CN117257630A - Shock wave treatment equipment and method based on real-time monitoring and dynamic feedback - Google Patents

Shock wave treatment equipment and method based on real-time monitoring and dynamic feedback Download PDF

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Publication number
CN117257630A
CN117257630A CN202311222421.4A CN202311222421A CN117257630A CN 117257630 A CN117257630 A CN 117257630A CN 202311222421 A CN202311222421 A CN 202311222421A CN 117257630 A CN117257630 A CN 117257630A
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shock wave
output
result
preprocessing
module
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张丽
瓮长水
蒋天裕
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Second Medical Center of PLA General Hospital
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Second Medical Center of PLA General Hospital
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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61HPHYSICAL THERAPY APPARATUS, e.g. DEVICES FOR LOCATING OR STIMULATING REFLEX POINTS IN THE BODY; ARTIFICIAL RESPIRATION; MASSAGE; BATHING DEVICES FOR SPECIAL THERAPEUTIC OR HYGIENIC PURPOSES OR SPECIFIC PARTS OF THE BODY
    • A61H23/00Percussion or vibration massage, e.g. using supersonic vibration; Suction-vibration massage; Massage with moving diaphragms
    • A61H23/008Percussion or vibration massage, e.g. using supersonic vibration; Suction-vibration massage; Massage with moving diaphragms using shock waves

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  • Epidemiology (AREA)
  • Pain & Pain Management (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Rehabilitation Therapy (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
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Abstract

The invention discloses shock wave treatment equipment and a shock wave treatment method based on real-time monitoring and dynamic feedback, which relate to the technical field of medical shock wave treatment and comprise the following steps: the equipment host is used for acquiring and analyzing the treatment scheme to obtain a corresponding shock wave application path and a shock wave output instruction; the shock wave generation system is connected with the equipment host and is used for realizing energy output of shock waves according to the shock wave output instruction; the mechanical arm is connected with the equipment host and the shock wave generation system and is used for controlling the movement of a controller in the shock wave generation system according to the shock wave application path; the invention can realize quantitative monitoring and regulation of relevant parameters of the output of the shock wave.

Description

Shock wave treatment equipment and method based on real-time monitoring and dynamic feedback
Technical Field
The invention relates to the technical field of medical shock wave treatment, in particular to shock wave treatment equipment and a shock wave treatment method based on real-time monitoring and dynamic feedback.
Background
At present, the external shock wave therapy (Extracorporeal Shock Wave Therapy, ESWT) is a novel method for accurately treating diseases by using mechanical energy in the form of Shock Wave (SW), and has the advantages of safety, high efficiency, accuracy, easy acceptance by patients and the like. In recent years, shock wave therapy has been developed rapidly, and in the field of treatment of various diseases, in vitro shock wave therapy has shown good application prospects.
However, the key to success of the shock wave treatment is that proper and stable output energy is accurately acted on the target part, and the actual output energy and the theoretical output energy of the existing shock wave treatment equipment are inconsistent due to the errors of the equipment, the influences of factors such as air resistance, tissue characteristics, texture and the like, and the actual output energy cannot be fed back and regulated in time in the treatment process, so that accurate regulation and control of the shock wave dosage cannot be achieved; in addition, in the existing shock wave treatment process, workers are required to hold the shock wave treatment handle in the whole process, continuously move, adjust the direction and the force, the time is tens of minutes, and the time is 1-2 hours, so that the working intensity and the burden are greatly increased.
Therefore, how to provide a shock wave treatment device capable of solving the above problems is a technical problem that needs to be solved in the art.
Disclosure of Invention
In view of the above, the invention provides a shock wave treatment device and a shock wave treatment method based on real-time monitoring and dynamic feedback, which can realize quantitative monitoring and regulation of relevant parameters of shock wave energy output, obtain shock wave actual output energy by combining a deep learning method and feed back the shock wave actual output energy to shock wave treatment equipment, can regulate and control shock wave output dosage in real time, further realize accurate energy output of the shock wave equipment, and can solve the problems of limited treatment range and large workload of staff in the existing shock wave treatment process, improve the working efficiency, lighten the working intensity of the staff and make the shock wave treatment process more intelligent, accurate and convenient.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a shock wave therapy apparatus based on real-time monitoring and dynamic feedback, comprising:
the equipment host is used for acquiring and analyzing the treatment scheme to obtain a corresponding shock wave application path and a shock wave output instruction;
the shock wave generation system is connected with the equipment host and is used for completing energy output of shock waves according to the shock wave output instruction;
the mechanical arm is a flexible safe mechanical arm, the surface of the mechanical arm is wrapped with electronic skin, meanwhile, a moment sensor can be arranged at the tail end of the mechanical arm to prevent a controller of a shock wave generating system such as a shock wave output handle from causing damage to a human body due to overlarge force application, and the mechanical arm is connected with the equipment host and the shock wave generating system and is used for controlling the movement of the controller in the shock wave generating system according to the shock wave application path;
the first detection system is connected with the shock wave generation system and is used for detecting output shock wave signals of the shock wave generation system in real time;
the second detection system is used for detecting the effective shock wave signals of the treatment area in real time;
the input end of the processing system is connected with the first detection system and the second detection system, the output end of the processing system is connected with the equipment host, and the processing system is used for processing according to the difference value between the output shock wave signal and the effective shock wave signal intensity and feeding back the processing result to the equipment host so as to update the shock wave applying path and the shock wave output instruction.
Preferably, the device host includes:
the planning system is used for acquiring and analyzing the treatment scheme to obtain a corresponding shock wave application path and a shock wave output instruction, wherein the shock wave output instruction comprises the theoretical output energy of the shock wave and the theoretical impact times;
the control system is connected with the planning system and the mechanical arm and is used for controlling the mechanical arm to move according to the shock wave applying path and simultaneously receiving and sending the shock wave output instruction.
Preferably, the shock wave generating system includes:
the shock wave generation module is connected with the control system and used for generating required shock waves according to the shock wave output instruction;
and the controller is connected with the shock wave generation module and is used for completing shock wave energy output according to the required shock wave until the theoretical shock times are reached.
Preferably, the first detection system includes:
the output shock wave signal detection module is connected with the controller and used for detecting the output shock wave signal of the controller in real time;
the first preprocessing module is connected with the output shock wave signal detection module and used for preprocessing and converting the output shock wave signal and sending a first preprocessing result to the processing system as the first preprocessing result.
Preferably, the second detection system includes:
the effective shock wave signal detection module is used for detecting effective shock wave signals of the treatment area in real time;
the input end of the second preprocessing module is connected with the effective shock wave signal detection module, the output end of the second preprocessing module is connected with the processing system and is used for preprocessing and converting the effective shock wave signal and sending a second preprocessing result to the processing system as a second preprocessing result.
Preferably, the processing system comprises:
the receiving module is connected with the first preprocessing module and the second preprocessing module and is used for receiving the first preprocessing result and the second preprocessing result;
the feedback module is connected with the receiving module and the controller and is used for comparing the first pretreatment result with the second pretreatment result and taking the difference value of the first pretreatment result and the second pretreatment result as a first treatment result, and carrying out energy feedback on the controller according to the first treatment result;
the fitting module is connected with the feedback module, and prestores a corresponding relation of output shock wave signals and a preset difference threshold value, and is used for updating the output shock wave signals according to the corresponding relation when the first processing result exceeds the preset difference threshold value;
the calibration module is connected with the fitting module and the control system and is used for constructing and training a long-short-time memory neural network, inputting the effective shock wave signals into the long-short-time memory neural network for processing, calibrating the output shock wave signals according to the processing result of the long-short-time memory neural network, and finally sending the calibration result to the control system to obtain the latest shock wave output instruction and the shock wave implementation path.
The invention also provides a method for realizing the shock wave treatment equipment based on real-time monitoring and dynamic feedback, which comprises the following steps:
s1: obtaining and analyzing a treatment scheme through a planning system to obtain a corresponding shock wave application path and a shock wave output instruction, wherein the shock wave output instruction comprises the theoretical output energy of the shock wave and the theoretical impact times;
s2: the control system receives the shock wave applying path and the shock wave output instruction, controls the mechanical arm to move according to the shock wave applying path, and controls the controller of the shock wave generating system to output required shock waves according to the shock wave output instruction until the theoretical shock times are reached;
in the process of outputting needed shock waves, the output shock wave signals of the controller are detected in real time through the output shock wave signal detection module, and meanwhile, the effective shock wave signals of the treatment area are detected in real time through the effective shock wave signal detection module which is attached to the body surface of the treatment area;
s3: preprocessing and converting the output shock wave signal and the effective shock wave signal to obtain a corresponding first preprocessing result and a corresponding second preprocessing result, and sending the first preprocessing result and the second preprocessing result to a processing system;
s4: and (3) processing the first pretreatment result and the second pretreatment result obtained in the step (S3) through the processing system, updating the shock wave output instruction and the shock wave application path, and controlling the output of shock waves.
Preferably, the specific process of S4 further includes:
s41: receiving a first preprocessing result and a second preprocessing result through a receiving module;
s42: comparing the first preprocessing result and the second preprocessing result through a feedback module, taking the difference value of the first preprocessing result and the second preprocessing result as a first processing result, and carrying out energy feedback on the controller according to the first processing result;
s43: the fitting module is pre-stored with a corresponding relation of output shock wave signal change, and when the first processing result exceeds a preset difference threshold value, the output shock wave signal is updated according to the corresponding relation;
s44: constructing and training a long-short-time memory neural network, inputting the effective shock wave signal into the long-short-time memory neural network for processing, outputting a calibration result, and sending the calibration result to a control system;
s45: and (3) generating a new shock wave output instruction and a new shock wave application path according to the calibration result obtained in the step (S44) by the control system, and controlling the energy output of the shock wave generation system and the movement of the mechanical arm.
Preferably, the specific process of S44 includes:
s441: constructing a long-short-time memory neural network, acquiring a historical data set, dividing the historical data set into a training set and a testing set, training the long-short-time memory neural network by using the training set, testing the long-short-time memory neural network by using the testing set, verifying model prediction precision by using a root mean square error method, and finishing training when the precision meets the requirement;
s442: and carrying out normalization processing on the effective shock wave signals, and inputting the effective shock wave signals into the long-short-time memory neural network processing obtained in the step S441 to obtain corresponding calibration results.
Preferably, the preprocessing and converting in S3 includes: outlier rejection, mean filtering, and analog-to-digital conversion.
Compared with the prior art, the invention discloses shock wave treatment equipment and a shock wave treatment method based on real-time monitoring and dynamic feedback, which adopt a novel flexible film type mechanical energy signal sensor (including but not limited to a polyvinylidene fluoride film (polyvinylidene difluoride, PVDF), a single-sided multistage sinusoidal magnetization film and the like) to realize quantitative monitoring and regulation of shock wave mechanical signals and energy density on the basis of conventional medical shock wave equipment, obtain shock wave pressure field and dynamic distribution characteristics by combining a deep learning algorithm, feed back the shock wave mechanical signals and the energy density to the shock wave treatment equipment to regulate and control shock wave output dose in real time, further realize accurate energy output of the shock wave equipment, solve the problems of limited treatment range and large workload of staff in the conventional shock wave treatment process, improve the working efficiency, reduce the working strength of the staff, and enable the shock wave treatment process to be more intelligent, accurate and simple.
The invention can also drive the movement of the shock wave treatment handle by controlling the movement of the mechanical arm, and can liberate the hands of a doctor, so that the doctor can directly finish the adjustment of the shock wave treatment scheme and the output dosage through the control panel.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic block diagram of a shock wave treatment device based on real-time monitoring and dynamic feedback according to the present invention;
FIG. 2 is a schematic block diagram of a first detection system according to an embodiment of the present invention;
FIG. 3 is a schematic block diagram of a second detection system according to an embodiment of the present invention;
FIG. 4 is a schematic block diagram of a processing system according to the present invention;
FIG. 5 is an overall flow chart of a method of implementing a shock wave therapy device in accordance with the present invention;
FIG. 6 is a flowchart of step S4 provided by the present invention;
fig. 7 is a flowchart of the operation of step S44 provided in the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, an embodiment of the present invention provides a shock wave treatment apparatus based on real-time monitoring and dynamic feedback, including:
the equipment host 1 is used for acquiring and analyzing a treatment scheme to obtain a corresponding shock wave application path and a shock wave output instruction, wherein the specific process of acquiring and analyzing the treatment scheme can be obtained by acquiring and processing medical information and health files of a patient, and can also be realized by planning the treatment scheme according to relevant experience summarized by machine learning;
the shock wave generation system 2 is connected with the equipment host 1 and is used for completing energy output of shock waves according to a shock wave output instruction;
the mechanical arm 3 is a flexible mechanical arm, can also be a multi-degree-of-freedom flexible cooperative mechanical arm, is composed of a plurality of joints, has a plurality of degrees of freedom, wraps the electronic skin on the surface, and can automatically avoid barriers and detect safety force application; the torque sensor is arranged at the tail end of the mechanical arm, and meanwhile, the three-dimensional torque sensor can be arranged at the tail end of the mechanical arm 3, so that the tail end torque feedback can be performed, and the higher control accuracy and the better safety protection effect are achieved; the mechanical arm 3 is connected with the equipment host 1 and a controller 22 in the shock wave generation system 2 and is used for controlling the movement of the shock wave generation system 2 according to a shock wave application path;
the first detection system 4 is connected with the shock wave generation system 2 and is used for detecting output shock wave signals of the shock wave generation system 2 in real time;
a second detection system 5 for detecting in real time the effective shock wave signal of the treatment area;
the processing system 6, the input end of the processing system 6 is connected with the first detecting system 4 and the second detecting system 5, the output end is connected with the equipment host 1, and the processing system is used for processing according to the difference value between the output shock wave signal and the effective shock wave signal, and feeding back the processing result to the equipment host 1 to update the shock wave applying path and the shock wave output instruction.
In a specific embodiment, the device host 1 includes:
the planning system 11 is configured to acquire and analyze a treatment plan, and obtain a corresponding shock wave application path and a shock wave output instruction, where the shock wave output instruction includes a theoretical output energy of the shock wave and a theoretical number of times of shock;
the control system 12, the control system 12 is connected with the planning system 11 and the mechanical arm 3, and is used for controlling the mechanical arm 3 to move according to the shock wave applying path and simultaneously receiving and sending shock wave output instructions.
In a specific embodiment, the shock wave generating system 2 comprises:
the shock wave generation module 21, the shock wave generation module 21 is connected with the control system 12, and is used for generating required shock waves according to the shock wave output instruction;
controller 22. Controller 22 includes but is not limited to various forms of shockwave output devices including output handles, controller 22 being coupled to shockwave generating module 21 for completing shockwave energy output according to a desired shockwave until a theoretical number of shocks is reached.
In a specific embodiment, the robotic arm 3 is mounted on a stand or directly on a base;
wherein the bracket can be internally provided with a device host 1 and a shock wave generation system 2; or the mechanical arm is directly arranged on the base, and the equipment host 1 and the shock wave generation system 2 are external equipment and are electrically connected with a controller on the mechanical arm.
Referring to fig. 2, in a specific embodiment, the first detection system 4 includes:
the output shock wave signal detection module 41, the output shock wave signal detection module 41 is connected with the controller 22, and is used for detecting the output shock wave signal of the controller 22 in real time;
the first preprocessing module 42, where the first preprocessing module 42 is connected to the output shock wave signal detection module 41, is configured to perform preprocessing and conversion on the output shock wave signal, and send the first preprocessing result to the processing system 6 as the first preprocessing result.
Specifically, the output shock wave signal may include the actual output energy and the actual impact frequency, that is, the output shock wave signal detection module 41 is configured to detect the actual output energy and the actual impact frequency, and may be implemented by using a laser sensor, where the laser sensor generally outputs a corresponding analog quantity and has a larger data collection quantity, so that the processes of preprocessing and converting may sequentially perform outlier rejection, average filtering and analog-to-digital conversion.
Referring to fig. 3, in a specific embodiment, the second detection system 5 includes:
an effective shock wave signal detection module 51 for detecting an effective shock wave signal of the treatment region in real time;
the input end of the second preprocessing module 52 is connected with the effective shock wave signal detection module 51, and the output end of the second preprocessing module 52 is connected with the processing system 6 and is used for preprocessing and converting the effective shock wave signal and sending the second preprocessing result to the processing system 6 as a second preprocessing result.
Specifically, the effective shock wave signal includes local mechanical parameters, position parameters and penetration depth of the treatment area, and the treatment area may include relevant human tissues such as skin, muscle, bone, etc. in the treatment area, and the effective shock wave signal detection module 51 includes a mechanical signal detection unit 511, a position detection unit 512 and a penetration depth detection unit 513, which are used for detecting the local mechanical parameters, the position parameters and the penetration depth in real time.
In a specific embodiment, the mechanical signal detection unit 511 and the penetration depth detection unit 513 may use any one or more of PVDF charge type pressure sensor and capacitive flexible electronic pressure sensor for detection, and the preprocessing and conversion may also sequentially perform outlier rejection, average filtering and analog-to-digital conversion.
In a specific embodiment, the mechanical parameters of the local tissue may include: any one or any several of hardness, elasticity and thickness.
Referring to fig. 4, in one particular embodiment, the processing system 6 includes:
the receiving module 61 is connected with the first preprocessing module 52 and the second preprocessing module 42, and is used for receiving the first preprocessing result and the second preprocessing result;
the feedback module 62, the feedback module 62 is connected with the receiving module 61 and the controller 22, and is used for comparing the first preprocessing result and the second preprocessing result, taking the difference value of the first preprocessing result and the second preprocessing result as the first processing result, and performing energy feedback on the controller 22 according to the first processing result;
the fitting module 63, the fitting module 63 is connected with the feedback module 62, and the fitting module 63 stores a corresponding relation of the output shock wave signal and a preset difference threshold in advance, and is used for updating the output shock wave signal according to the corresponding relation when the first processing result exceeds the preset difference threshold;
the calibration module 64 is connected with the fitting module 63 and the control system 12, and is used for constructing and training a long-short-time memory neural network, inputting an effective shock wave signal into the long-short-time memory neural network for processing, calibrating an output shock wave signal according to the processing result of the long-short-time memory neural network, and finally transmitting the calibration result to the control system 12 to obtain the latest shock wave output instruction and the latest shock wave implementation path.
Specifically, the feedback module 62 may perform energy feedback according to the comparison result, and perform pressurization processing when the energy feedback is smaller than the comparison result, and perform depressurization processing when the energy feedback is equal to the comparison result.
Referring to fig. 5, the embodiment of the invention further provides a method for implementing the shock wave treatment equipment based on real-time monitoring and dynamic feedback, which comprises the following steps:
s1: obtaining and analyzing a treatment scheme through a planning system 11 to obtain a corresponding shock wave application path and a shock wave output instruction, wherein the shock wave output instruction comprises the theoretical output energy of the shock wave and the theoretical impact times;
s2: the control system 12 receives the shock wave applying path and the shock wave output command, controls the mechanical arm 3 to move according to the shock wave applying path, and simultaneously controls the controller 22 of the shock wave generating system 2 to output required shock waves according to the shock wave output command until the theoretical shock times are reached;
in the process of outputting the needed shock wave, the output shock wave signal of the controller 22 is detected in real time through the output shock wave signal detection module 41, and meanwhile, the effective shock wave signal of the treatment area is detected in real time through the effective shock wave signal detection module 51 which is applied to the body surface of the treatment area;
s3: preprocessing and converting the output shock wave signal and the effective shock wave signal to obtain a corresponding first preprocessing result and a corresponding second preprocessing result, and sending the first preprocessing result and the second preprocessing result to a processing system 6;
s4: the processing system 6 processes the first pretreatment result and the second pretreatment result obtained in the step S3, updates the shock wave output command and the shock wave application path, and controls the output of the shock wave.
Specifically, the specific expression used to implement step S2 may be:
equation (1) describes the pressure distribution in tissue under a shock wave pressure load of a certain frequency, where p ω () For pressure distribution at different depth positions in tissue r p Is radius, u ω The displacement value of the shock wave output piston is ω, the shock wave output piston frequency is ω, the tissue density is c s For the propagation velocity of the shock wave in the tissue, k=ω/c is the wave number, r is the tissue depth, θ is the normal angle to the shock wave output piston, J1 () is the bessel function, and the corresponding pressure value P of the shock wave output is obtained by equation (1).
Equation (2) describes fluence (Energy Flux Density, EFD) within the tissue, where P is the pressure value at different depth locations in the tissue. For a location, EFD describes the energy flux density (J/mm) at that location 2 ) Its value is accumulated from the pressure value P at that location to produce a square integral term.
Referring to fig. 6, in a specific embodiment, the specific process of S4 further includes:
s41: receiving the first pre-processing result and the second pre-processing result through the receiving module 61;
s42: comparing the first preprocessing result and the second preprocessing result through the feedback module 62, taking the difference value of the first preprocessing result and the second preprocessing result as a first processing result, and carrying out energy feedback on the controller 22 according to the first processing result;
s43: the calibration module 64 stores the corresponding relation of the output shock wave signal variation in advance, and updates the output shock wave signal according to the corresponding relation when the first processing result exceeds the preset difference threshold;
s44: constructing and training a long-short-time memory neural network, inputting an effective shock wave signal into the long-short-time memory neural network for processing, outputting a calibration result, and sending the calibration result to the control system 12;
s45: the control system 12 generates a new shock wave output command and a new shock wave application path based on the calibration result obtained in S44, and controls the energy output of the shock wave generation system 2 and the movement of the robot arm 3.
Referring to fig. 7, in a specific embodiment, the specific process of S44 includes:
s441: constructing a long-short-time memory neural network, acquiring a historical data set, dividing the historical data set into a training set and a test set, training the long-short-time memory neural network by using the training set, testing the long-short-time memory neural network by using the test set, verifying model prediction precision by using a root mean square error method, and finishing training when the precision meets the requirement;
s442: and carrying out normalization processing on the effective shock wave signals, and inputting the effective shock wave signals into the long-short-time memory neural network processing obtained in the step S441 to obtain corresponding calibration results.
Specifically, the basic idea of long-short-term memory neural network (LSTM neural network) is to design a neuron controlled by a plurality of control gates (i.e. a memory module) so as to overcome the phenomenon of gradient disappearance in the recurrent neural network, and the recurrent neural network is composed of three layers, namely an input layer, a hidden layer and an output layer.
In a specific embodiment, the preprocessing and converting in S3 includes: outlier rejection, mean filtering, and analog-to-digital conversion.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. Shock wave treatment equipment based on real-time monitoring and dynamic feedback, characterized by comprising:
the equipment host (1) is used for acquiring and analyzing the treatment scheme to obtain a corresponding shock wave application path and a shock wave output instruction;
the shock wave generation system (2) is connected with the equipment host (1) and is used for completing energy output of shock waves according to the shock wave output instruction;
the mechanical arm (3), the mechanical arm (3) is a flexible mechanical arm, and the mechanical arm (3) is connected with the equipment host (1) and the shock wave generation system (2) and is used for controlling the movement of the shock wave generation system (2) according to the shock wave application path;
the first detection system (4) is connected with the shock wave generation system (2) and is used for detecting output shock wave signals of the shock wave generation system (2) in real time;
a second detection system (5) for detecting in real time the effective shock wave signal of the treatment area;
the input end of the processing system (6) is connected with the first detection system (4) and the second detection system (5), the output end of the processing system (6) is connected with the equipment host (1) and is used for processing according to the difference value between the output shock wave signal and the effective shock wave signal, and the processing result is fed back to the equipment host (1) so as to update the shock wave applying path and the shock wave output instruction.
2. A shock wave treatment device based on real time monitoring and dynamic feedback according to claim 1, characterized in that the device host (1) comprises:
the planning system (11) is used for acquiring and analyzing the treatment scheme to obtain a corresponding shock wave application path and a shock wave output instruction, wherein the shock wave output instruction comprises the theoretical output energy of the shock wave and the theoretical impact times;
the control system (12) is connected with the planning system (11) and the mechanical arm (3) and is used for controlling the mechanical arm (3) to reach a designated position according to the shock wave application path and simultaneously receiving and sending the shock wave output instruction.
3. A shock wave treatment apparatus based on real time monitoring and dynamic feedback according to claim 2, characterized in that the shock wave generation system (2) comprises:
the shock wave generation module (21), the said shock wave generation module (21) connects with said control system (12), is used for producing the required shock wave according to the said shock wave output command;
and the controller (22) is connected with the shock wave generation module (21) and is used for completing shock wave energy output according to required shock waves until the theoretical number of shock times is reached.
4. A shock wave treatment apparatus based on real time monitoring and dynamic feedback according to claim 3, characterized in that the first detection system (4) comprises:
the output shock wave signal detection module (41), the output shock wave signal detection module (41) is connected with the controller (22) and is used for detecting the output shock wave signal of the controller (22) in real time;
the first preprocessing module (42) is connected with the output shock wave signal detection module (41) and is used for preprocessing and converting the output shock wave signal and sending a first preprocessing result to the processing system (6) as the first preprocessing result.
5. A shock wave treatment device based on real-time monitoring and dynamic feedback according to claim 4, characterized in that the second detection system (5) comprises:
the effective shock wave signal detection module (51), the effective shock wave signal detection module (51) is applied to the body surface of the treatment area in a non-invasive manner and is used for detecting the effective shock wave signal of the treatment area in real time;
and the input end of the second preprocessing module (52) is connected with the effective shock wave signal detection module (51), and the output end of the second preprocessing module (52) is connected with the processing system (6) and is used for preprocessing and converting the effective shock wave signal and sending a second preprocessing result to the processing system (6) as a second preprocessing result.
6. A shock wave treatment device based on real-time monitoring and dynamic feedback according to claim 5, characterized in that the processing system (6) comprises:
the receiving module (61) is connected with the second preprocessing module (52) and the first preprocessing module (42) and is used for receiving the second preprocessing result and the first preprocessing result;
the feedback module (62) is connected with the receiving module (61) and the controller (22) and is used for comparing the first preprocessing result with the second preprocessing result and taking the difference value of the first preprocessing result and the second preprocessing result as a first processing result, and carrying out energy feedback on the controller (22) according to the first processing result;
the fitting module (63), the fitting module (63) is connected with the feedback module (62), and the fitting module (63) stores a corresponding relation of output shock wave signals and a preset difference threshold in advance, and is used for updating the output shock wave signals according to the corresponding relation when the first processing result exceeds the preset difference threshold;
the calibration module (64) is connected with the fitting module (63) and the control system (12) and is used for constructing and training a long-time memory neural network, inputting the effective shock wave signals into the long-time memory neural network for processing, calibrating the output shock wave signals according to the processing result of the long-time memory neural network, and finally sending the calibration result to the control system (12) to obtain the latest shock wave output instruction and the shock wave implementation path.
7. The method for realizing the shock wave treatment equipment based on the real-time monitoring and the dynamic feedback is characterized by comprising the following steps of:
s1: obtaining and analyzing a treatment scheme through a planning system (11) to obtain a corresponding shock wave application path and a shock wave output instruction, wherein the shock wave output instruction comprises the theoretical output energy of the shock wave and the theoretical impact times;
s2: the control system (12) receives the shock wave application path and the shock wave output instruction, controls the mechanical arm (3) to move according to the shock wave application path, and simultaneously controls the controller (22) of the shock wave generation system (2) to output required shock waves according to the shock wave output instruction until the theoretical number of shock times is reached;
in the process of outputting required shock waves, an output shock wave signal of the controller (22) is detected in real time through an output shock wave signal detection module (41), and meanwhile, an effective shock wave signal of a treatment area is detected in real time through an effective shock wave signal detection module (51) attached to the body surface of the treatment area;
s3: preprocessing and converting the output shock wave signal and the effective shock wave signal to obtain a corresponding first preprocessing result and a corresponding second preprocessing result, and sending the first preprocessing result and the second preprocessing result to a processing system (6);
s4: and (3) processing the first pretreatment result and the second pretreatment result obtained in the step (S3) through the processing system (6), updating the shock wave output instruction and the shock wave application path, and controlling the output of the shock wave.
8. The method for implementing shock wave treatment equipment based on real-time monitoring and dynamic feedback according to claim 7, wherein the specific process of S4 further comprises:
s41: receiving the first pre-processing result and the second pre-processing result through a receiving module (61);
s42: comparing the first pretreatment result and the second pretreatment result through a feedback module (62) and taking the difference value of the first pretreatment result and the second pretreatment result as a first treatment result, and carrying out energy feedback on the controller (22) according to the first treatment result;
s43: the fitting module (63) stores a corresponding relation of output shock wave signal change in advance, and updates the output shock wave signal according to the corresponding relation when the first processing result exceeds a preset difference threshold;
s44: constructing and training a long-short-time memory neural network, inputting the effective shock wave signal into the long-short-time memory neural network for processing, outputting a calibration result, and sending the calibration result to a control system (12);
s45: the control system (12) generates a new shock wave output command and a new shock wave application path according to the calibration result obtained in the step S44, and controls the energy output of the shock wave generation system (2) and the movement of the mechanical arm (3).
9. The method for implementing shock wave treatment equipment based on real-time monitoring and dynamic feedback according to claim 8, wherein the specific process of S44 comprises:
s441: constructing a long-short-time memory neural network, acquiring a historical data set, dividing the historical data set into a training set and a testing set, training the long-short-time memory neural network by using the training set, testing the long-short-time memory neural network by using the testing set, verifying model prediction precision by using a root mean square error method, and finishing training when the precision meets the requirement;
s442: and carrying out normalization processing on the effective shock wave signals, and inputting the effective shock wave signals into the long-short-time memory neural network processing obtained in the step S441 to obtain corresponding calibration results.
10. The method for implementing shock wave treatment equipment based on real-time monitoring and dynamic feedback according to claim 7, wherein the preprocessing and converting in S3 comprises: outlier rejection, mean filtering, and analog-to-digital conversion.
CN202311222421.4A 2023-09-21 2023-09-21 Shock wave treatment equipment and method based on real-time monitoring and dynamic feedback Pending CN117257630A (en)

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