System for evaluating treatment effect of alcohol use disorder patient by using electroencephalogram power spectrum characteristics

Abstract

According to the system for evaluating the treatment effect of the AUD patient through the electroencephalogram power spectrum characteristics, the electroencephalogram activity is captured through an electroencephalogram monitoring sensor, the electroencephalogram power spectrum characteristics in a resting state are calculated through a data processing unit, the electroencephalogram power spectrum characteristics are compared with a preset reference value or index modes in different psychological states, and the treatment effect of the AUD patient is evaluated. To identify features of brain activity of the patient. The preset value is based on a classification of subconsciousness and consciousness reactions of the AUD patient and statistically validated. The system judges the brain activity state and the treatment effect of the AUD patient according to the analysis result of the electroencephalogram power spectrum characteristics, and the analysis and judgment result is displayed through an output unit. The system can accurately evaluate the treatment effect of the new treatment method of subconsciousness memory degradation on the AUD patient, so as to provide accurate treatment and prevention strategies for the AUD patient.

Description

Technical Field

[0001] The present invention relates to a system for evaluating the treatment effect of patients with alcohol use disorder. Background Art

[0002] Alcohol use disorders (AUD) are characterized by compulsive heavy drinking and loss of control over alcohol intake. It is a common chronic disease that is extremely harmful to society. AUD is associated with a variety of physical and mental sequelae and is one of the most common mental disorders in the world. Alcohol relapse is the main clinical problem of AUD, and the craving for alcohol is the key factor in the relapse of AUD patients. The craving for alcohol is the main feature of AUD patients and one of the important items for diagnosing AUD. Craving can be defined as an urgent and irresistible desire or impulse to drink, which, if not satisfied, will lead to psychological and physiological symptom reactions. Therefore, reducing craving is the key to treating AUD. Alcohol cues are an important factor in inducing AUD relapse. How to accurately assess the psychological craving induced by alcohol cues and its changes in the treatment of alcohol dependence currently faces great challenges due to the lack of objective evidence.

[0003] Resting-state EEG records brain activity when participants are awake and do not need to participate in specific tasks. Usually, the eyes are closed to prevent eye movement from affecting the EEG signal. The EEG signal in the resting state reflects the basic state of the brain, shows its basic neural activity mechanism, and is associated with events involving attention, memory, thinking, and cognitive processes. There are nearly 10 trillion synapses in the human brain that are interconnected, which form a variety of loops of various sizes, forming the structural basis of behavior and mental activities. Therefore, resting state activity can predict behavioral performance, perception, decision-making, and related neural activities. Power spectrum analysis can expand the understanding of the complex functional structure of the resting brain. EEG measurement usually represents a high time resolution of milliseconds. Its advantage is that it can measure neuronal activity with high time accuracy, and compared with other brain science technologies (FMRI, MEG, etc.), it is low-cost and easy to move, and can measure the brain activity of subjects in resting and task states.

[0004] It should be noted that the information disclosed in the above background technology section is only used for understanding the background of the present application, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the invention

[0005] The main purpose of the present invention is to overcome the defects of the above-mentioned background technology and provide a system for evaluating the treatment effect of patients with alcohol use disorder using EEG power spectrum characteristics. The present invention uses the research and discovery of the characteristics of the brain neural mechanism of subconscious memory extinction applied to AUD patients. Through the detection and analysis of EEG power spectrum characteristics by the system of the present invention, it can accurately evaluate the treatment effect of new treatment methods for subconscious memory extinction on AUD patients, and provide more accurate treatment and detection prevention strategies for AUD patients, which has a good guiding significance.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A system for evaluating the treatment effect of patients with alcohol use disorder (AUD) using EEG power spectrum characteristics, comprising:

[0008] EEG monitoring sensors, which measure the user’s electrical brain activity;

[0009] A data processing unit, connected to the EEG monitoring sensor, is used to perform the following operations:

[0010] a. Obtain the user's brain electrical activity by measuring the EEG signal in real time through the EEG monitoring sensor, and calculate the EEG power spectrum characteristics in the resting state;

[0011] b. Comparing the calculated EEG power spectrum characteristics with preset baseline values ​​or with index patterns under different psychological states to identify the brain activity characteristics of the patient under a specific psychological state; the preset baseline values ​​or index patterns are based on the classification of subconscious and conscious reactions of AUD patients under different exposure conditions, and are analyzed and verified using statistical methods;

[0012] c. Based on the comparison results of EEG power spectrum characteristics, analyze and determine the characteristics of the patient's brain neural mechanism when subconsciously processing alcohol stimulation;

[0013] d. Comprehensively judge the brain activity status and treatment effect of AUD patients based on the analysis results of EEG power spectrum characteristics;

[0014] The output unit is used to output the EEG power spectrum feature analysis and judgment results.

[0015] The present invention has the following beneficial effects:

[0016] The system of the present invention provides a new and effective method for evaluating the therapeutic effect of subconscious memory extinction on patients with alcohol use disorder (AUD) by monitoring and analyzing the characteristics of EEG power spectrum. The system can accurately capture the changes in brain activity of patients during the treatment of subconscious memory extinction. By monitoring EEG signals and calculating the characteristics of EEG power spectrum in the resting state, the system can reveal the activity characteristics of the patient's brain under different psychological states, reflect the dynamics of the brain neural network, identify and evaluate the treatment response of AUD patients, and provide a new treatment effect evaluation tool for clinicians. In addition, the real-time feedback provided by the system can improve the patient's treatment compliance and participation. Using the personalized monitoring and analysis results generated by the system, the treatment plan can be adjusted according to the patient's specific response to achieve personalized treatment and improve the effectiveness of treatment, thereby providing strong technical support for the rehabilitation of AUD patients. The system realizes a non-invasive, low-cost treatment effect evaluation, and the design of the system allows it to be integrated with existing medical equipment and workflows, which is convenient for implementation and use in different medical environments, while helping to reduce medical costs and improve the efficiency of medical resource use.

[0017] Other beneficial effects of the embodiments of the present invention will be further described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of electrode positions according to an embodiment of the present invention.

[0019] Figure 2 and Figure 3 This is a diagram of average power in different frequency bands of different groups according to an embodiment of the present invention.

[0020] Figure 4 These are power spectrum maps of different frequency bands of different groups according to the embodiments of the present invention.

[0021] Figure 5 Schematic diagram of the system structure for evaluating the treatment effect of patients with alcohol use disorder using EEG power spectrum characteristics according to an embodiment of the present invention. DETAILED DESCRIPTION

[0022] The following is a detailed description of the embodiments of the present invention. It should be emphasized that the following description is only exemplary and is not intended to limit the scope and application of the present invention.

[0023] Key terms and concepts:

[0024] EEG signals

[0025] Electroencephalogram (EEG): The brain is composed of billions of cells, half of which are neurons, which are closely connected through synapses (which can inhibit excitatory activity). When a large number of neurons discharge at the same time, a strong electric field is formed, which propagates to tissues, bones and skulls, and can eventually be measured on the scalp. We use electrophysiological indicators to record the electrical signals generated by brain activity on the surface of the scalp (the sum of postsynaptic potentials when a large number of pyramidal neurons are excited synchronously). EEG is a plane diagram that records the electrical signals generated by the brain with time as the horizontal axis and potential as the vertical axis. EEG measurement usually represents high time resolution at the millisecond level. Its advantage is that it can measure neuronal activity with high time accuracy, and it is less expensive and more portable than other brain science technologies (FMRI, MEG, etc.). It can measure the brain activity of subjects in resting and task states. Resting-state EEG reflects the basic state of the brain, shows its basic neural activity mechanism, and is associated with events involving attention, memory, thinking and cognitive processes. There are nearly 10 trillion interconnected synapses in the human brain, which form a variety of large and small loops, forming the structural basis of behavior and mental activities. Therefore, resting state activity can predict behavioral performance, perceptual decisions and related neural activities. Power spectral density analysis can expand our understanding of the complex functional structure of the resting brain.

[0026] Specific frequency bands of resting-state EEG

[0027] According to the EEG energy rhythm and changing rules, the EEG rhythm signals are divided into several typical signal characteristics from small to large, such as delta, theta, alpha, beta, gamma, etc.

[0028] The delta band is an EEG frequency band in the range of 1-3Hz, mainly appearing in the frontal and occipital regions of the brain. The delta band mainly appears in deep sleep without dreams, and can be used as a standard for detecting sleep quality. If the delta band appears in a non-sleep state, it is an abnormal phenomenon.

[0029] Theta frequency band refers to EEG with a frequency range of 4-8Hz, which mainly appears in the parietal and temporal lobes of the brain. Theta waves are related to cognitive processing, memory, thinking activities and concentration. Theta waves mainly appear in people when they are sleepy, and sometimes appear in the frontal lobe when they are quiet and have their eyes closed.

[0030] The alpha band refers to the EEG with a frequency range of 8-13Hz, which mainly appears in the parietal lobe and occipital lobe. The alpha wave is the main EEG rhythm in adults in the resting state of consciousness, and its activity is symmetrically distributed. It usually appears when people are alert, calm and have their eyes closed, and disappears when they open their eyes, think about problems or receive stimulation. It is related to cognition, memory, etc.

[0031] The beta band refers to the EEG frequency range of 14-20Hz, which mainly appears in the frontal lobe, temporal lobe and central area of ​​the brain. It is considered to be an indicator of cortical arousal and is involved in people's emotional response and cognitive process. Beta waves are also more likely to appear when people are working, concentrating, nervous and excited.

[0032] The gamma band refers to the EEG frequencies greater than 20 Hz.

[0033] The embodiment of the present invention provides a system for evaluating the treatment effect of alcohol use disorder (AUD) patients using EEG power spectrum characteristics, including:

[0034] EEG monitoring sensors to measure the user’s electrical brain activity;

[0035] A data processing unit, connected to the EEG monitoring sensor, is used to perform the following operations:

[0036] a. Obtain the user's brain electrical activity by measuring the EEG signal in real time through the EEG monitoring sensor, and calculate the EEG power spectrum characteristics in the resting state;

[0037] b. Comparing the calculated EEG power spectrum characteristics with preset baseline values ​​or with index patterns under different psychological states to identify the brain activity characteristics of the patient under a specific psychological state; the preset baseline values ​​or index patterns are based on the classification of subconscious and conscious reactions of AUD patients under different exposure conditions, and are analyzed and verified using statistical methods;

[0038] c. Based on the comparison results of EEG power spectrum characteristics, analyze and determine the characteristics of the patient's brain neural mechanism when subconsciously processing alcohol stimulation;

[0039] d. Comprehensively judge the brain activity status and treatment effect of AUD patients based on the analysis results of EEG power spectrum characteristics;

[0040] The output unit, such as a display screen, is used to output (eg, display) the analysis and judgment results of the EEG power spectrum characteristics.

[0041] In some embodiments, the EEG power spectrum features include the average power of each of the delta, theta, alpha, and beta frequency bands.

[0042] In some embodiments, the processing of the data processing unit includes: calculating the average power of the delta and theta frequency bands respectively, comparing the EEG power spectrum characteristics in the delta and theta frequency bands before and after treatment to identify the changes in each frequency band during the treatment process; and using the changes to evaluate the effect of alcohol cue exposure therapy at the subconscious level.

[0043] In some embodiments, the baseline value or indicator pattern is established based on the following method: classifying the subconscious and conscious reactions of AUD patients under different exposure conditions; establishing EEG indicator patterns corresponding to subconscious processing of alcohol stimuli, subconscious processing of neutral stimuli and conscious processing of alcohol stimuli based on the classification results; and using statistical methods, such as one-way analysis of variance and multiple comparison correction, to verify the significance of the indicator pattern.

[0044] The system of the present invention accurately evaluates the therapeutic effect of different interventions, including the effects of subconscious alcohol cue exposure treatment group (very brief exposure, VBE), subconscious neutral cue exposure treatment group (very brief neutral-stimulus, VBN), and conscious alcohol cue exposure treatment group (clearly visible exposure, CVE), on the EEG power spectrum characteristics of patients with alcohol use disorder (AUD). The present invention quantifies and evaluates the therapeutic effect by using neurophysiological indicators through power spectrum analysis of electroencephalogram (EEG). By comparing the changes in EEG indicators before and after treatment, the present invention can reveal the specific effects of different interventions on the brain activity of AUD patients, and provide an accurate basis for the evaluation of clinical treatment effects. In general, the present invention provides an effective solution for the clinical treatment effect evaluation of AUD through EEG power spectrum characteristics.

[0045] The preprocessing process includes: (1) importing raw data; (2) positioning electrodes, using the internationally accepted 10-20 standard lead system to locate relevant information; (3) deleting useless electrodes ECG (electrocardiogram), FT9, and FT10; (4) offline filtering, using a 0.1Hz high-pass filter to eliminate voltage drift, a 50Hz low-pass filter to eliminate noise, and a 48-52Hz notch filter to remove power frequency interference; (5) downsampling: downsampling the collected 1000Hz raw data to 500Hz; (6) removing bad segments and replacing bad leads: through manual screening, removing bad segments with too many lead artifacts, removing leads with bad tracks and performing bad track interpolation reconstruction; (7) re-reference: replacing the previous reference electrode, using bilateral mastoid TP9 and TP10 as re-reference; (8) re-segmenting the above EEG data into 2s segments; (9) independent component analysis method (Independent component ICA: Use ICA to analyze EEG data and manually exclude EEG artifacts, including electrooculography (blinking, eye movement artifacts), electromyography (frontal muscle, temporalis muscle activity), electrocardiography (heartbeat), other artifacts (scalp sweating), and other interferences. Note that blinking and eye movement are low-frequency, and electromyography is high-frequency. Around 50Hz may be power frequency interference, and vertical eye movement, horizontal eye movement, blinking, electromyography and other artifacts are removed from the components. For example, if the energy amplitude of a certain component is large, the noise frequency range is wide, and the impact on the front area of ​​the head is significant, it may be an electrooculography artifact; when the energy of a certain component is mainly spike-shaped high-frequency electrical activity, it may be an electromyography artifact. Artifacts caused by scalp sweating appear as a low-frequency, low-amplitude, wavy electrical signal in the brain wave. Remove as many artifacts, interference, and noise as possible to retain pure EEG signals.

[0046] After preprocessing the resting EEG data, the data of each electrode point was subjected to Fast Fourier Transform (FTT) to extract the power spectrum of each electrode point, and the data results were transformed by 10*log10. The range of each frequency band is as follows: delta (0.5-4Hz), theta (4-8Hz), alpha (8-13Hz), beta (13-30Hz), gamma (20-40Hz). The average absolute power of EEG in each frequency band comes from the whole brain area of ​​each scalp electrode.

[0047] Resting state power spectrum results

[0048] Figure 2-Figure 3It is the power spectral density of the resting frequency bands of the three groups of research subjects after different treatment conditions, among which the average power of the frequency bands delta (1-3Hz), theta (4-7Hz), alpha (8-13Hz), beta (13-20Hz), and gamma (20-40Hz) are compared. The data show that there are significant differences in the gamm frequency band at the C3 electrode site, significant differences in delta and gamma at the C5 electrode, significant differences in alpha and gamma at the Cz electrode, and significant differences in gamma at the Pz electrode. In summary, the experimental data show that through the power analysis of the delta, theta, alpha, beta, and gamma frequency bands of the electroencephalogram (EEG), especially the delta, alpha, and gamma frequency bands, there are significant differences in the C3, C5, Cz, and Pz electrodes, reflecting the changes in the neurons of the frontal and parietal cortex of the brain. These findings show that the present invention can quantify the treatment effect and detect the changes in the brain activity of AUD patients during the treatment process, thereby providing a basis for the adjustment and optimization of personalized treatment plans for clinical practice, thereby improving the effectiveness of treatment.

[0049] Furthermore, in order to accurately evaluate the treatment effect of patients with alcohol use disorder (AUD), a benchmark or reference point is set, and the detected and calculated EEG power spectrum features are compared with the preset benchmark or index pattern to measure the changes before and after treatment, confirm the effectiveness of the treatment and the improvement of the patient. Through statistical verification and classification of the responses of AUD patients under different exposure conditions, a benchmark value or index pattern can be established to ensure the accuracy and reliability of the treatment effect evaluation.

[0050] The embodiment of the present invention provides an innovative technical solution, which can effectively evaluate the treatment effect of patients with alcohol use disorder by setting a benchmark or reference point, performing statistical verification, and performing classification analysis. Specifically, the benchmark or reference point can be set by classifying the subconscious and conscious reactions of AUD patients under different exposure conditions, and combined with statistical verification and classification analysis, an accurate evaluation of the treatment effect of patients with alcohol use disorder can be achieved. This process can use known statistical methods such as one-way analysis of variance to determine the baseline value or index pattern of the EEG power spectrum characteristics, and use this as a reference to confirm the effectiveness of the treatment and the improvement of the patient by comparing the changes in different treatment conditions. That is, the detected EEG power spectrum characteristic index is used to measure the changes before and after treatment by comparing with the preset baseline value or index pattern. In addition, by applying statistical methods, such as one-way analysis of variance and multiple comparison correction, the significance of the index pattern can be verified, thereby ensuring the accuracy and reliability of the treatment effect evaluation. Through this systematic solution, the present invention can effectively evaluate and judge the physiological state and treatment effect of AUD patients, so as to provide more accurate treatment and prevention strategies for clinicians.

[0051] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art of the present invention, several equivalent substitutions or obvious variations can be made without departing from the concept of the present invention, and the performance or use is the same, which should be regarded as belonging to the protection scope of the present invention.

Claims

1. A system for evaluating the treatment effect of patients with alcohol use disorder (AUD) using EEG power spectrum characteristics, characterized in that: include: EEG monitoring sensors, which measure the user’s electrical brain activity; A data processing unit, connected to the EEG monitoring sensor, is used to perform the following operations: a. Obtain the user's brain electrical activity by measuring the EEG signal in real time through the EEG monitoring sensor, and calculate the EEG power spectrum characteristics in the resting state; b. Comparing the calculated EEG power spectrum characteristics with preset baseline values ​​or with index patterns under different psychological states to identify the brain activity characteristics of the patient under a specific psychological state; the preset baseline values ​​or index patterns are based on the classification of subconscious and conscious reactions of AUD patients under different exposure conditions, and are analyzed and verified using statistical methods; c. Based on the comparison results of EEG power spectrum characteristics, analyze and determine the characteristics of the patient's brain neural mechanism when subconsciously processing alcohol stimulation; d. Comprehensively judge the brain activity status and treatment effect of AUD patients based on the analysis results of EEG power spectrum characteristics; The output unit is used to output the EEG power spectrum feature analysis and judgment results.

2. The system according to claim 1, characterized in that The EEG power spectrum features include the average power of each frequency band of delta, theta, alpha, and beta.

3. The system according to claim 1, characterized in that The processing of the data processing unit includes: The average power of delta and theta frequency bands was calculated respectively, and the EEG power spectrum characteristics in the delta and theta frequency bands were compared before and after treatment to identify the changes in each frequency band during the treatment process; the changes were used to evaluate the effect of alcohol cue exposure treatment at the subconscious level.

4. The system according to claim 1, characterized in that The benchmark value or indicator model is established based on the following method: Classify the subconscious and conscious responses of AUD patients under different exposure conditions; Based on the classification results, the EEG index patterns corresponding to subconscious processing of alcohol stimuli, subconscious processing of neutral stimuli, and conscious processing of alcohol stimuli were established; Statistical methods, such as one-way ANOVA with correction for multiple comparisons, were used to verify the significance of the indicator patterns.

5. The system according to claim 1, characterized in that The processing of the data processing unit includes: Preprocessing of EEG signal data, including filtering, noise removal and baseline drift correction; The preprocessed EEG signal is subjected to fast Fourier transform (FFT) to extract the power spectrum of each electrode.

6. The system according to any one of claims 1 to 5, characterized in that: The output unit comprises: The display screen is used to display the results of the EEG power spectrum feature analysis and judgment.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, data processing of the system according to any one of claims 1 to 6 is realized.

8. A computer program product, characterized in that When the computer program product is executed by a processor, the computer program product implements data processing of the system according to any one of claims 1 to 6.

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