CN115153589A - Method, system, electronic device and storage medium for recording electroencephalogram signal data - Google Patents

Abstract

The present application provides a method, system, electronic device and storage medium for EEG signal data recording, including: acquiring EEG signals to be recorded in target EEG data, where the EEG signals to be recorded are EEG signals with nerve impulses ; Count the numerical value of the EEG signal to be recorded, and obtain the EEG signal feature of the target EEG data; classify and mark the EEG signal to be recorded according to the EEG signal feature, and the classification includes: normal EEG signal, abnormal EEG signal; classify and record the normal EEG signal and/or abnormal EEG signal. The EEG signals are divided into normal EEG signals and abnormal EEG signals according to the EEG patterns, and corresponding index addresses are recorded for different types of EEG signals, which greatly shortens the retrieval time of EEG signals.

Description

EEG signal data recording method, system, electronic device and storage medium

technical field

The present application belongs to the field of electroencephalography, and in particular relates to a method, system, electronic device and storage medium for recording electroencephalographic signal data.

Background technique

At present, the recording method of EEG signal is mainly polyconductive signal. The number of signal channels and recording time of polyconductive signal are limited. Most of the original data is recorded, and the amount of recorded data is not large, so the amount of data for data analysis is not large. Most of the time, the data traversal method is used to find the required data, and the index method is not used to find the data.

The search time of EEG signal search by traversal method is greatly affected by the amount of data. When the amount of data is small, the search time is short, which is acceptable. If the amount of data increases, it will increase the time to search for the required data. Take up a lot of resources.

SUMMARY OF THE INVENTION

The main purpose of the embodiments of the present invention is to provide a method, system, electronic device and storage medium for EEG signal data recording, so that EEG signals can be divided into normal EEG signals and abnormal EEG signals according to EEG patterns. EEG signals are recorded with corresponding index addresses, which greatly shortens the retrieval time of EEG signals.

In a first aspect, a method for recording EEG signal data is provided, the method comprising:

Obtaining the EEG signal to be recorded in the target EEG data, the EEG signal to be recorded is an EEG signal with nerve impulses;

Count the numerical value of the EEG signal to be recorded, and obtain the EEG signal characteristics of the target EEG data;

Classify and mark the to-be-recorded EEG signals according to the features of the EEG signals, and the classification includes: normal EEG signals and abnormal EEG signals;

The normal EEG signal and/or the abnormal EEG signal are classified and recorded.

In a possible implementation manner, the classification and recording of the normal EEG signal and/or the abnormal EEG signal includes:

If the to-be-recorded EEG signal is a normal EEG signal, record the start time, peak/trough frequency, duration, and index address of the normal EEG signal; and,

If the to-be-recorded EEG signal is an abnormal EEG signal, record the start time, the frequency, duration, and index address of the abnormal EEG signal.

In another possible implementation manner, the counting of the values of the EEG signals to be recorded, and obtaining the EEG signal characteristics of the target EEG data, include:

Counting the number of peaks and/or troughs in the EEG signal to be recorded in the set time period, and obtaining the value of each peak and/or trough;

Based on the numbers and values, an average peak value and/or an average trough value are obtained.

In another possible implementation manner, classifying and marking the to-be-recorded EEG signal according to the EEG signal feature includes:

Obtain the peak value difference and/or the trough value difference between the peak value and/or the trough value of the EEG signal to be recorded and the average peak value and/or the average trough value;

If the absolute value of the peak value difference and/or the trough value difference is outside the threshold range, the EEG signal to be recorded is an abnormal EEG signal; and, if the absolute value of the peak value difference and/or the trough value difference is If the value is within the threshold range, the EEG signal to be recorded is a normal EEG signal.

In a second aspect, a system for recording EEG signal data is provided, the system comprising:

a to-be-recorded EEG signal acquisition module, configured to acquire the to-be-recorded EEG signal in the target EEG data, where the to-be-recorded EEG signal is an EEG signal with nerve impulses;

an EEG signal feature acquisition module, configured to count the value of the EEG signal to be recorded, and obtain the EEG signal feature of the target EEG data;

A classification and marking module, configured to classify and record the normal EEG signal and/or the abnormal EEG signal, and the classification includes: normal EEG signal and abnormal EEG signal;

The index address recording module is used to respectively record the corresponding index addresses of the normal EEG signal and/or the abnormal EEG signal.

In a possible implementation manner, the classification and recording of the normal EEG signal and/or the abnormal EEG signal includes:

If the to-be-recorded EEG signal is a normal EEG signal, record the start time, peak/trough frequency, duration, and index address of the normal EEG signal; and,

If the to-be-recorded EEG signal is an abnormal EEG signal, record the start time, the frequency, duration, and index address of the abnormal EEG signal.

In another possible implementation, the EEG signal feature acquisition module includes:

A quantity and value acquisition unit, used to count the number of peaks and/or troughs in the EEG signal to be recorded, and obtain the value of each peak and/or trough;

an average value obtaining unit, configured to obtain an average peak value and/or an average trough value according to the number and value.

In another possible implementation, the classification and marking module includes:

A numerical difference obtaining unit, used for obtaining the peak numerical value and/or the trough numerical value of the EEG signal to be recorded and the peak numerical value difference and/or the trough numerical value difference of the average peak numerical value and/or the average wave trough numerical value;

A classification unit, for if the absolute value of the peak value difference and/or the trough value difference is greater than a preset value difference threshold, the EEG signal to be recorded is an abnormal EEG signal; and, if the peak value difference And/or the absolute value of the trough numerical difference is smaller than the preset numerical difference threshold, the EEG signal to be recorded is a normal EEG signal.

In a third aspect, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the program, the EEG signal data recording method provided in the first aspect is realized. method.

In a fourth aspect, a non-transitory computer-readable storage medium is provided on which a computer program is stored, and when the computer program is executed by a processor, the method for recording EEG signal data as provided in the first aspect is provided.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments of the present application.

1 is a flowchart of a method for recording EEG signal data provided by an embodiment of the present invention;

2 is a flowchart of a method for recording EEG signal data provided by yet another embodiment of the present invention;

3 is a flowchart of a method for recording EEG signal data provided by another embodiment of the present invention;

4 is a structural diagram of a system for recording EEG signal data provided by an embodiment of the present invention;

5 is a structural diagram of a system for recording EEG signal data provided by yet another embodiment of the present invention;

6 is a structural diagram of a system for recording EEG signal data provided by another embodiment of the present invention;

FIG. 7 is a schematic diagram of the physical structure of an electronic device of the present invention.

specific implementation

The following describes in detail the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar modules or modules having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, but not to be construed as limiting the present invention.

It will be understood by those skilled in the art that the singular forms "a", "an", "the" and "the" as used herein can include the plural forms as well, unless expressly stated otherwise. It should be further understood that the word "comprising" used in the description of this application refers to the presence of the stated features, integers, steps, operations, modules and/or components, but does not preclude the presence or addition of one or more other features, Integers, steps, operations, modules, components and/or groups thereof. It will be understood that when we refer to a module as being "connected" or "coupled" to another module, it can be directly connected or coupled to the other module or intervening modules may also be present. Furthermore, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any and all combinations of one or more of the associated listed items.

In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation manner of the present application will be further described in detail below with reference to the accompanying drawings.

The technical solutions of the present application and the technical solutions of the present application, such as and solutions to the above-mentioned technical problems, will be described in detail below with specific examples. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

FIG. 1 is a flowchart of a method for recording EEG signal data provided by an embodiment of the present invention, and the method includes:

Step 101, acquiring the EEG signal to be recorded in the target EEG data, the EEG signal to be recorded is an EEG signal with nerve impulses;

Step 102, count the numerical value of the EEG signal to be recorded, and obtain the EEG signal feature of the target EEG data;

Step 103 , classify and mark the to-be-recorded EEG signals according to the features of the EEG signals, and the classification includes: normal EEG signals and abnormal EEG signals;

Step 104, classify and record the normal EEG signal and/or the abnormal EEG signal.

In this embodiment of the present invention, a piece of complete EEG data includes multiple EEG signals with short-term nerve impulse waveforms. When recording starts, an EEG signal with a neural impulse waveform can be extracted from a complete piece of EEG data through intuitive vision, and marked as the EEG signal to be recorded. The EEG signal to be recorded is a nerve impulse signal in the form of "peak-valley", and the EEG signal characteristics of the target EEG data can be obtained by counting the values of each peak and trough. Compare the EEG signal to be recorded with the characteristics of the EEG signal, classify the EEG signal to be recorded into normal EEG signal and abnormal EEG signal according to the comparison result, and record the corresponding EEG signal respectively. The index address to complete the classification and recording of EEG signals.

Wherein, the EEG signal features include: action potential threshold, waveform envelope feature points, number of peaks, number of troughs, duration and/or power spectral density.

Wherein, classifying and recording the normal EEG signal and/or abnormal EEG signal includes:

If the to-be-recorded EEG signal is a normal EEG signal, record the start time, peak/trough frequency, duration, and index address of the normal EEG signal; and,

If the to-be-recorded EEG signal is an abnormal EEG signal, record the start time, the frequency, duration, and index address of the abnormal EEG signal.

Specifically, the classifying and recording the normal EEG signal and/or the abnormal EEG signal includes: creating corresponding record information according to the normal EEG signal and/or the abnormal EEG signal to establish an index database, wherein , each piece of record information includes an index segment, a data segment and a signal type.

The index segment includes the index address of the EEG signal, the index address is the storage location of the EEG signal in the index library, and the data segment includes the action potential threshold of the EEG signal, the waveform envelope feature points, and the number of peaks. , the number of troughs, the duration and/or the power spectral density, the signal types include normal EEG, abnormal EEG and ambiguous EEG. Among them, the unclear EEG signal refers to the signal that cannot be determined at present whether it is an abnormal EEG signal or a normal EEG signal.

In a preferred embodiment, the data segment further includes the position of the brain tissue corresponding to the EEG signal.

In this embodiment of the present invention, the EEG signals to be recorded in the target EEG data are acquired, the values of the EEG signals to be recorded are counted, the EEG signal features of the target EEG data are obtained, and the EEG signals to be recorded are classified according to the EEG signal characteristics It is marked as a normal EEG signal and/or an abnormal EEG signal, and the corresponding index addresses are respectively recorded for the normal EEG signal and/or the abnormal EEG signal. The EEG signals in the EEG data are classified and recorded for statistics, which reduces the time for retrieving the EEG signals.

FIG. 2 is a flowchart of a method for recording EEG signal data provided by another embodiment of the present invention. The EEG signal characteristics of the target EEG data are obtained by counting the values of the EEG signal to be recorded. ,include:

Step 201, count the number of peaks and/or troughs in the EEG signal to be recorded in the set time period, and obtain the value of each peak and/or trough;

Step 202: Obtain an average peak value and/or an average trough value according to the number and value. In the embodiment of the present invention, the EEG signal features mainly include the average peak value and/or the average trough value, and the average peak value and/or the average trough value can be used as normal EEG signals and/or abnormal values in the subsequent process. EEG signal judgment basis.

FIG. 3 is a flowchart of a method for recording EEG signal data provided by another embodiment of the present invention. The classification and marking of the EEG signal to be recorded according to the EEG signal feature includes:

Step 301, obtaining the peak value difference and/or the trough value difference between the peak value and/or the trough value of the EEG signal to be recorded and the average peak value and/or the average trough value;

Step 302, if the absolute value of the peak value difference and/or the trough value difference is outside the threshold range, then the EEG signal to be recorded is an abnormal EEG signal; And, if the peak value difference and/or the trough value difference If the absolute value of the difference is within the threshold range, the EEG signal to be recorded is a normal EEG signal.

In the embodiment of the present invention, determining the type of the EEG signal is mainly based on the difference between the peak value and the average peak value of the EEG signal to be recorded, and the value difference between the trough value and the average trough value. Since the peaks and/or troughs of the EEG signals to be recorded may be larger than the average peaks and/or troughs, or may be smaller than the average peaks and/or troughs, after obtaining the peak value difference and/or the trough value difference, take the The absolute value of the peak value difference and/or the trough value difference. Compare the absolute value with the preset value difference threshold. If it is greater than the value difference threshold, the EEG signal to be recorded is a normal EEG signal. If it is smaller than the value difference threshold , the EEG signal to be recorded is abnormal EEG signal.

FIG. 4 is a structural diagram of a system for recording EEG signal data provided by an embodiment of the present invention, where the system includes:

The EEG signal acquisition module 401 to be recorded is used for acquiring the EEG signal to be recorded in the target EEG data, the EEG signal to be recorded is an EEG signal with nerve impulses;

An EEG signal feature acquisition module 402, configured to count the value of the EEG signal to be recorded, and obtain the EEG signal feature of the target EEG data;

The classification and marking module 403 is configured to classify and record the normal EEG signal and/or the abnormal EEG signal, and the classification includes: normal EEG signal and abnormal EEG signal;

The index address recording module 404 is configured to respectively record the corresponding index addresses for the normal EEG signal and/or the abnormal EEG signal.

In this embodiment of the present invention, a piece of complete EEG data includes multiple EEG signals with short-term nerve impulse waveforms. When recording starts, an EEG signal with a neural impulse waveform can be extracted from a complete piece of EEG data through intuitive vision, and marked as the EEG signal to be recorded. The EEG signal to be recorded is a nerve impulse signal in the form of "peak-valley", and the EEG signal characteristics of the target EEG data can be obtained by counting the values of each peak and trough. Compare the EEG signal to be recorded with the characteristics of the EEG signal, classify the EEG signal to be recorded into normal EEG signal and abnormal EEG signal according to the comparison result, and record the corresponding EEG signal respectively. The index address to complete the classification and recording of EEG signals.

Wherein, classifying and recording the normal EEG signal and/or abnormal EEG signal includes:

If the to-be-recorded EEG signal is a normal EEG signal, record the start time, peak/trough frequency, duration, and index address of the normal EEG signal; and,

If the to-be-recorded EEG signal is an abnormal EEG signal, record the start time, the frequency, duration, and index address of the abnormal EEG signal.

In this embodiment of the present invention, the EEG signals to be recorded in the target EEG data are acquired, the values of the EEG signals to be recorded are counted, the EEG signal features of the target EEG data are obtained, and the EEG signals to be recorded are classified according to the EEG signal characteristics It is marked as a normal EEG signal and/or an abnormal EEG signal, and the corresponding index addresses are respectively recorded for the normal EEG signal and/or the abnormal EEG signal. The EEG signals in the EEG data are classified and recorded for statistics, which reduces the time for retrieving the EEG signals.

FIG. 5 is a structural diagram of a system for recording EEG signal data provided by another embodiment of the present invention. The EEG signal feature acquisition module 402 includes:

Quantity and numerical value acquisition unit 501, used to count the number of peaks and/or troughs in the EEG signal to be recorded, and obtain the numerical value of each peak and/or trough;

The average value obtaining unit 502 is configured to obtain the average peak value and/or the average trough value according to the number and value.

In the embodiment of the present invention, the EEG signal features mainly include the average peak value and/or the average trough value, and the average peak value and/or the average trough value can be used as normal EEG signals and/or abnormal values in the subsequent process. EEG signal judgment basis.

FIG. 6 is a structural diagram of a system for recording EEG signal data provided by another embodiment of the present invention. The classification and marking module 403 includes:

Numerical difference obtaining unit 601, for obtaining the peak value difference and/or the trough value of the EEG signal to be recorded and the peak value difference and/or the trough value of the average peak value and/or the average trough value;

Classification unit 602, for if the absolute value of the peak value difference and/or the trough value difference is greater than a preset value difference threshold, the EEG signal to be recorded is an abnormal EEG signal; and, if the peak value If the absolute value of the difference and/or the trough numerical difference is smaller than the preset numerical difference threshold, the EEG signal to be recorded is a normal EEG signal.

In the embodiment of the present invention, determining the type of the EEG signal is mainly based on the difference between the peak value and the average peak value of the EEG signal to be recorded, and the value difference between the trough value and the average trough value. Since the peaks and/or troughs of the EEG signals to be recorded may be larger than the average peaks and/or troughs, or may be smaller than the average peaks and/or troughs, after obtaining the peak value difference and/or the trough value difference, take the The absolute value of the peak value difference and/or the trough value difference. Compare the absolute value with the preset value difference threshold. If it is greater than the value difference threshold, the EEG signal to be recorded is a normal EEG signal. If it is smaller than the value difference threshold , the EEG signal to be recorded is abnormal EEG signal.

FIG. 7 illustrates a schematic diagram of the physical structure of an electronic device. As shown in FIG. 7 , the electronic device may include: a processor (processor) 701, a communication interface (Communications Interface) 702, a memory (memory) 703, and a communication bus 704, Among them, the processor, the communication interface, and the memory communicate with each other through the communication bus. The processor can call the logic instructions in the memory to perform a method for recording EEG signal data, the method comprising: acquiring EEG signals to be recorded in the target EEG data, the EEG signals to be recorded are brains with nerve impulses electrical signals; count the values of the EEG signals to be recorded, and obtain the EEG signal features of the target EEG data; classify and mark the EEG signals to be recorded according to the EEG signal features, and the classification includes : normal EEG signal, abnormal EEG signal; classify and record the normal EEG signal and/or abnormal EEG signal.

In addition, the above-mentioned logic instructions in the memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk and other media that can store program codes .

On the other hand, an embodiment of the present invention also provides a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, when the program instructions When executed by the computer, the computer can execute the method for recording EEG signal data provided by the above method embodiments, the method includes: acquiring the EEG signal to be recorded in the target EEG data, the EEG signal to be recorded is a EEG signals of nerve impulses; count the values of the EEG signals to be recorded, and obtain EEG signal characteristics of the target EEG data; classify and mark the EEG signals to be recorded according to the EEG signal characteristics, The classification includes: normal EEG signals, abnormal EEG signals; classifying and recording the normal EEG signals and/or abnormal EEG signals.

In yet another aspect, an embodiment of the present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored, and the computer program is implemented by a processor to execute the EEG signal data recording provided by the above-mentioned embodiments. The method includes: acquiring the EEG signal to be recorded in the target EEG data, the EEG signal to be recorded is an EEG signal with nerve impulses; EEG signal features of the target EEG data; classify and mark the EEG signals to be recorded according to the EEG signal features, and the classification includes: normal EEG signals and abnormal EEG signals; Signals and/or abnormal EEG signals are classified and recorded.

It should be understood that although the various steps in the flowchart of the accompanying drawings are sequentially shown in the order indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order and may be performed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but may be executed at different times, and the execution sequence is also It does not have to be performed sequentially, but may be performed alternately or alternately with other steps or at least a portion of sub-steps or stages of other steps.

The above are only partial implementations of the present invention. It should be pointed out that for those skilled in the art, without departing from the principles of the present invention, several improvements and modifications can also be made. It should be regarded as the protection scope of the present invention.

Claims (10)

1. a method for EEG data recording, characterized in that the method comprises: Obtaining the EEG signal to be recorded in the target EEG data, the EEG signal to be recorded is an EEG signal with nerve impulses; obtaining the EEG signal characteristics of the target EEG data; Classify and mark the to-be-recorded EEG signals according to the features of the EEG signals, and the classification includes: normal EEG signals and abnormal EEG signals; The normal EEG signal and/or the abnormal EEG signal are classified and recorded. 2. The method according to claim 1, wherein the classifying and recording the normal EEG signal and/or the abnormal EEG signal comprises: Corresponding record information is created according to the normal EEG signal and/or the abnormal EEG signal, wherein each piece of the record information includes an index segment, a data segment and a signal type. 3. The method according to claim 2, wherein the index segment includes an index address of an EEG signal, and the data segment includes an action potential threshold, a waveform envelope feature point, a number of peaks, and a trough of the EEG signal. Quantity, duration and/or power spectral density, the signal types include normal EEG, abnormal EEG and ambiguous EEG. 4. The method of claim 1, wherein the EEG signal features include: action potential threshold, waveform envelope feature points, number of peaks, number of troughs, duration and/or power spectral density. 5. The method of claim 1, wherein the acquiring the electroencephalographic signal characteristics of the target electroencephalographic data comprises: Counting the number of peaks and/or troughs in the EEG signal to be recorded in the set time period, and obtaining the value of each peak and/or trough; Based on the numbers and values, an average peak value and/or an average trough value are obtained. 6. The method according to claim 5, wherein the classifying and marking the to-be-recorded EEG signal according to the EEG signal feature comprises: Obtain the peak value difference and/or the trough value difference between the peak value and/or the trough value of the EEG signal to be recorded and the average peak value and/or the average trough value; If the absolute value of the peak value difference and/or the trough value difference is outside the threshold range, the EEG signal to be recorded is an abnormal EEG signal; and, if the absolute value of the peak value difference and/or the trough value difference is If the value is within the threshold range, the EEG signal to be recorded is a normal EEG signal. 7. A system for EEG signal data recording, wherein the system comprises: a to-be-recorded EEG signal acquisition module, configured to acquire the to-be-recorded EEG signal in the target EEG data, where the to-be-recorded EEG signal is an EEG signal with nerve impulses; an EEG signal feature acquisition module, configured to count the value of the EEG signal to be recorded, and obtain the EEG signal feature of the target EEG data; A classification and marking module, configured to classify and record the normal EEG signal and/or the abnormal EEG signal, and the classification includes: normal EEG signal and abnormal EEG signal; The index address recording module is used to respectively record the corresponding index addresses of the normal EEG signal and/or the abnormal EEG signal. 8. The system of claim 7, wherein the EEG signal feature acquisition module comprises: A quantity and value acquisition unit, used to count the number of peaks and/or troughs in the EEG signal to be recorded, and obtain the value of each peak and/or trough; an average value obtaining unit, configured to obtain an average peak value and/or an average trough value according to the number and value. 9. An electronic device, comprising a memory, a processor and a computer program stored on the memory and running on the processor, wherein the processor implements any one of claims 1-6 when the processor executes the program The method for EEG signal data recording described in item. 10. A non-transitory computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the EEG signal data according to any one of claims 1-6 is realized method of recording.

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