CN119339892A - A real-time evaluation system for acupuncture treatment effects based on brain-computer interface technology - Google Patents
A real-time evaluation system for acupuncture treatment effects based on brain-computer interface technology Download PDFInfo
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Abstract
本发明公开了一种基于脑机接口技术的针灸治疗效果实时评估系统，属于针灸疗效评估技术领域，包括脑机数据收集模块、针灸数据采集模块、疗效实时评估模块、患者画像生成模块、长时疗效综合评估模块，所述脑机数据收集模块，包括脑电传感器，基于非侵入性脑机接口技术，收集治疗前与治疗过程中患者的脑电信号，并传输至后续模块中，所述针灸数据采集模块，包括高清摄像头，用以收集治疗过程中医生的动作，用以判定当前患者治疗过程中的施针穴位、施针深度。本发明一种基于脑机接口技术的针灸治疗效果实时评估系统，通过结合脑机接口技术和针灸治疗特点，基于患者的个体差异建立针灸效果实时评估方案，以提高针灸治疗的精准性和有效性。
The present invention discloses a real-time evaluation system for acupuncture treatment effect based on brain-computer interface technology, which belongs to the technical field of acupuncture treatment effect evaluation, including a brain-computer data collection module, an acupuncture data collection module, a real-time treatment effect evaluation module, a patient portrait generation module, and a long-term treatment effect comprehensive evaluation module. The brain-computer data collection module includes an electroencephalogram sensor, which collects the electroencephalogram signals of the patient before and during treatment based on non-invasive brain-computer interface technology, and transmits them to subsequent modules. The acupuncture data collection module includes a high-definition camera, which is used to collect the doctor's actions during the treatment process, and is used to determine the acupuncture points and acupuncture depths during the current patient's treatment process. The present invention discloses a real-time evaluation system for acupuncture treatment effect based on brain-computer interface technology, which combines brain-computer interface technology and acupuncture treatment characteristics, and establishes a real-time evaluation scheme for acupuncture effect based on individual differences of patients to improve the accuracy and effectiveness of acupuncture treatment.
Description
Technical Field
The invention belongs to the technical field of acupuncture treatment effect evaluation, and particularly relates to an acupuncture treatment effect real-time evaluation system based on brain-computer interface technology.
Background
Acupuncture is one of the important components of Chinese medicine, and includes two methods, needle and moxibustion, the needle is to penetrate certain acupoints of human body with special needle to treat diseases, the moxibustion is to burn moxa or other inflammable material in specific parts of body surface to heat stimulation for treating diseases, and modern acupuncture is usually needle punched mainly;
Because of individual differences of patients, in the process of performing acupuncture, the needle application method and the needle application depth can be different under the feeling of different patients, meanwhile, the treatment effects of different patients can be different by the needle application method and the needle application depth, the conventional acupuncture treatment effect real-time evaluation system is difficult to evaluate the acupuncture treatment effect in the treatment process in real time according to the individual differences, meanwhile, the individual differences of the patients cannot be evaluated based on the needle application method and the needle application depth, and the problems of low practicability and low functionality exist;
Aiming at the above, the scheme provides a brain-computer interface technology-based acupuncture treatment effect real-time evaluation system so as to solve the technical problems.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides a brain-computer interface technology-based acupuncture treatment effect real-time evaluation system, which solves the technical problems by improving the detection mode and the processing mode.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
the system comprises a brain-computer data collection module, an acupuncture data acquisition module, a curative effect real-time evaluation module, a patient portrait generation module and a long-time curative effect comprehensive evaluation module;
The brain-computer data collection module comprises an electroencephalogram sensor, collects electroencephalogram signals of a patient before and during treatment based on a non-embedded brain-computer interface technology, and transmits the electroencephalogram signals to the subsequent module;
the acupuncture data acquisition module comprises a high-definition camera, is used for collecting actions of doctors in the treatment process, is used for judging Shi Zhen acupuncture points, needle application depth and needle application methods in the current treatment process of patients, and transmits related data into the follow-up module;
The curative effect real-time evaluation module is used for collecting the electroencephalogram signal data of different patients in the current disease state in the treatment process based on the historical diagnosis and treatment data, determining the treatment effect influence parameters, and carrying out real-time evaluation on the treatment effect of the patients by combining the electroencephalogram signal change of the current patients in the treatment process;
the patient portrait generation module is used for generating a treatment portrait of the patient based on the needle application technique and the needle application depth of a doctor in the acupuncture treatment process, correlating treatment feedback electroencephalogram signals of the current patient, including the treatment sensitivity and the treatment effect improvement degree of the patient, and comprehensively determining the optimal treatment scheme;
The long-term efficacy comprehensive evaluation module is used for setting a long-term efficacy evaluation node based on the treatment period of the patient, and performing long-term efficacy evaluation on the patient in the current period by combining the patient-specific efficacy evaluation score in the period.
Further, the acupuncture data acquisition module comprises a high-definition camera, is used for collecting actions of doctors in the treatment process, is used for judging Shi Zhen acupoints, needle application depth and needle application methods in the current patient treatment process, and transmits related data to a subsequent module, and comprises the following steps:
Capturing the needle application action of a doctor through a high-definition camera, collecting a video stream in the treatment process, identifying a human body part in the video stream through a target detection algorithm, recording characteristic parameters of the needle application part, and determining the needle application acupuncture point of the current patient through cosine similarity comparison;
extracting needle initial length in video stream by target detection algorithm Combined with the residual length of the needle body after needle applicationCalculating to obtain the needle application depth;
For different acupuncture manipulations, collecting high-definition video data of various acupuncture manipulations performed by different doctors, extracting key features of Shi Zhen hand movements, including movement types, movement directions and movement amplitudes, respectively establishing training sets and testing sets for different acupuncture manipulations, training an acupuncture manipulation model through a convolutional neural network, substituting the acupuncture feature data in the current video stream into the trained neural network acupuncture manipulation model frame by frame, calculating the matching degree of the current frame and each known manipulation model, and judging the acupuncture manipulation based on similarity values.
Further, the therapeutic effect real-time evaluation module collects electroencephalogram data of different patients in the current disease based on historical diagnosis and treatment data, determines a therapeutic effect influence parameter, and evaluates the therapeutic effect of the patient in real time by combining the electroencephalogram change of the current patients in the therapeutic process, wherein the specific steps are as follows:
Collecting diagnosis and treatment data of patients under the same disease history, dividing brain electrical signal frequency bands by combining brain electrical signal data of different patients under the current disease, distinguishing active brain electrical signal frequency bands from passive brain electrical signal frequency bands, determining treatment effect influence parameters, and carrying out real-time evaluation on treatment effects of the patients by combining brain electrical signal changes of the current patients in the treatment process, wherein the method comprises the following specific steps of:
Dividing the electroencephalogram signals into different frequency bands according to the fluctuation frequency range of the electroencephalogram signals of the patient in the history treatment process, converting the acquired electroencephalogram signals from a time domain to a frequency domain through fast Fourier transform, calculating the power spectral density of each frequency component, and determining the signal characteristics of the different frequency bands;
Based on the historical disease diagnosis and treatment data set and the current treatment feedback and symptom change condition of the patient, judging the association of different frequency bands and treatment effects, namely recording the fluctuation frequency band of the patient when the symptoms of the patient are relieved and the fluctuation frequency band of the patient when the pain is aggravated or the symptoms are aggravated, dividing the former into active electroencephalogram frequency bands and the latter into passive electroencephalogram frequency bands;
According to the power spectral density of each frequency band of the patient before treatment, the fluctuation values of different frequency bands in the active frequency bands and the fluctuation values of different frequency bands in the passive frequency bands are obtained by combining the power spectral density of each frequency band after treatment is completed, the products of the frequency bands are accumulated by multiplying the fluctuation values of the frequency bands and the corresponding weight coefficients of the frequency bands, the products of the frequency bands in the active frequency bands are accumulated, the products of the polar frequency bands are accumulated, and finally the accumulated values of the active frequency band and the accumulated values of the passive frequency bands are summed to obtain a real-time treatment effect evaluation score in the treatment process, wherein when the real-time treatment effect evaluation score is larger than 0, the positive treatment effect is represented, and when the real-time treatment effect evaluation score is smaller than 0, the negative treatment effect is represented.
Further, the patient portrait generation module is used for generating a treatment portrait of the patient based on the needle application method and the needle application depth of a doctor in the acupuncture treatment process and the treatment feedback brain electric signal of the current patient, and comprises the following specific steps of comprehensively determining the optimal treatment scheme:
Establishing a time stamp based on the change of the brain electrical signal in the treatment process of the patient, and simultaneously establishing a time stamp for acupuncture data in the treatment process of the patient synchronously, and correlating the acupuncture data and brain-computer data in the treatment process of the current patient;
Based on the dividing result of the feedback electroencephalogram signal in the curative effect real-time evaluation module, active feedback electroencephalogram signal data and passive feedback electroencephalogram signal data are obtained, and the relevance of the relevant feedback electroencephalogram signal data and acupuncture data is combined to generate a treatment portrait of the patient, wherein the treatment portrait comprises the treatment sensitivity and the treatment effect improvement degree of different acupuncture data on the patient, and the optimal treatment scheme is comprehensively determined.
Furthermore, the time stamp is established based on the change of the brain electrical signal in the treatment process of the patient, and simultaneously the time stamp is established for the acupuncture data in the treatment process of the patient, and the acupuncture data and the brain-computer data in the treatment process of the current patient are associated, which comprises the following specific steps:
Based on different acupuncture manipulations, establishing corresponding time stamps generated by the acupuncture depth and the fluctuation of different electroencephalogram signal frequency bands under the corresponding acupuncture manipulations, and calculating electroencephalogram signal frequency bands positively or negatively related to the acupuncture depth under the corresponding acupuncture manipulations, wherein the specific steps are as follows:
in the electroencephalogram data, marking the acupuncture manipulation and the acupuncture depth corresponding to each time point, matching the power spectral density of a specific frequency band of fluctuation in the electroencephalogram according to the time stamp, and calculating the correlation between the acupuncture depth under the current acupuncture manipulation and the characteristic fluctuation of the corresponding electroencephalogram through the pearson correlation coefficient:
The pearson correlation coefficient between the acupuncture depth and the power spectral density fluctuation of different specific frequency bands of the electroencephalogram signals under the current acupuncture manipulation is calculated respectively, and a specific algorithm formula is as follows:
;
Wherein, Representing the depth of the acupuncture under the acupuncture technique Q,Represents the fluctuation power spectral density value of the electroencephalogram signal under the frequency band a,The pearson correlation coefficient representing the acupuncture depth under the acupuncture technique Q to the electroencephalogram signal fluctuation power spectral density value under the frequency band a;
Wherein, The number of (C) ranges from-1 to 1 when<0, The needle application depth y is inversely related to the frequency band a under the acupuncture technique Q, i.e. when one variable is increased, the other variable is decreased;
When (when) When the pressure is approximately equal to 0, the needle application depth y is irrelevant to the frequency band a under the acupuncture technique Q, namely, when one variable is increased or decreased, the other variable is not changed;
When (when) At >0, the depth y of the needle is positively correlated with the frequency band a, i.e., one variable increases while the other variable increases.
Further, the dividing result of the feedback brain electrical signal based on the curative effect real-time evaluation module obtains the active feedback brain electrical signal data and the passive feedback brain electrical signal data, combines the relevance of the relevant feedback brain electrical signal data and the acupuncture data, and generates the treatment portrait of the patient, which comprises the treatment sensitivity and the treatment effect improvement degree of different acupuncture data to the patient, and comprehensively determines the optimal treatment scheme, and the specific steps are as follows:
Counting a frequency band a which has correlation with the needle application depth y under the same acupuncture technique Q, establishing a patient acupuncture database through MySQL, establishing a patient portrait file in the database, carrying out file subdivision based on the type of the acupuncture technique Q, respectively establishing files with shallow, medium and deep needle application depths in each acupuncture technique Q file, establishing positive correlation frequency band, negative correlation frequency band and uncorrelated frequency band files in the files with shallow, medium and deep needle application depths, and respectively establishing active frequency band files and negative frequency band files in each positive correlation frequency band, negative correlation frequency band and uncorrelated frequency band file;
Respectively inducing the frequency bands divided according to the pearson correlation coefficient into each positive correlation frequency band, each negative correlation frequency band and each uncorrelated frequency band file in combination with the needle application depth, and further dividing the frequency bands into an active frequency band file and a passive frequency band file in combination with the frequency band attribute divided by the curative effect real-time evaluation module;
Respectively calculating the acupuncture sensitivity and the treatment improvement degree under different acupuncture manipulation Q and different needle application depth conditions, the method comprises the following specific steps:
For the sensitivity of acupuncture, statistics is carried out on the extraction of all the pearson correlation coefficients of the negative frequency bands from the negative correlation frequency bands under the current acupuncture technique Q Calculating the magnitude of the influence of the inversely related frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of negative bands in the negative correlation band profile,Is the negative correlation coefficient in which the frequency band is negative,Is the product of the absolute value of the negative correlation coefficient and the number of negative frequency bands;
counting all passive frequency band pearson correlation coefficients extracted from positive correlation frequency band under current acupuncture technique Q Calculating the influence size of the positively correlated frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of passive bands in the positive correlation band profile,Is the positive correlation coefficient in which the frequency band is negative,Is the product of the absolute value of the positive correlation coefficient and the number of the negative frequency bands, is synthesizedAnd (3) withObtaining the sensitivity of the acupuncture of the patientWherein,The larger the acupuncture sensitivity of the current treatment is, the larger the acupuncture sensitivity is, and the different needle application depths are calculated;
For the improvement degree of the treatment effect, statistics is carried out on the extraction of all positive frequency band pearson correlation coefficients from the negative correlation frequency bands under the current acupuncture technique QCalculating the magnitude of the influence of the inversely related frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of active bands in the inversely related band profile,Is the negative correlation coefficient of the active frequency band therein,Is the product of the absolute value of the negative correlation coefficient and the number of active frequency bands;
counting all positive frequency band pearson correlation coefficients extracted from positive correlation frequency bands under the current acupuncture technique Q Calculating the influence size of the positively correlated frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of active bands in the positive correlation band profile,Is the positive correlation coefficient in which the frequency band is aggressive,Is the product of the absolute value of the positive correlation coefficient and the number of active frequency bands, is synthesizedAnd (3) withObtaining the sensitivity of the acupuncture of the patientWherein,The larger the treatment effect of the current treatment is, the larger the degree of improvement is, and the different needle application depths are calculated;
Calculating the comprehensive influence degree under different needle application depthsWhen (when)0 Represents that the therapeutic effect is positive when<0 Represents the negative therapeutic effect by applying different acupuncture techniques and depths of needlesThe 0 condition is arranged in a descending order, the acupuncture manipulation and the acupuncture depth under the first arrangement are selected as the specific treatment scheme of the current patient, and the different acupuncture depths under different acupuncture manipulations are recorded in the patient image fileValues.
Further, the curative effect real-time evaluation module further comprises a step of generating a patient treatment specific curative effect evaluation score based on a patient portrait file established in the current patient treatment process in the patient portrait generation module and combining the acupuncture technique and the needle application depth in the current patient treatment process;
The acupuncture and moxibustion technique and the acupuncture and moxibustion depth of each acupuncture and moxibustion applied in the current treatment process are obtained through an acupuncture and moxibustion data acquisition module, and the comprehensive influence degree of different acupuncture and moxibustion techniques of different patients based on the current patient image file is obtained Calculating to obtain the evaluation score of the specific curative effect of the treatment of the patient, wherein the algorithm formula is as follows:
;
Wherein, Represents the evaluation score of the specific curative effect of the current treatment of the patient, and i represents the administration frequency of the current treatment of the patient.
Further, the long-term efficacy comprehensive evaluation module sets a long-term efficacy evaluation node based on the treatment period of the patient, and performs long-term efficacy evaluation on the patient in the current period by combining the patient-specific efficacy evaluation score in the period, and the specific steps are as follows:
Setting a long-term efficacy evaluation node based on the number of treatments n in the current patient treatment cycle and on the number of intervals T, dividing the patient treatment cycle into A step of counting each treatment time in the current stepValues for each phase after the patient treatment phase is completedValues were recorded and a line graph was drawn.
Further, the brain-computer data collection module comprises an electroencephalogram sensor, collects brain electrical signals of a patient before treatment and in the treatment process based on a non-invasive brain-computer interface technology, and transmits the brain electrical signals to a subsequent module, and the specific steps are as follows:
The method comprises the steps of selecting a proper electroencephalogram sensor, including a non-invasive dry electrode and a non-invasive wet electrode, placing the electroencephalogram sensor on forehead and scalp areas of a patient, capturing electroencephalogram signal frequency bands before and during treatment of the patient through a non-invasive brain-computer interface technology, and adding a time stamp to each electroencephalogram signal sample.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, by arranging the patient portrait generation module, according to the difference of individual differences of different patients, the influences generated by the acupuncture depths of different patients under different acupuncture techniques are counted and collected respectively, and the acupuncture sensitivity and the treatment effect promotion degree of different patients are obtained in a differentiated manner through the different patient negative frequency bands recorded in the file, so that the acupuncture effect of the patients is evaluated in a targeted manner, and the pertinence of the system is enhanced;
According to the invention, the comprehensive influence degree of the patient under different acupuncture techniques and needle application depths is calculated, so that an optimal acupuncture scheme is adopted for assisting a doctor to perform acupuncture treatment on the patient according to the current condition of the patient, objective index support is provided for the acupuncture treatment effect, real-time optimization of the treatment scheme of the patient in the acupuncture treatment process is facilitated, and the practicability of the system is enhanced;
according to the invention, by combining a curative effect real-time evaluation module with a non-invasive brain-computer technology, the treatment effect of a patient is evaluated in real time in the acupuncture treatment process, so that discomfort or adverse reaction of the patient in the treatment process can be found in time, excessive stimulation is avoided, and meanwhile, real-time data can help doctors to optimize acupuncture treatment parameters including acupuncture depth and acupuncture application technique, so that the functionality of the system is enhanced;
in the invention, the individual of the patient is subjected to specific treatment effect evaluation, treatment phases are divided by combining treatment periods, specific treatment effect evaluation scores are counted under each treatment phase, a line graph is drawn, the specific treatment response of each patient is known in detail, the treatment progress is monitored in real time by counting the evaluation scores in each treatment phase, and the treatment strategy is adjusted in time so as to improve the treatment effect;
The whole brain-computer interface technology-based acupuncture treatment effect real-time evaluation system establishes an acupuncture effect real-time evaluation scheme based on individual differences of patients by combining brain-computer interface technology and acupuncture treatment characteristics so as to improve the accuracy and effectiveness of acupuncture treatment.
Drawings
Fig. 1 is a block diagram of a system for evaluating the therapeutic effect of acupuncture based on brain-computer interface technology in real time according to the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment 1, as shown in fig. 1, a brain-computer interface technology-based acupuncture treatment effect real-time evaluation system comprises a brain-computer data collection module, an acupuncture data acquisition module, a treatment effect real-time evaluation module, a patient portrait generation module and a long-time treatment effect comprehensive evaluation module;
The brain-computer data collection module comprises an electroencephalogram sensor, is based on a non-embedded brain-computer interface technology, collects electroencephalogram signals of a patient before treatment and in the treatment process, and transmits the electroencephalogram signals to the subsequent module, and comprises the following specific steps:
Selecting proper electroencephalogram sensors, including non-invasive dry electrodes and wet electrodes, for placing on forehead and scalp areas of a patient, capturing electroencephalogram signal frequency bands of the patient before and during treatment through a non-invasive brain-computer interface technology, and adding a time stamp to each electroencephalogram signal sample;
The acupuncture data acquisition module comprises a high-definition camera, is used for collecting actions of doctors in the treatment process, is used for judging Shi Zhen acupoints, needle application depth and needle application methods in the current patient treatment process, and transmits related data to a subsequent module, and comprises the following steps:
Capturing the needle application action of a doctor through a high-definition camera, collecting a video stream in the treatment process, identifying a human body part in the video stream through a target detection algorithm, recording characteristic parameters of the needle application part, and determining the needle application acupuncture point of the current patient through cosine similarity comparison;
extracting needle initial length in video stream by target detection algorithm Combined with the residual length of the needle body after needle applicationCalculating to obtain the needle application depth;
For different acupuncture manipulations, collecting high-definition video data of various acupuncture manipulations performed by different doctors, extracting key features of Shi Zhen hand movements, including movement types, movement directions and movement amplitudes, respectively establishing training sets and testing sets for different acupuncture manipulations, training an acupuncture manipulation model through a convolutional neural network, substituting the acupuncture feature data in the current video stream into the trained neural network acupuncture manipulation model frame by frame, calculating the matching degree of the current frame and each known manipulation model, and judging the acupuncture manipulation based on similarity values.
In the process of extracting key features of hand motions, the key features of hand motions need to be marked frame by an acupuncture expert with abundant experience, the acupuncture techniques comprise an interpolation method, a twist interpolation method, a flat interpolation method and the like, the motion types comprise interpolation, twist and the like, feature models of different acupuncture techniques are respectively established through a convolutional neural network, the matching degree of a current frame and each known technique feature model is calculated through the feature models in combination with the input features, and the current acupuncture technique is judged by combining a similarity threshold, namely when the similarity of the current acupuncture technique and each feature model is greater than the similarity threshold of a certain feature model, the current acupuncture technique is represented as the acupuncture technique represented by the feature model.
The treatment effect real-time evaluation module is used for collecting the electroencephalogram signal data of different patients in the current disease state based on the historical diagnosis and treatment data, determining treatment effect influence parameters, carrying out real-time evaluation on the treatment effect of the patients by combining the electroencephalogram signal change of the current patients in the treatment process, collecting the electroencephalogram signal data of different patients in the current disease state based on the historical diagnosis and treatment data, determining treatment effect influence parameters, carrying out real-time evaluation on the treatment effect of the patients by combining the brain-computer signal change of the current patients in the treatment process, and comprises the following specific steps:
Collecting diagnosis and treatment data of patients under the same disease history, dividing brain electrical signal frequency bands by combining brain electrical signal data of different patients under the current disease, distinguishing active brain electrical signal frequency bands from passive brain electrical signal frequency bands, determining treatment effect influence parameters, and carrying out real-time evaluation on treatment effects of the patients by combining brain electrical signal changes of the current patients in the treatment process, wherein the method comprises the following specific steps of:
Dividing the electroencephalogram signals into different frequency bands according to the fluctuation frequency range of the electroencephalogram signals of the patient in the history treatment process, converting the acquired electroencephalogram signals from a time domain to a frequency domain through fast Fourier transform, calculating the power spectral density of each frequency component, and determining the signal characteristics of the different frequency bands;
Based on the historical disease diagnosis and treatment data set and the current treatment feedback and symptom change condition of the patient, judging the association of different frequency bands and treatment effects, namely recording the fluctuation frequency band of the patient when the symptoms of the patient are relieved and the fluctuation frequency band of the patient when the pain is aggravated or the symptoms are aggravated, dividing the former into active electroencephalogram frequency bands and the latter into passive electroencephalogram frequency bands;
According to the power spectral density of each frequency band of the patient before treatment, the fluctuation values of different frequency bands in the active frequency bands and the fluctuation values of different frequency bands in the passive frequency bands are obtained by combining the power spectral density of each frequency band after treatment is completed, the products of the frequency bands are accumulated by multiplying the fluctuation values of the frequency bands and the corresponding weight coefficients of the frequency bands, the products of the frequency bands in the active frequency bands are accumulated, the products of the polar frequency bands are accumulated, and finally the accumulated values of the active frequency band and the accumulated values of the passive frequency bands are summed to obtain a real-time treatment effect evaluation score in the treatment process, wherein when the real-time treatment effect evaluation score is larger than 0, the positive treatment effect is represented, and when the real-time treatment effect evaluation score is smaller than 0, the negative treatment effect is represented.
It should be noted that, the weight coefficient of each frequency band in the active frequency band and the weight coefficient of each frequency band in the passive frequency band need to be set according to the treatment results represented by different frequency bands in the history data and by combining the experience of the expert in the related field, wherein the fluctuation value comprises positive and negative values, so the accumulated positive frequency band accumulation value and the accumulated negative frequency band accumulation value also comprise positive and negative values, and the fluctuation value is the real-time power spectral density value of the related frequency band minus the initial power spectral density value of the frequency band in the treatment process.
Embodiment 2, a patient portrait generation module, based on the needle application technique and needle application depth of a doctor in the acupuncture treatment process, correlates the treatment feedback brain electric signal of the current patient, generates the treatment portrait of the patient, comprises the treatment sensitivity and the treatment effect improvement degree of the patient, and comprehensively determines the optimal treatment scheme, and specifically comprises the following steps:
Establishing a time stamp based on the change of the brain electrical signal in the treatment process of the patient, simultaneously synchronously establishing the time stamp for the acupuncture data in the treatment process of the patient, and correlating the acupuncture data and the brain-computer data in the treatment process of the current patient, wherein the specific steps are as follows:
Based on different acupuncture manipulations, establishing corresponding time stamps generated by the acupuncture depth and the fluctuation of different electroencephalogram signal frequency bands under the corresponding acupuncture manipulations, and calculating electroencephalogram signal frequency bands positively or negatively related to the acupuncture depth under the corresponding acupuncture manipulations, wherein the specific steps are as follows:
in the electroencephalogram data, marking the acupuncture manipulation and the acupuncture depth corresponding to each time point, matching the power spectral density of a specific frequency band of fluctuation in the electroencephalogram according to the time stamp, and calculating the correlation between the acupuncture depth under the current acupuncture manipulation and the characteristic fluctuation of the corresponding electroencephalogram through the pearson correlation coefficient:
The pearson correlation coefficient between the acupuncture depth and the power spectral density fluctuation of different specific frequency bands of the electroencephalogram signals under the current acupuncture manipulation is calculated respectively, and a specific algorithm formula is as follows:
;
Wherein, Representing the depth of the acupuncture under the acupuncture technique Q,Represents the fluctuation power spectral density value of the electroencephalogram signal under the frequency band a,The pearson correlation coefficient representing the acupuncture depth under the acupuncture technique Q to the electroencephalogram signal fluctuation power spectral density value under the frequency band a;
It should be noted that, the acupuncture technique Q is an acupuncture technique in an acupuncture technique model trained by the acupuncture data acquisition module, including an interpolation method, a twist interpolation method, a flat interpolation method, and the like, the frequency band a is a treatment effect influence parameter determined by the treatment effect real-time evaluation module based on the historical diagnosis and treatment data, the frequency band is divided into a positive frequency band and a negative frequency band, and the influence of the acupuncture depth under the same acupuncture technique on the frequency band is calculated, so that the influence of different acupuncture techniques and the acupuncture depth on different electroencephalogram frequency bands can be determined, and the doctor is assisted in adjusting the acupuncture treatment scheme.
Wherein, The number of (C) ranges from-1 to 1 when<0, The needle application depth y is inversely related to the frequency band a under the acupuncture technique Q, i.e. when one variable is increased, the other variable is decreased;
When (when) When the pressure is approximately equal to 0, the needle application depth y is irrelevant to the frequency band a under the acupuncture technique Q, namely, when one variable is increased or decreased, the other variable is not changed;
When (when) At >0, the depth y of the needle is positively correlated with the frequency band a, i.e., one variable increases while the other variable increases.
It should be noted that the number of the substrates,The number of (C) ranges from-1 to 1, i.e. whenThe closer to 1, the stronger the positive correlation representing the two variables, whenThe closer to-1, the stronger the negative correlation of the two variables is represented, whenThe closer to 0, the weaker the correlation representing the two variables, when<0, The power spectral density of the corresponding EEG signal decreases when the acupuncture depth increases, whenWhen >0, the power spectral density of the corresponding electroencephalogram signal increases when the depth of acupuncture increases.
Based on the dividing result of the feedback electroencephalogram signal in the curative effect real-time evaluation module, active feedback electroencephalogram signal data and passive feedback electroencephalogram signal data are obtained, and the relevance of relevant feedback electroencephalogram signal data and acupuncture data is combined to generate a treatment portrait of a patient, wherein the treatment portrait comprises the treatment sensitivity and the treatment effect improvement degree of different acupuncture data on the patient, and the treatment optimal scheme is comprehensively determined, and the specific steps are as follows:
Counting a frequency band a which has correlation with the needle application depth y under the same acupuncture technique Q, establishing a patient acupuncture database through MySQL, establishing a patient portrait file in the database, carrying out file subdivision based on the type of the acupuncture technique Q, respectively establishing files with shallow, medium and deep needle application depths in each acupuncture technique Q file, establishing positive correlation frequency band, negative correlation frequency band and uncorrelated frequency band files in the files with shallow, medium and deep needle application depths, and respectively establishing active frequency band files and negative frequency band files in each positive correlation frequency band, negative correlation frequency band and uncorrelated frequency band file;
It should be noted that, the division of the needle application depth is determined according to the requirements of the expert of traditional Chinese medicine in the related field, the needle application depth is usually about 0.5-1.0 cm for the needle, about 1.0-2.5 cm for the needle in Shi Zhen depth, and more than 2.5 cm for the needle in skin, and the needle application depth is obtained by the target detection algorithm in the acupuncture data acquisition module And (5) performing preset threshold setting to divide the depth grade of the current needle application.
Respectively inducing the frequency bands divided according to the pearson correlation coefficient into each positive correlation frequency band, each negative correlation frequency band and each uncorrelated frequency band file in combination with the needle application depth, and further dividing the frequency bands into an active frequency band file and a passive frequency band file in combination with the frequency band attribute divided by the curative effect real-time evaluation module;
Respectively calculating the acupuncture sensitivity and the treatment improvement degree under different acupuncture manipulation Q and different needle application depth conditions, the method comprises the following specific steps:
For the sensitivity of acupuncture, statistics is carried out on the extraction of all the pearson correlation coefficients of the negative frequency bands from the negative correlation frequency bands under the current acupuncture technique Q Calculating the magnitude of the influence of the inversely related frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of negative bands in the negative correlation band profile,Is the negative correlation coefficient in which the frequency band is negative,Is the product of the absolute value of the negative correlation coefficient and the number of negative frequency bands;
counting all passive frequency band pearson correlation coefficients extracted from positive correlation frequency band under current acupuncture technique Q Calculating the influence size of the positively correlated frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of passive bands in the positive correlation band profile,Is the positive correlation coefficient in which the frequency band is negative,Is the product of the absolute value of the positive correlation coefficient and the number of the negative frequency bands, is synthesizedAnd (3) withObtaining the sensitivity of the acupuncture of the patientWherein,The larger the acupuncture sensitivity of the current treatment is, the larger the acupuncture sensitivity is, and the different needle application depths are calculated;
For the improvement degree of the treatment effect, statistics is carried out on the extraction of all positive frequency band pearson correlation coefficients from the negative correlation frequency bands under the current acupuncture technique QCalculating the magnitude of the influence of the inversely related frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of active bands in the inversely related band profile,Is the negative correlation coefficient of the active frequency band therein,Is the product of the absolute value of the negative correlation coefficient and the number of active frequency bands;
counting all positive frequency band pearson correlation coefficients extracted from positive correlation frequency bands under the current acupuncture technique Q Calculating the influence size of the positively correlated frequency bandThe algorithm formula is as follows:
;
Wherein, Is the number of active bands in the positive correlation band profile,Is the positive correlation coefficient in which the frequency band is aggressive,Is the product of the absolute value of the positive correlation coefficient and the number of active frequency bands, is synthesizedAnd (3) withObtaining the sensitivity of the acupuncture of the patientWherein,The larger the treatment effect of the current treatment is, the larger the degree of improvement is, and the different needle application depths are calculated;
It should be noted that, adding the positive correlation negative frequency band influence and the negative correlation negative frequency band influence can obtain a comprehensive value, the value represents the degree of negative influence on the patient by combining all the negative frequency bands no matter whether the frequency bands are positively correlated or negatively correlated with the acupuncture depth, and according to the difference of the individual differences of different patients, the treatment sensitivity of different patients is obtained differently through the different patient negative frequency bands recorded in the file, so as to evaluate the acupuncture effect of the patient in a targeted manner.
Calculating the comprehensive influence degree under different needle application depthsWhen (when)0 Represents that the therapeutic effect is positive when<0 Represents the negative therapeutic effect by applying different acupuncture techniques and depths of needlesThe 0 condition is arranged in a descending order, the acupuncture manipulation and the acupuncture depth under the first arrangement are selected as the specific treatment scheme of the current patient, and the different acupuncture depths under different acupuncture manipulations are recorded in the patient image fileValues.
The curative effect real-time evaluation module further comprises a step of generating a patient treatment specific curative effect evaluation score based on a patient portrait file established in the current patient treatment process in the patient portrait generation module and combining the acupuncture technique and the needle application depth in the current patient treatment process;
The acupuncture and moxibustion technique and the acupuncture and moxibustion depth of each acupuncture and moxibustion applied in the current treatment process are obtained through an acupuncture and moxibustion data acquisition module, and the comprehensive influence degree of different acupuncture and moxibustion techniques of different patients based on the current patient image file is obtained Calculating to obtain the evaluation score of the specific curative effect of the treatment of the patient, wherein the algorithm formula is as follows:
;
Wherein, Represents the evaluation score of the specific curative effect of the current treatment of the patient, and i represents the administration frequency of the current treatment of the patient.
By the way, the comprehensive influence degree of each needle application of the patient in the current treatment processThe total combined effect of the treatment can be obtained by accumulation, the specific curative effect evaluation score of each needle application in the treatment process can be obtained by combining the needle application times of the treatment,A value greater than 0 indicates that the treatment is effective, and a greater value indicates that the treatment is more effective.
The long-term curative effect comprehensive evaluation module is used for setting a long-term curative effect evaluation node based on the treatment period of a patient, and performing long-term curative effect evaluation on the patient in the current period by combining the patient-specific curative effect evaluation score in the period, and comprises the following specific steps of:
Setting a long-term efficacy evaluation node based on the number of treatments n in the current patient treatment cycle and on the number of intervals T, dividing the patient treatment cycle into A step of counting each treatment time in the current stepValues for each phase after the patient treatment phase is completedValues were recorded and a line graph was drawn.
It should be noted that, the interval number T is generally set to 5, and by analyzing the fold line, when the fold line shows an ascending trend, it is indicated that the therapeutic effect of the patient is continuously improved along with the progress of the treatment, if the fold line is relatively stable, the therapeutic effect is in a relatively stable state, and when the fold line descends, it may be a problem to represent the therapeutic scheme, and further searching for a cause is required to adjust the therapeutic scheme.
The invention relates to an acupuncture treatment effect real-time evaluation system based on brain-computer interface technology, which is used for collecting brain electrical signals of a patient before treatment and in the treatment process through a brain-computer data collection module based on non-invasive brain-computer interface technology, collecting actions of doctors in the treatment process through an acupuncture data collection module, judging Shi Zhen acupuncture points, needle application depth and needle application methods in the treatment process of the current patient, transmitting data into a treatment effect real-time evaluation module, and carrying out real-time evaluation on the treatment effect of the patient by combining historical diagnosis and treatment data and acquired treatment influence parameters of the patient under the current disease;
Meanwhile, based on the needle application technique and the needle application depth of a doctor in the acupuncture treatment process, the treatment feedback electroencephalogram signals of the current patient are related to generate a treatment portrait file of the patient, wherein the treatment portrait file comprises the treatment sensitivity and the treatment effect improvement degree of the patient, the doctor is assisted to comprehensively determine a treatment optimal scheme, the acupuncture technique and the needle application depth of the current treatment are combined to obtain a patient-specific treatment effect evaluation score, the long-time treatment effect comprehensive evaluation module is used for setting a long-time treatment effect evaluation node based on the treatment period of the patient, and the long-time treatment effect evaluation is further carried out on the patient in the current period by combining the patient-specific treatment effect evaluation score.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be another division manner in actual implementation, and the modules described as separate components may or may not be physically separated, and components displayed as the modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of this embodiment.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (9)
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