CN113244533A - Parameter adjusting method and device, electronic equipment and computer readable storage medium - Google Patents
Parameter adjusting method and device, electronic equipment and computer readable storage medium Download PDFInfo
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- A—HUMAN NECESSITIES
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Abstract
The application provides a parameter adjusting method, a parameter adjusting device, an electronic device and a computer readable storage medium, wherein the method comprises the following steps: receiving a marking operation by using a program control device arranged outside the patient body, and acquiring an electroencephalogram signal of the patient by using the stimulator in response to the marking operation; storing the patient's electroencephalographic signal and state type association to a first data set; training a first deep learning model by using the first data set to obtain a state classification model; collecting real-time electroencephalogram signals of the patient by using the stimulator; inputting the real-time electroencephalogram signals into the state classification model to obtain real-time state types corresponding to the real-time electroencephalogram signals; acquiring parameter configuration information corresponding to the real-time state type; adjusting, with the programming device, parameters of the stimulator to cause the stimulator to apply corresponding electrical stimulation to the patient. The method can apply timely and accurate electrical stimulation to patients, and has good stimulation effect.
Description
Technical Field
The present application relates to the field of implantable neurostimulation systems, and in particular, to a parameter adjustment method, an apparatus, an electronic device, and a computer-readable storage medium.
Background
The implanted nerve stimulation system mainly comprises a stimulator implanted in a body, an electrode and program control equipment in vitro. The existing nerve regulation and control technology is mainly characterized in that an electrode is implanted in a specific structure (namely a target spot) in a body through a three-dimensional operation, and a stimulator implanted in the body of a patient sends electric pulses to the target spot through the electrode to regulate and control the electric activity and the function of a corresponding nerve structure and network, so that symptoms are improved, and pain is relieved.
After the patient is regulated by the nerves of the doctor in the hospital, the patient returns home and changes the environment or the self state, such as the change of the self state caused by the behaviors of taking medicine, moving, sleeping and the like, and the parameters of the stimulator in the patient body need to be finely adjusted to achieve the best stimulation effect.
However, the existing parameter adjustment method is generally to set a stimulation parameter range by a doctor and to be adjusted by a patient, and the adjustment method is a passive and very inaccurate adjustment method, and the actual effect is not ideal. There is also a method of automatically switching parameters of the device by a time-varying stimulation parameter set by a doctor, which also fails to precisely match the patient's condition and has poor stimulation effect.
Disclosure of Invention
The application aims to provide a parameter adjusting method, a parameter adjusting device, an electronic device and a computer readable storage medium, which can identify the state of a patient based on an electroencephalogram signal of the patient when the state of the patient changes, automatically apply timely and accurate electrical stimulation to the patient, and enable the patient to obtain a relatively ideal stimulation effect.
The purpose of the application is realized by adopting the following technical scheme:
in a first aspect, the present application provides a parameter adjustment method for automatically adjusting a parameter of a stimulator implanted in a patient, the method comprising: receiving a marking operation by using a program control device arranged outside the patient body, and collecting an electroencephalogram signal of the patient by using the stimulator in response to the marking operation, wherein the marking operation is used for marking the state type of the patient; storing the electroencephalogram signal and the state type of the patient into a first data set in an associated mode, so that the first data set comprises a plurality of electroencephalogram signals of the patient and the state type corresponding to each electroencephalogram signal; training a first deep learning model by using the first data set to obtain a state classification model; collecting real-time electroencephalogram signals of the patient by using the stimulator; inputting the real-time electroencephalogram signals into the state classification model to obtain real-time state types corresponding to the real-time electroencephalogram signals; when the real-time state type is detected to change relative to the last moment, acquiring parameter configuration information corresponding to the real-time state type; and adjusting the parameters of the stimulator by using the program control equipment based on the parameter configuration information corresponding to the real-time state type so that the stimulator applies corresponding electrical stimulation to the patient. The technical scheme has the advantages that the state of the patient can be marked, after the program control equipment receives the marking operation, the stimulator can be used for collecting the electroencephalogram of the patient at the moment, the electroencephalogram and the state type of the patient are stored in a first data set in an associated mode, the first deep learning model is trained by using the first data set, the state classification model can be obtained, the state of the patient can be automatically identified by the state classification model, the real-time electroencephalogram is input into the state classification model, the real-time state type corresponding to the real-time electroencephalogram can be obtained, when the real-time state type is detected to change relative to the last moment, the parameters of the stimulator can be adjusted based on the parameter configuration information corresponding to the current real-time state type, and timely and accurate electrical stimulation can be automatically applied to the patient.
In conclusion, the method can identify the state of the patient based on the electroencephalogram signal of the patient when the state of the patient changes, and automatically apply timely and accurate electrical stimulation to the patient according to the parameter configuration information corresponding to the state, so that the patient can obtain a relatively ideal stimulation effect.
In some optional embodiments, the acquiring real-time brain electrical signals of the patient with the stimulator includes: and acquiring real-time electroencephalogram signals of the patient by using the stimulator at preset time or at preset time intervals. The technical scheme has the beneficial effects that on one hand, the states of the patients are different due to different preset time selections, and the preset time can be, for example, one hour after the patients take medicines, during sleeping or during sports, the real-time electroencephalograms of the patients can be collected at the preset time, so that the real-time electroencephalograms of the patients in different states can be obtained; on the other hand, the real-time electroencephalogram signals of the patient can be acquired every preset time, and the preset time can be preset time, such as 1 hour, 2 hours or 3 hours, so that the real-time electroencephalogram signals of the patient in different time periods can be acquired. Generally speaking, the state type of the patient can not be changed frequently, so that reasonable preset time or preset duration can be set, and real-time electroencephalogram signals are collected to perform state analysis when the current time meets the preset time or preset duration conditions, so that the waste of computing resources is avoided.
In some optional embodiments, the obtaining of the parameter configuration information corresponding to the real-time status type includes: acquiring a parameter configuration strategy of the patient, wherein the parameter configuration strategy is used for indicating the corresponding relation between the state type and the parameter configuration information; and determining parameter configuration information corresponding to the real-time state type based on the parameter configuration strategy of the patient. The technical scheme has the advantages that after the real-time state type of the patient is determined, the parameter configuration information corresponding to the real-time state type can be obtained based on the parameter configuration strategy of the patient, so that the patient is stimulated by utilizing the parameter configuration information.
In some optional embodiments, the obtaining the parameter configuration policy of the patient includes: receiving an entry operation by a doctor device or the program-controlled device, and determining a parameter configuration strategy of the patient in response to the entry operation; or importing the parameter configuration strategy of the patient by using a data interface. On one hand, professionals such as doctors can input parameter configuration information corresponding to different state types by using doctor equipment or program control equipment, so that parameter configuration strategies of patients are determined; on the other hand, the preset parameter configuration strategy of the patient can be directly imported by using the data interface, the data import efficiency is high, the human errors can be avoided, and the method is suitable for some common cases without difficult miscellaneous diseases.
In some optional embodiments, the obtaining of the parameter configuration information corresponding to the real-time status type includes: acquiring a second data set, wherein the second data set comprises a plurality of state types of the patient and parameter configuration information corresponding to each state type; training a second deep learning model by using the second data set to obtain a parameter configuration model; and inputting the real-time state type into the parameter configuration model to obtain the parameter configuration information corresponding to the real-time state type. The technical scheme has the advantages that the second deep learning model can be trained by utilizing the second data set to obtain the parameter configuration model, on one hand, the real-time state type can be input into the parameter configuration model to obtain the parameter configuration information corresponding to the real-time state type, so that the parameter configuration information is utilized to stimulate the patient; on the other hand, the parameter configuration model can be formed by training a large amount of sample data, can identify various real-time state types, and has wide application range and high intelligence level.
In some optional embodiments, the adjusting, by the programming device, the parameters of the stimulator based on the parameter configuration information corresponding to the real-time status type includes: generating an adjustment request based on the parameter configuration information corresponding to the real-time state type, and sending the adjustment request to doctor equipment corresponding to the patient, wherein the adjustment request comprises the real-time state type and the parameter configuration information corresponding to the real-time state type; receiving a feedback operation of the physician device; when the feedback operation is a confirmation operation, responding to the confirmation operation, and adjusting the parameters of the stimulator by using the program control equipment based on the parameter configuration information corresponding to the real-time state type; and when the feedback operation is a modification operation, modifying the parameter configuration information corresponding to the real-time state type in response to the modification operation, and adjusting the parameters of the stimulator by using the program control equipment based on the modified parameter configuration information. The technical scheme has the advantages that an adjustment request can be generated and sent to doctor equipment corresponding to a patient based on the parameter configuration information corresponding to the real-time state type, and the doctor determines whether to adjust the parameters of the stimulator by adopting the parameter configuration information; on the other hand, when the doctor considers that the parameter configuration information is not appropriate and needs to be modified, the parameter configuration information can be modified, and the parameters of the stimulator can be adjusted based on the modified parameter configuration information. The marking of the state type of the patient is generally completed by the patient or a person who cares for the patient, a condition of error marking may exist during marking, if the condition is not confirmed by a doctor, electrical stimulation is directly applied according to parameters corresponding to the condition type marked with the error, the patient may be injured, and the life may be damaged in serious conditions, so that feedback operation of the doctor is very necessary, the life safety of the patient can be guaranteed, and the doctor can know the condition change condition of the patient.
In some optional embodiments, the method further comprises: when the feedback operation is a cancellation operation, canceling the adjustment of the parameters of the stimulator in response to the cancellation operation. The technical scheme has the beneficial effect that when the doctor thinks that the parameters of the stimulator of the patient do not need to be adjusted, the doctor equipment can be utilized to cancel the adjustment of the parameters of the stimulator.
In a second aspect, the present application provides a parameter adjustment device for automatically adjusting a parameter of a stimulator implanted in a patient, the device comprising: the data acquisition module is used for receiving marking operation by using a program control device arranged outside the patient body, responding to the marking operation, and acquiring electroencephalogram signals of the patient by using the stimulator, wherein the marking operation is used for marking the state type of the patient; the data storage module is used for storing the electroencephalogram signal and the state type of the patient into a first data set in an associated mode so that the first data set comprises a plurality of electroencephalogram signals of the patient and the state type corresponding to each electroencephalogram signal; the model training module is used for training a first deep learning model by utilizing the first data set to obtain a state classification model; the real-time acquisition module is used for acquiring real-time electroencephalogram signals of the patient by using the stimulator; the state classification module is used for inputting the real-time electroencephalogram signals into the state classification model to obtain real-time state types corresponding to the real-time electroencephalogram signals; the configuration acquisition module is used for acquiring parameter configuration information corresponding to the real-time state type when the real-time state type is detected to change relative to the last moment; and the parameter adjusting module is used for adjusting the parameters of the stimulator by using the program control equipment based on the parameter configuration information corresponding to the real-time state type so that the stimulator applies corresponding electrical stimulation to the patient.
In some optional embodiments, the data acquisition module is configured to acquire real-time electroencephalogram signals of the patient by using the stimulator at preset time or at preset time intervals.
In some optional embodiments, the configuration acquisition module comprises: the strategy acquisition unit is used for acquiring a parameter configuration strategy of the patient, wherein the parameter configuration strategy is used for indicating the corresponding relation between the state type and the parameter configuration information; and the configuration determining unit is used for determining the parameter configuration information corresponding to the real-time state type based on the parameter configuration strategy of the patient.
In some optional embodiments, the policy obtaining unit includes: the data entry subunit is used for receiving entry operation by utilizing a doctor device or the program-controlled device, and determining a parameter configuration strategy of the patient in response to the entry operation; or, the data importing subunit is configured to import the parameter configuration policy of the patient by using a data interface.
In some optional embodiments, the configuration acquisition module comprises: a data set unit, configured to acquire a second data set, where the second data set includes a plurality of status types of the patient and parameter configuration information corresponding to each status type; the configuration model unit is used for training a second deep learning model by utilizing the second data set to obtain a parameter configuration model; and the configuration information unit is used for inputting the real-time state type into the parameter configuration model to obtain the parameter configuration information corresponding to the real-time state type.
In some optional embodiments, the parameter adjustment module comprises: the request generating unit is used for generating an adjusting request based on the parameter configuration information corresponding to the real-time state type and sending the adjusting request to the doctor equipment corresponding to the patient, wherein the adjusting request comprises the real-time state type and the parameter configuration information corresponding to the real-time state type; a feedback receiving unit for receiving a feedback operation of the doctor device; a first adjusting unit, configured to, when the feedback operation is a confirmation operation, adjust, by the programming device, a parameter of the stimulator based on parameter configuration information corresponding to the real-time status type in response to the confirmation operation; and the second adjusting unit is used for responding to the modification operation when the feedback operation is the modification operation, modifying the parameter configuration information corresponding to the real-time state type, and adjusting the parameters of the stimulator by using the program control equipment based on the modified parameter configuration information.
In some optional embodiments, the apparatus further comprises: a cancellation operation module for canceling the adjustment of the parameters of the stimulator in response to the cancellation operation when the feedback operation is a cancellation operation.
In a third aspect, the present application provides an electronic device for automatically adjusting parameters of a stimulator implanted in a patient, the electronic device comprising a memory storing a computer program and a processor implementing the steps of any of the above methods when the computer program is executed by the processor.
In some alternative embodiments, the electronic device is integrated with the programming device.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of any of the methods described above.
Drawings
The present application is further described below with reference to the drawings and examples.
Fig. 1 is a schematic flow chart of a parameter adjusting method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a process for obtaining parameter configuration information according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart of acquiring a parameter configuration policy according to an embodiment of the present application;
fig. 4 is a schematic flowchart of another process for acquiring parameter configuration information according to an embodiment of the present application;
FIG. 5 is a schematic flow chart for adjusting parameters of a stimulator according to an embodiment of the present disclosure;
fig. 6 is a partial schematic flow chart of a parameter adjusting method according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a parameter adjusting apparatus according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a configuration acquisition module according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of a policy obtaining unit according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of another configuration acquisition module provided in an embodiment of the present application;
fig. 11 is a schematic structural diagram of a parameter adjustment module according to an embodiment of the present application;
fig. 12 is a schematic partial structural diagram of a parameter adjusting apparatus according to an embodiment of the present application;
fig. 13 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 14 is a schematic structural diagram of a program product for implementing a parameter adjustment method according to an embodiment of the present application.
Detailed Description
The present application is further described with reference to the accompanying drawings and the detailed description, and it should be noted that, in the present application, the embodiments or technical features described below may be arbitrarily combined to form a new embodiment without conflict.
Referring to fig. 1, the embodiment of the present application provides a parameter adjusting method for automatically adjusting parameters of a stimulator implanted in a patient, the method includes steps S101 to S107. The stimulator may be any one of an Implantable nerve electrical stimulation device, an Implantable cardiac electrical stimulation System (also called a cardiac pacemaker), an Implantable Drug Delivery System (I DDS for short), and a lead switching device. Examples of the implantable neural electrical Stimulation device include Deep Brain Stimulation (DBS), Cortical Brain Stimulation (CNS), Spinal Cord Stimulation (SCS), Sacral Nerve Stimulation (SNS), and Vagal Nerve Stimulation (VNS). Parameters of the stimulator are, for example, the frequency (number of pulses per unit time 1s, in Hz), the pulse width (duration of each pulse, in mus), and the amplitude (generally expressed in voltage, i.e. the intensity of each pulse, in V). In a particular application, the parameters of the stimulator may be adjusted in either current mode or voltage mode.
The patients in the embodiment of the application can be Parkinson patients, or mental disease patients such as depression patients and obsessive compulsive disease patients, and can also be drug addiction patients or drug abstinence personnel.
For Parkinson patients, the most commonly used parameters are 130Hz, 60 μ s and a voltage of 2-3V. For patients with tremor symptoms, pulse stimulation above 100Hz is effective, while low frequency stimulation may even exacerbate the tremor.
Step S101: receiving a marking operation by using a program control device arranged outside the patient body, and collecting the electroencephalogram signal of the patient by using the stimulator in response to the marking operation, wherein the marking operation is used for marking the state type of the patient.
The target for marking the program control device may be the patient himself, or a patient care person such as a doctor, a nurse, or a family of the patient.
The program control device for receiving the marking operation can adopt a program control device existing in the prior art, namely a program control device arranged outside the patient body; alternatively, the programmable device may be a separate hardware device, which is an electronic device capable of performing data interaction with the stimulator or the programmable device, such as a tablet computer, a mobile phone, or a smart wearable device, and the patient or the care provider may perform the marking operation using the programmable device. Generally, a program-controlled device is loaded with a computer program (i.e., software), and the computer program, when executed by a processor, can implement the steps of the parameter adjustment method in the embodiments of the present application.
The status type of the patient may include, for example, at least one of: before sleep, after getting up, after taking medicine, after meals and in sports, the state types can be preset options, and one of the options can be selected when the state types are marked, or the state types can be customized by a user of the program control equipment.
Step S102: and storing the electroencephalogram signal and the state type of the patient into a first data set in an associated manner, so that the first data set comprises a plurality of electroencephalogram signals of the patient and the state type corresponding to each electroencephalogram signal.
Step S103: and training a first deep learning model by using the first data set to obtain a state classification model. Wherein the first deep learning model is, for example, a given neural network, or a re-constructed neural network.
Step S104: and acquiring real-time electroencephalogram signals of the patient by using the stimulator. In the collecting process, the stimulator can obtain the real-time electroencephalogram signal corresponding to each moment, such as the real-time electroencephalogram signal at the previous moment, the real-time electroencephalogram signal at the current moment and the real-time electroencephalogram signal at the next moment.
In some embodiments, the method for acquiring real-time brain electrical signals of the patient by using the stimulator in the step S101 may include: and acquiring real-time electroencephalogram signals of the patient by using the stimulator at preset time or at preset time intervals.
Therefore, on one hand, the states of the patients are different due to different preset time selections, and the preset time can be, for example, one hour after the patients take medicines, during sleeping or during exercise, the real-time electroencephalogram signals of the patients can be collected at the preset time, so that the real-time electroencephalogram signals of the patients in different states are obtained; on the other hand, the real-time electroencephalogram signals of the patient can be acquired every preset time, and the preset time can be preset time, such as 1 hour, 2 hours or 3 hours, so that the real-time electroencephalogram signals of the patient in different time periods can be acquired. Generally speaking, the state type of the patient can not be changed frequently, so that reasonable preset time or preset duration can be set, and real-time electroencephalogram signals are collected to perform state analysis when the current time meets the preset time or preset duration conditions, so that the waste of computing resources is avoided.
Step S105: and inputting the real-time electroencephalogram signals into the state classification model to obtain real-time state types corresponding to the real-time electroencephalogram signals.
Step S106: and when the real-time state type is detected to be changed relative to the last moment, acquiring the parameter configuration information corresponding to the real-time state type. Wherein the parameter configuration information is used to determine parameters of the stimulator to adjust the electrical stimulation applied by the stimulator to the patient.
Referring to fig. 2, in some embodiments, the method for acquiring the parameter configuration information corresponding to the real-time status type in step S106 may include steps S201 to S202.
Step S201: and acquiring a parameter configuration strategy of the patient, wherein the parameter configuration strategy is used for indicating the corresponding relation between the state type and the parameter configuration information. And aiming at a certain state type, corresponding to unique parameter configuration information. Generally speaking, the status type and the parameter configuration information may be in a one-to-one correspondence relationship, for example, the parameter configuration information corresponding to the status before sleep causes the stimulator to stop applying electrical stimulation, and the parameter configuration information corresponding to the status after getting up causes the stimulator to start applying electrical stimulation; in other cases, such as after breakfast and after dinner, the same set of parameter configuration information may be selected to configure the parameters of the stimulator such that the stimulator applies electrical stimulation of the same parameters to the patient during the time periods after breakfast and after dinner.
Referring to fig. 3, in some embodiments, the step S201 may include step S301 or step S302.
Step S301: receiving an entry operation with a physician device or the programming device, and determining a parameter configuration policy of the patient in response to the entry operation. The doctor device is, for example, a mobile phone, a tablet computer (for example, ipad), a computer, a smart wearable device, and the like, and the doctor can set a customized and personalized parameter configuration policy for the patient by using the doctor device. Some program control equipment is near a patient, and doctor equipment can be equipment carried by a doctor, so that compared with the mode that the program control equipment is used for inputting information, the mode that the doctor equipment is used for inputting information is not limited by places, and related information can be input even if the doctor equipment is not near the patient.
Step S302: importing a parameter configuration policy for the patient using a data interface.
Therefore, on one hand, professionals such as doctors can input parameter configuration information corresponding to different state types by using doctor equipment or program control equipment, so that parameter configuration strategies of patients are determined; on the other hand, the preset parameter configuration strategy of the patient can be directly imported by using the data interface, the data import efficiency is high, the human errors can be avoided, and the method is suitable for some common cases without difficult miscellaneous diseases.
Step S202: and determining parameter configuration information corresponding to the real-time state type based on the parameter configuration strategy of the patient.
Therefore, after the real-time state type of the patient is determined, the parameter configuration information corresponding to the real-time state type can be acquired based on the parameter configuration strategy of the patient, so that the patient is stimulated by the parameter configuration information.
Referring to fig. 4, in some embodiments, the method for acquiring the parameter configuration information corresponding to the real-time status type in step S106 may include steps S401 to S403.
Step S401: a second data set is obtained that includes a plurality of status types for the patient and parameter configuration information corresponding to each status type.
Step S402: and training a second deep learning model by using the second data set to obtain a parameter configuration model.
Step S403: and inputting the real-time state type into the parameter configuration model to obtain the parameter configuration information corresponding to the real-time state type.
Therefore, the second deep learning model can be trained by using the second data set to obtain the parameter configuration model, on one hand, the real-time state type can be input into the parameter configuration model to obtain the parameter configuration information corresponding to the real-time state type, and therefore, the patient is stimulated by using the parameter configuration information; on the other hand, the parameter configuration model can be formed by training a large amount of sample data, can identify various real-time state types, and has wide application range and high intelligence level.
Step S107: and adjusting the parameters of the stimulator by using the program control equipment based on the parameter configuration information corresponding to the real-time state type so that the stimulator applies corresponding electrical stimulation to the patient.
Therefore, the state of the patient can be marked, after the program control equipment receives the marking operation, the stimulator can be used for collecting the electroencephalograms of the patient at the moment, the electroencephalograms and the state types of the patient are stored in a first data set in an associated mode, a first deep learning model is trained by the aid of the first data set, a state classification model is obtained, the state of the patient can be automatically recognized by the state classification model, the real-time electroencephalograms are input into the state classification model, the real-time state types corresponding to the real-time electroencephalograms can be obtained, when the real-time state types are detected to change relative to the last moment, the parameters of the stimulator can be adjusted based on the parameter configuration information corresponding to the current real-time state types, and timely and accurate electrical stimulation can be automatically applied to the patient.
In conclusion, the method can identify the state of the patient based on the electroencephalogram signal of the patient when the state of the patient changes, and automatically apply timely and accurate electrical stimulation to the patient according to the parameter configuration information corresponding to the state, so that the patient can obtain a relatively ideal stimulation effect.
Referring to fig. 5, in some embodiments, the method for adjusting parameters of the stimulator by using the programming device based on the parameter configuration information corresponding to the real-time status type in step S107 may include steps S501 to S504.
Step S501: and generating an adjustment request based on the parameter configuration information corresponding to the real-time state type, and sending the adjustment request to the doctor equipment corresponding to the patient, wherein the adjustment request comprises the real-time state type and the parameter configuration information corresponding to the real-time state type.
Step S502: receiving a feedback operation of the physician device. The feedback operation is, for example, any one of a confirmation operation, a modification operation, and a cancellation operation.
Step S503: when the feedback operation is a confirmation operation, adjusting parameters of the stimulator by the programming device based on parameter configuration information corresponding to the real-time status type in response to the confirmation operation.
Step S504: and when the feedback operation is a modification operation, modifying the parameter configuration information corresponding to the real-time state type in response to the modification operation, and adjusting the parameters of the stimulator by using the program control equipment based on the modified parameter configuration information.
Therefore, an adjustment request can be generated and sent to doctor equipment corresponding to a patient based on the parameter configuration information corresponding to the real-time state type, and a doctor determines whether to adjust the parameters of the stimulator by adopting the parameter configuration information; on the other hand, when the doctor considers that the parameter configuration information is not appropriate and needs to be modified, the parameter configuration information can be modified, and the parameters of the stimulator can be adjusted based on the modified parameter configuration information. The marking of the state type of the patient is generally completed by the patient or a person who cares for the patient, a condition of error marking may exist during marking, if the condition is not confirmed by a doctor, electrical stimulation is directly applied according to parameters corresponding to the condition type marked with the error, the patient may be injured, and the life may be damaged in serious conditions, so that feedback operation of the doctor is very necessary, the life safety of the patient can be guaranteed, and the doctor can know the condition change condition of the patient.
Referring to fig. 6, in some embodiments, the method may further include step S108.
Step S108: when the feedback operation is a cancellation operation, canceling the adjustment of the parameters of the stimulator in response to the cancellation operation.
Thus, when the physician deems that the parameters of the stimulator of the patient do not need to be adjusted, the physician device can be used to cancel the adjustment of the parameters of the stimulator.
Referring to fig. 7, an embodiment of the present application further provides a parameter adjusting apparatus, and a specific implementation manner of the parameter adjusting apparatus is consistent with the implementation manner and the achieved technical effect described in the embodiment of the parameter adjusting method, and details of a part of the implementation manner and the achieved technical effect are not repeated.
The apparatus for automatically adjusting parameters of a stimulator implanted in a patient, the apparatus comprising: the data acquisition module 101 is configured to receive a marking operation by using a program-controlled device disposed outside the patient, and acquire an electroencephalogram signal of the patient by using the stimulator in response to the marking operation, where the marking operation is used to mark a status type of the patient; the data storage module 102 is configured to store the electroencephalogram signal of the patient and the state type in association with a first data set, so that the first data set includes a plurality of electroencephalograms of the patient and a state type corresponding to each electroencephalogram; the model training module 103 is configured to train a first deep learning model by using the first data set to obtain a state classification model; a real-time acquisition module 104 for acquiring real-time electroencephalogram signals of the patient using the stimulator; the state classification module 105 is used for inputting the real-time electroencephalogram signals into the state classification model to obtain real-time state types corresponding to the real-time electroencephalogram signals; a configuration obtaining module 106, configured to obtain parameter configuration information corresponding to the real-time status type when it is detected that the real-time status type changes from a previous time; a parameter adjusting module 107, configured to adjust, by using the program control device, a parameter of the stimulator based on the parameter configuration information corresponding to the real-time status type, so that the stimulator applies corresponding electrical stimulation to the patient.
In some embodiments, the data acquisition module 101 may be configured to acquire real-time electroencephalographic signals of the patient using the stimulator at a preset time or at preset intervals.
Referring to fig. 8, in some embodiments, the configuration acquisition module 106 may include: a policy obtaining unit 1061, configured to obtain a parameter configuration policy of the patient, where the parameter configuration policy is used to indicate a correspondence between a state type and parameter configuration information; the configuration determining unit 1062 is configured to determine, based on the parameter configuration policy of the patient, parameter configuration information corresponding to the real-time status type.
Referring to fig. 9, in some embodiments, the policy obtaining unit 1061 may include: a data entry subunit 1061a, configured to receive an entry operation with a physician device or the program-controlled device, and determine, in response to the entry operation, a parameter configuration policy of the patient; or, the data import subunit 1061b is configured to import the parameter configuration policy of the patient by using a data interface.
Referring to fig. 10, in some embodiments, the configuration acquisition module 106 may include: a data set unit 1063, configured to obtain a second data set, where the second data set includes a plurality of status types of the patient and parameter configuration information corresponding to each status type; a configuration model unit 1064, configured to train a second deep learning model using the second data set to obtain a parameter configuration model; the configuration information unit 1065 is configured to input the real-time status type into the parameter configuration model, so as to obtain parameter configuration information corresponding to the real-time status type.
Referring to fig. 11, in some embodiments, the parameter adjusting module 107 may include: a request generating unit 1071, configured to generate an adjustment request based on the parameter configuration information corresponding to the real-time status type, and send the adjustment request to the doctor device corresponding to the patient, where the adjustment request includes the real-time status type and the parameter configuration information corresponding to the real-time status type; a feedback receiving unit 1072 for receiving a feedback operation of the doctor device; a first adjusting unit 1073, configured to adjust, when the feedback operation is a confirmation operation, a parameter of the stimulator by using the programming device based on the parameter configuration information corresponding to the real-time status type in response to the confirmation operation; a second adjusting unit 1074, configured to, when the feedback operation is a modification operation, modify the parameter configuration information corresponding to the real-time status type in response to the modification operation, and adjust the parameter of the stimulator by using the programming device based on the modified parameter configuration information.
Referring to fig. 12, in some embodiments, the apparatus may further include: a cancellation operation module 108, which may be configured to cancel adjusting the parameters of the stimulator in response to the cancellation operation when the feedback operation is a cancellation operation.
Referring to fig. 13, an embodiment of the present application further provides an electronic device 200, where the electronic device 200 includes at least one memory 210, at least one processor 220, and a bus 230 connecting different platform systems.
The memory 210 may include readable media in the form of volatile memory, such as Random Access Memory (RAM)211 and/or cache memory 212, and may further include Read Only Memory (ROM) 213.
The memory 210 further stores a computer program, and the computer program can be executed by the processor 220, so that the processor 220 executes the steps of the parameter adjustment method in the embodiment of the present application, and the specific implementation manner of the method is consistent with the implementation manner and the achieved technical effect described in the embodiment of the parameter adjustment method, and some contents are not described again.
Accordingly, the processor 220 may execute the computer programs described above, and may execute the utility 214.
The electronic device 200 may also communicate with one or more external devices 240, such as a keyboard, pointing device, bluetooth device, etc., and may also communicate with one or more devices capable of interacting with the electronic device 200, and/or with any devices (e.g., routers, modems, etc.) that enable the electronic device 200 to communicate with one or more other computing devices. Such communication may be through input-output interface 250. Also, the electronic device 200 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 260. The network adapter 260 may communicate with other modules of the electronic device 200 via the bus 230. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 200, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.
The embodiment of the present application is not limited to the specific structure of the electronic device 200, and the electronic device 200 is used to automatically adjust the parameters of the stimulator implanted in the patient.
In a specific application, the electronic device 200 may be integrated with a program control device, so that the program control device may utilize the electronic device 200 to implement the steps of the parameter adjustment method, so as to apply timely and accurate electrical stimulation to a patient, so that the patient obtains a relatively ideal stimulation effect.
In another specific application, the electronic device 200 may be integrated with any one of a stimulator, a doctor device, and a cloud server.
The embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium is used to store a computer program, and when the computer program is executed, the steps of the parameter adjustment method in the embodiments of the present application are implemented, and a specific implementation manner of the method is consistent with the implementation manner and the achieved technical effect described in the embodiments of the parameter adjustment method, and some details are not repeated.
Fig. 14 shows a program product 300 for implementing the parameter adjustment method provided in this embodiment, which may employ a portable compact disc read only memory (CD-ROM) and include program codes, and may be executed on a terminal device, such as a personal computer. However, the program product 300 of the present invention is not so limited, and in this application, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. Program product 300 may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that can communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the C language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
While the present application is described in terms of various aspects, including exemplary embodiments, the principles of the invention should not be limited to the disclosed embodiments, but are also intended to cover various modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.
Claims (11)
1. A parameter adjustment method for automatically adjusting a parameter of a stimulator implanted in a patient, the method comprising:
receiving a marking operation by using a program control device arranged outside the patient body, and collecting an electroencephalogram signal of the patient by using the stimulator in response to the marking operation, wherein the marking operation is used for marking the state type of the patient;
storing the electroencephalogram signal and the state type of the patient into a first data set in an associated mode, so that the first data set comprises a plurality of electroencephalogram signals of the patient and the state type corresponding to each electroencephalogram signal;
training a first deep learning model by using the first data set to obtain a state classification model;
collecting real-time electroencephalogram signals of the patient by using the stimulator;
inputting the real-time electroencephalogram signals into the state classification model to obtain real-time state types corresponding to the real-time electroencephalogram signals;
when the real-time state type is detected to change relative to the last moment, acquiring parameter configuration information corresponding to the real-time state type;
and adjusting the parameters of the stimulator by using the program control equipment based on the parameter configuration information corresponding to the real-time state type so that the stimulator applies corresponding electrical stimulation to the patient.
2. The parameter adjustment method according to claim 1, wherein the acquiring real-time brain electrical signals of the patient with the stimulator comprises:
and acquiring real-time electroencephalogram signals of the patient by using the stimulator at preset time or at preset time intervals.
3. The method according to claim 1, wherein the obtaining the parameter configuration information corresponding to the real-time status type includes:
acquiring a parameter configuration strategy of the patient, wherein the parameter configuration strategy is used for indicating the corresponding relation between the state type and the parameter configuration information;
and determining parameter configuration information corresponding to the real-time state type based on the parameter configuration strategy of the patient.
4. The parameter adjustment method according to claim 3, wherein the obtaining the parameter configuration policy of the patient comprises:
receiving an entry operation by a doctor device or the program-controlled device, and determining a parameter configuration strategy of the patient in response to the entry operation; alternatively, the first and second electrodes may be,
importing a parameter configuration policy for the patient using a data interface.
5. The method according to claim 1, wherein the obtaining the parameter configuration information corresponding to the real-time status type includes:
acquiring a second data set, wherein the second data set comprises a plurality of state types of the patient and parameter configuration information corresponding to each state type;
training a second deep learning model by using the second data set to obtain a parameter configuration model;
and inputting the real-time state type into the parameter configuration model to obtain the parameter configuration information corresponding to the real-time state type.
6. The parameter adjustment method according to claim 1, wherein the adjusting the parameters of the stimulator by using the programming device based on the parameter configuration information corresponding to the real-time status type includes:
generating an adjustment request based on the parameter configuration information corresponding to the real-time state type, and sending the adjustment request to doctor equipment corresponding to the patient, wherein the adjustment request comprises the real-time state type and the parameter configuration information corresponding to the real-time state type;
receiving a feedback operation of the physician device;
when the feedback operation is a confirmation operation, responding to the confirmation operation, and adjusting the parameters of the stimulator by using the program control equipment based on the parameter configuration information corresponding to the real-time state type;
and when the feedback operation is a modification operation, modifying the parameter configuration information corresponding to the real-time state type in response to the modification operation, and adjusting the parameters of the stimulator by using the program control equipment based on the modified parameter configuration information.
7. The method of claim 6, further comprising:
when the feedback operation is a cancellation operation, canceling the adjustment of the parameters of the stimulator in response to the cancellation operation.
8. A parameter adjustment device for automatically adjusting a parameter of a stimulator implanted in a patient, the device comprising:
the data acquisition module is used for receiving marking operation by using a program control device arranged outside the patient body, responding to the marking operation, and acquiring electroencephalogram signals of the patient by using the stimulator, wherein the marking operation is used for marking the state type of the patient;
the data storage module is used for storing the electroencephalogram signal and the state type of the patient into a first data set in an associated mode so that the first data set comprises a plurality of electroencephalogram signals of the patient and the state type corresponding to each electroencephalogram signal;
the model training module is used for training a first deep learning model by utilizing the first data set to obtain a state classification model;
the real-time acquisition module is used for acquiring real-time electroencephalogram signals of the patient by using the stimulator;
the state classification module is used for inputting the real-time electroencephalogram signals into the state classification model to obtain real-time state types corresponding to the real-time electroencephalogram signals;
the configuration acquisition module is used for acquiring parameter configuration information corresponding to the real-time state type when the real-time state type is detected to change relative to the last moment;
and the parameter adjusting module is used for adjusting the parameters of the stimulator by using the program control equipment based on the parameter configuration information corresponding to the real-time state type so that the stimulator applies corresponding electrical stimulation to the patient.
9. An electronic device for automatically adjusting parameters of a stimulator implanted in a patient, the electronic device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of the method according to any one of claims 1 to 7 when executing the computer program.
10. The electronic device of claim 9, wherein the electronic device is integrated with a programming device.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114272488A (en) * | 2021-12-21 | 2022-04-05 | 上海梅斯医药科技有限公司 | Acousto-optic synchronous stimulation regulation and control method and device and computer readable storage medium |
| CN115054828A (en) * | 2022-07-25 | 2022-09-16 | 苏州景昱医疗器械有限公司 | Pulse generator, medical system, and computer-readable storage medium |
| WO2023071378A1 (en) * | 2021-10-26 | 2023-05-04 | 苏州景昱医疗器械有限公司 | Implantable nerve stimulator and implantable nerve stimulation system |
| WO2023124390A1 (en) * | 2021-12-27 | 2023-07-06 | 苏州景昱医疗器械有限公司 | Program-controlled device and implantable neurostimulation system |
| WO2023185410A1 (en) * | 2022-03-31 | 2023-10-05 | 苏州景昱医疗器械有限公司 | Imaging identification method for stimulation electrode wire, and related apparatus |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106512206A (en) * | 2016-11-04 | 2017-03-22 | 清华大学 | Implanted closed-loop brain deep stimulating system |
| CN106621041A (en) * | 2016-12-21 | 2017-05-10 | 北京品驰医疗设备有限公司 | Configuration system for electronic prescription of vagus nerve stimulator |
| CN106730337A (en) * | 2016-12-22 | 2017-05-31 | 北京品驰医疗设备有限公司 | A kind of vagus nerve stimulator electronic prescription configuration system of quickly-chargeable |
| CN109529193A (en) * | 2018-12-29 | 2019-03-29 | 北京品驰医疗设备有限公司 | Vagus nerve stimulator and system based on closed-loop control |
| CN109864750A (en) * | 2019-01-31 | 2019-06-11 | 华南理工大学 | Based on the state of mind assessment and regulating system and its working method stimulated through cranium |
| CN111477299A (en) * | 2020-04-08 | 2020-07-31 | 广州艾博润医疗科技有限公司 | Method and device for regulating and controlling sound-electricity stimulation nerves by combining electroencephalogram detection and analysis control |
| CN111481830A (en) * | 2020-04-24 | 2020-08-04 | 上海交通大学 | Closed-loop electrical nerve stimulation system and method for setting parameters of closed-loop electrical nerve stimulation |
| CN112691292A (en) * | 2021-01-12 | 2021-04-23 | 天津大学 | Parkinson closed-loop deep brain stimulation system based on wearable intelligent equipment |
| CN112999518A (en) * | 2014-11-21 | 2021-06-22 | 美敦力公司 | Electrode selection for electrical stimulation therapy |
-
2021
- 2021-06-24 CN CN202110705352.7A patent/CN113244533A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112999518A (en) * | 2014-11-21 | 2021-06-22 | 美敦力公司 | Electrode selection for electrical stimulation therapy |
| CN106512206A (en) * | 2016-11-04 | 2017-03-22 | 清华大学 | Implanted closed-loop brain deep stimulating system |
| CN106621041A (en) * | 2016-12-21 | 2017-05-10 | 北京品驰医疗设备有限公司 | Configuration system for electronic prescription of vagus nerve stimulator |
| CN106730337A (en) * | 2016-12-22 | 2017-05-31 | 北京品驰医疗设备有限公司 | A kind of vagus nerve stimulator electronic prescription configuration system of quickly-chargeable |
| CN109529193A (en) * | 2018-12-29 | 2019-03-29 | 北京品驰医疗设备有限公司 | Vagus nerve stimulator and system based on closed-loop control |
| CN109864750A (en) * | 2019-01-31 | 2019-06-11 | 华南理工大学 | Based on the state of mind assessment and regulating system and its working method stimulated through cranium |
| CN111477299A (en) * | 2020-04-08 | 2020-07-31 | 广州艾博润医疗科技有限公司 | Method and device for regulating and controlling sound-electricity stimulation nerves by combining electroencephalogram detection and analysis control |
| CN111481830A (en) * | 2020-04-24 | 2020-08-04 | 上海交通大学 | Closed-loop electrical nerve stimulation system and method for setting parameters of closed-loop electrical nerve stimulation |
| CN112691292A (en) * | 2021-01-12 | 2021-04-23 | 天津大学 | Parkinson closed-loop deep brain stimulation system based on wearable intelligent equipment |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2023071378A1 (en) * | 2021-10-26 | 2023-05-04 | 苏州景昱医疗器械有限公司 | Implantable nerve stimulator and implantable nerve stimulation system |
| CN114272488A (en) * | 2021-12-21 | 2022-04-05 | 上海梅斯医药科技有限公司 | Acousto-optic synchronous stimulation regulation and control method and device and computer readable storage medium |
| CN114272488B (en) * | 2021-12-21 | 2024-04-12 | 上海梅斯医药科技有限公司 | Acousto-optic synchronous stimulation regulation and control method, device and computer readable storage medium |
| WO2023124390A1 (en) * | 2021-12-27 | 2023-07-06 | 苏州景昱医疗器械有限公司 | Program-controlled device and implantable neurostimulation system |
| WO2023185410A1 (en) * | 2022-03-31 | 2023-10-05 | 苏州景昱医疗器械有限公司 | Imaging identification method for stimulation electrode wire, and related apparatus |
| CN115054828A (en) * | 2022-07-25 | 2022-09-16 | 苏州景昱医疗器械有限公司 | Pulse generator, medical system, and computer-readable storage medium |
| CN115054828B (en) * | 2022-07-25 | 2022-11-01 | 苏州景昱医疗器械有限公司 | Pulse generator, medical system, and computer-readable storage medium |
| WO2024021960A1 (en) * | 2022-07-25 | 2024-02-01 | 景昱医疗科技（苏州）股份有限公司 | Pulse generator, medical system, and computer-readable storage medium |
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