the content of a certain process parameter is (0.15, 45), which means "the gas flow rate is 0.15m ³ And/s, the transmission time is 45s ".

In some embodiments, the processing parameters may be determined based on an image recognition model. The relevant description of the image recognition model can be found in fig. 4 and its associated description.

In some embodiments, a correspondence table between the positions to be processed and the processing parameters may be preset, and the processing parameters of the positions to be processed may be determined through the correspondence. For example, when the positions to be processed are located on the face, the hands, the legs, and the back, the processing parameters may be preset to (0.05, 20), (0.1, 30), (0.15, 40), and (0.15, 50), respectively. Then, based on the aforementioned data to be processed, "the position a to be processed is located on the face, and the position B to be processed is located on the hand," the obtained content of the processing parameters corresponding to the position to be processed may be "the processing parameter of the position a to be processed is (0.05, 20)," and the processing parameter of the position B to be processed is (0.1, 30) ".

In some embodiments of the present description, the relevant data of the position to be processed is determined through image recognition, so that the determination process is more intelligent, and time and labor cost are saved.

FIG. 4 is a diagram of an exemplary structure of an image recognition model according to some embodiments of the present description.

In some embodiments, the control module 140 may process patient data of the subject to be processed based on the image recognition model to determine the data to be processed. The image recognition model may be a machine learning model. Such as convolutional neural network models, etc.

As shown in fig. 4, the input of the image recognition model 420 may be patient data 410, the patient data 410 may be image data of a subject to be processed, and the output may be to-be-processed data 430.

In some embodiments, the to-be-processed data 430 may include a to-be-processed location 430-1 of the to-be-processed object. The treatment location 430-1 may include locations where a plurality of treatment sites are located. For example, the content of the to-be-processed position 430-1 may be "the to-be-processed position a is located at a hand, and the to-be-processed position B is located at a back.

In some embodiments, the pending data may also include the severity of each pending location. Severity may refer to the severity of the dermatological symptoms at the site to be treated. For example, severity can include very severe, more severe, general, and mild. In some embodiments, severity may also be characterized by a severity score, with higher scores representing a greater severity of dermatological symptoms at the treatment site. For example, if the severity score of the to-be-processed position a is 5 and the severity score of the to-be-processed position B is 3, the severity of the to-be-processed position a is higher than that of the to-be-processed position B.

In some embodiments, the severity in the data to be processed may also be output by the image recognition model. As shown in FIG. 4, the to-be-processed data 430 output by the image recognition model 420 may also include a severity 430-2 for each to-be-processed location. Illustratively, the content of the severity 430-2 of each to-be-processed location may be "the severity score of to-be-processed location a is 2, and the severity score of to-be-processed location B is 4.

In some embodiments of the present description, by introducing severity into the data to be processed, the adaptability of subsequent processing procedures determined based on the data to be processed to each location to be processed may be enhanced.

In some embodiments, the to-be-treated data may also include a patient type for each to-be-treated location.

The type of patient may refer to the type of skin disease of the site to be treated, and may be, for example, ringworm, sore, pustule, and the like.

In some embodiments, the patient type in the data to be processed may also be output by the image recognition model. As shown in FIG. 4, the to-be-processed data 430 output by the image recognition model 420 may also include a patient type 430-3 for each to-be-processed location. Illustratively, the content of the patient type 430-3 of each treatment location may be "the patient type of the treatment location a is ringworm, and the patient type of the treatment location B is sore.

In some embodiments, the image recognition model 420 may be trained from a plurality of labeled training samples. For example, a plurality of labeled training samples may be input into the initial image recognition model, a loss function may be constructed from the labels and the results of the initial image recognition model, and parameters of the initial image recognition model may be iteratively updated based on the loss function. And finishing model training when the loss function of the initial image recognition model meets a preset condition to obtain a trained image recognition model. The preset condition may be that the loss function converges, the number of iterations reaches a threshold, and the like.

In some embodiments, the training sample may include at least a plurality of historical patient data. The label can be the position to be processed corresponding to each patient data, the severity of each position to be processed and the patient type of each position to be processed. Wherein the labels may be retrieved based on manual labeling.

In some embodiments, the process parameters may also include a number of processes, which may refer to the number of times plasma emission module 120 processes the location to be processed. Specifically, the plasma emission module 120 counts the number of times of one process from reaching the position to be processed to leaving the position to be processed. The duration of each treatment may be equal.

In some embodiments, the control module 140 may determine the number of treatments based on the type of patient at the location to be treated. For example, the corresponding relationship between the patient type and the treatment frequency may be preset, and the treatment frequency may be determined based on the corresponding relationship.

In some embodiments of the present disclosure, the treatment times are determined according to the type of patient, and different treatment regimens are used for different types of patients, so that the treatment regimens are more targeted.

In some embodiments, the number of treatments may be related to severity. For example, the number of treatments may be positively correlated with the severity score, i.e., the greater the severity score of the location to be treated, the greater the number of treatments.

In some embodiments of the present disclosure, the treatment times are determined according to the severity of different regions, which makes the treatment protocol more flexible and more targeted.

FIG. 5 is an exemplary flow diagram illustrating determining a movement path of a movement module according to some embodiments of the present description. In some embodiments, the process 500 may be performed by the control module 140. As shown in fig. 5, the process 500 may include the following steps:

and step 510, determining the shortest path of the traversal node by taking the position to be processed as the node. The shortest path refers to a path having the smallest distance that the moving module 130 can complete the processing of all the positions to be processed moves between the positions to be processed. Completing the processing of all the positions to be processed may mean that the processing of each position to be processed reaches the processing number.

In some embodiments, the method of determining the shortest path may comprise the steps of:

if the nodes are shared

A is prepared from

Represents a starting point node, to

Represents the first

A remaining node, then

Can form a node set

Then there is

. Wherein the starting point node

The selection can be random or can be preset manually. The value of the path weight between every two nodes can be preset. For example, the path weight may be preset based on the spatial distance between the positions to be processed, and further, the path weight may be preset to have a positive correlation with the spatial distance between the positions to be processed. The path weight may characterize a degree of priority in moving from the current node to the next node. Specifically, the smaller the path weight corresponding to a node is, the higher the priority to move from the current node to the node is.

Construct a

Matrix of orders

For storing the division start point node

Path weights between every two nodes of other nodes. Illustratively, the elements of the second row and the third column of the matrix

Representing a slave node

To a node

Has a value of 5.

A recursive process is performed. The recursive process may include: to be provided with

As a starting point, from

Optionally one node as a slave

The next node to move to, for example,

(ii) a I.e. represent from

Move to

Then, the next step is

As a starting point, from

Remaining nodes (except

Other nodes) as the next node to move to, e.g.,

(ii) a And so on until all nodes are reached once; returning from the last reached node

(ii) a And counting the sum of the path weights among all the nodes of the path to finish path planning.

Repeating the above steps, and executing again

The order of selecting the nodes in the path planning method may not be completely the same as that of all the planned paths until all possible path planning results are counted. Illustratively, the recursion process may use a recursion formula as shown in equation (1) below:

wherein the content of the first and second substances,

represents from

Departure access

All nodes in the shortest path back to the starting pointThe sum of the path weights;

represents

In removing

Followed by an empty set, corresponding

Represents from

To

Path weights of, i.e. from

The starting point can be returned to without passing any other point

So that the sum of the path weights of the shortest paths is

And

inter-path weights;

represents

In removing

Not empty set later, corresponding

Represents from

To

The weight of the path of (a) is,

represents from

Departure access

Is except for

、

And

go back to after all nodes are left

The sum of all path weights in the shortest path of (c).

Illustratively, assume that there are 4 nodes corresponding to the positions to be processed, where the starting point node is

，

Is a

，

，

Then the sum of the path weights to be computed can be expressed as

Then, it is

The calculation can be made by the following equation (2):

wherein the content of the first and second substances,

and can be based on the above formula

Further recursion is performed until the sum of the path weights for all possible paths is computed once.

Finally, the path with the smallest sum of the path weights may be taken as the shortest path.

Step 520, determining a moving path of the mobile module based on the shortest path.

In some embodiments, the shortest path may be determined as the movement path of the movement module 130.

In some embodiments, when determining the shortest path, the path weight from the current pending location to the next pending location may be related to the severity of the next pending location.

In some embodiments, the path weight may be negatively correlated to severity, i.e., the greater the severity score, the smaller the corresponding path weight.

In some embodiments of the present description, the greater the severity of the position to be treated, the higher the priority of treatment, so that the degree of urgent treatment caused by the severity is fully considered by the treatment scheme, and the treatment path of the treatment scheme is optimized.

In some embodiments, a pending location may be considered a plurality of pending locations if it requires multiple processes. For example, if the number of times that the to-be-processed position D needs to be processed is 3, the to-be-processed position D may be regarded as the to-be-processed position D ₁ A position to be processed D ₂ And a position D to be processed ₃ . Position to be processed D ₁ 、D ₂ And D ₃ Overlap of the actual spatial positions of D ₁ 、D ₂ And D ₃ The path weights to other pending positions are equal, but D ₁ 、D ₂ And D ₃ The inter-path weight may be set to a value much larger than the maximum value of the path weights to other positions to be processed, for example, set to 1000 times the maximum value of the path weights to other positions to be processed.

In some embodiments of the present description, positions that need to be processed multiple times are regarded as multiple positions to be processed, so that an effect of discontinuously processing the same position to be processed can be achieved, route planning for positions that need to be processed multiple times can be completed in one-time dynamic planning, and planning efficiency is improved.

In some embodiments, whether the node to be processed requires multiple processes may be determined based on the number of processes of the node to be processed. The related description of the processing times of the nodes to be processed can be referred to fig. 4 and the related description thereof.

In some embodiments of the present description, the route to be processed is planned through the number of times of processing of the node to be processed, so that the adaptability of the planned route to the processing process can be enhanced.

In some embodiments of the present description, energy consumption can be saved while improving treatment efficiency by determining the shortest path to execute a treatment plan.

It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such alterations, modifications, and improvements are intended to be suggested in this specification, and are intended to be within the spirit and scope of the exemplary embodiments of this specification.

Also, the description uses specific words to describe embodiments of the description. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Additionally, the order in which the elements and sequences of the process are recited in the specification, the use of alphanumeric characters, or other designations, is not intended to limit the order in which the processes and methods of the specification occur, unless otherwise specified in the claims. While various presently contemplated embodiments have been discussed in the foregoing disclosure by way of example, it should be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the foregoing description of embodiments of the specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters set forth in the specification and claims are approximations that may vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document does not conform to or conflict with the contents of the present specification, it is to be understood that the application history document, as used herein in the present specification or appended claims, is intended to define the broadest scope of the present specification (whether presently or later in the specification) rather than the broadest scope of the present specification. It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of this specification shall control if they are inconsistent or contrary to the descriptions and/or uses of terms in this specification.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. A cryogenic plasma system for common skin condition treatment, the system comprising:

a plasma generating module for generating plasma;

the plasma emission module is used for emitting the plasma;

the moving module is used for carrying and moving the plasma emission module;

the control module is used for:

acquiring patient data of an object to be processed;

determining data to be processed based on the patient data of the object to be processed, wherein the data to be processed comprises a position to be processed, a patient type of the position to be processed, processing parameters corresponding to the position to be processed and the severity of the position to be processed, the processing parameters comprise processing times, the severity refers to the severity of skin disease symptoms of the position to be processed, and the severity is obtained based on an image recognition model; wherein, determining the processing parameters corresponding to the position to be processed comprises:

performing image recognition processing based on the patient data of the object to be processed, and determining the position to be processed; the patient data is image data;

determining the treatment parameters corresponding to the position to be treated based on the patient type of the position to be treated;

determining a moving path of the moving module based on the position to be processed;

controlling the moving module to move along the moving path so as to perform plasma processing on the position to be processed; wherein the determining a movement path of the mobile module based on the to-be-processed position comprises:

determining a shortest path traversing the nodes by taking the positions to be processed as nodes, wherein the shortest path comprises a path with the minimum path weight for the mobile module which completes the processing of all the positions to be processed to move among the positions to be processed, the path weight is preset to be positively correlated with the spatial distance among the positions to be processed, the path weight represents the priority degree when the mobile module moves from the current node to the next node, the completion of the processing of all the positions to be processed means that the processing of each position to be processed reaches the processing times, and the path weight is correlated with the severity degree; wherein, in response to the position to be processed requiring multiple processing, regarding it as a plurality of positions to be processed, and whether the position to be processed requires multiple processing is determined based on the number of processing times of the position to be processed;

determining a movement path of the mobile module based on the shortest path.