Biofeedback-based acousto-optic hypnosis system for senile depression

Abstract

The present application relates to the technical field of biomedical engineering, and proposes a sound-light hypnosis system for senile depression based on biological feedback, which comprises: collecting electroencephalogram curves of resting state and stimulation state of multiple electrodes of a patient through an electrode cap; obtaining power spectral density of each electrode, and then obtaining a senile attenuation index; obtaining a reduction amplitude according to the senile attenuation index, and obtaining a reduction electroencephalogram curve of each electrode; obtaining a plurality of local electroencephalogram curves by segmentation; obtaining a probability of each local electroencephalogram curve being entrained; screening a plurality of entrained electroencephalogram curves of the reduction electroencephalogram curve of each electrode; comprehensively obtaining a final electroencephalogram curve of each electrode, so as to re-calculate an asymmetry index and assist in sound-light hypnosis analysis and evaluation. The present application aims to solve the problem that the brain entrainment effect of the elderly patients fails to affect the sound-light hypnosis electroencephalogram signal analysis and judgment.

Description

Technical Field

[0001] This invention relates to the field of biomedical engineering technology, specifically to a biofeedback-based audio-visual hypnosis system for geriatric depression. Background Technology

[0002] Evoked brainwaves (EEGs) are electrical activities measured on the surface of the cerebral cortex. They are used to detect neural responses to specific stimuli, such as visual, auditory, tactile, or other sensory stimuli. Evoked EEG measures brain signals on the surface of the cerebral cortex to detect neural responses, including brain waves, peripheral EEG, pattern-reversal visual evoked potentials (PRVEPs) generated by eye movements, and auditory evoked potentials. The results of evoked EEG measurements reflect the neural responses of the cerebral cortex and can therefore be used to diagnose cortical dysfunction in geriatric depression. Furthermore, by administering audio-visual stimulation to geriatric patients with depression, and using EEG signals as biofeedback, the impact of depression on different brain regions can be assessed. The principle involves monitoring whether the EEG signals in different electrode areas are affected by the audio-visual stimulation at a fixed pulse frequency, thus producing EEG signals of the same frequency, and determining the affected region.

[0003] Due to neurotransmitter imbalances, decreased key neurotransmitters, and the dominance of rumination networks in the thinking processes of patients with depression, as well as the decline in the number of neurons and the decrease in EEG amplitude in elderly patients, the brain entrainment effect produced by EEG signals after exposure to sound and light stimulation becomes ineffective. As a result, due to the slowed brain activity response in the elderly and the influence of depression, the lack of focus on the task leads to these signals being misjudged as bad segments of the EEG signal. These bad segments are then removed during the preprocessing to eliminate them, thus rendering sound and light hypnosis ineffective. Summary of the Invention

[0004] This invention provides a biofeedback-based audio-visual hypnosis system for geriatric depression, addressing the problem that existing methods for analyzing and interpreting EEG signals during audio-visual hypnosis are hampered by the failure of the brain entrainment effect in elderly patients. The specific technical solution adopted is as follows:

[0005] This invention proposes a biofeedback-based audio-visual hypnosis system for geriatric depression, the system comprising:

[0006] The EEG signal acquisition module is used to acquire EEG signal curves of multiple electrodes in the patient's resting and stimulated states through the electrode cap.

[0007] The EEG signal processing module is used to obtain the power spectral density of each electrode based on the EEG signal curves of the three electrodes in the left and right frontal lobes in the resting state through Fourier transform and the frequency distribution of the alpha wave, and then obtain the age decay index. For the amplitude of the frequency that is the same as the stimulation frequency of the sound and light signal in the spectrum diagram of the EEG signal curve after Fourier transform in the stimulated state, the restored amplitude is obtained according to the age decay index, and the restored EEG signal curve of each electrode is obtained through inverse Fourier transform.

[0008] The restored EEG signal curves of each electrode are segmented to obtain several local EEG curves; the amplitude of the local EEG curve at the same frequency as the stimulation frequency of the sound and light signal is analyzed, and the difference between the amplitude of the local EEG curve and the amplitude of other frequencies in the frequency domain is obtained to obtain the entrainment probability of each local EEG curve; based on the entrainment probability, a threshold judgment is made to select several entrainment segments, and then several entrainment EEG curves of the restored EEG signal curves of each electrode are obtained.

[0009] The audio-visual hypnosis analysis module is used to synthesize the amplitude performance of the same frequency in the frequency domain of several accompanying EEG curves based on the restored EEG signal curves of each electrode, and then recalculate the asymmetry index.

[0010] Optionally, the power spectral density of each electrode is obtained using the following method:

[0011] For the EEG signal curves of three electrodes each in the left and right frontal lobes at rest, for any one of the EEG signal curves, the EEG signal curve is transformed into the frequency domain by Fourier transform, and the result is a complex array. Each element in the complex array corresponds to a frequency. Based on the frequency range of the Alpha wave, the mean of the square values ​​of several elements whose corresponding frequencies are within the frequency range is used as the power spectral density of the electrode corresponding to the EEG signal curve.

[0012] Optionally, the specific method for obtaining the age-related decline index includes:

[0013] Obtain the power spectral density of three electrodes in each of the left and right frontal lobes; the average power spectral density of the three electrodes in the right frontal lobe is taken as the right anterior alpha power. The average power spectral density of the three electrodes in the left frontal lobe was used as the left anterior alpha power. ;

[0014] The difference between the natural logarithm of the right anterior alpha power and the natural logarithm of the left anterior alpha power is used as the attenuation coefficient. The difference between the asymmetry index and the attenuation coefficient is used as the aging attenuation index.

[0015] Optionally, the specific method for obtaining the restored amplitude based on the age-related decline index includes:

[0016] Extracting the stimulation frequency of the acoustic-optic signal, for the right frontal lobe... The electroencephalogram (EEG) signal curves of each electrode in the stimulated state are obtained by Fourier transform to obtain a spectrum diagram. The frequency in the spectrum diagram that is the same as the stimulation frequency of the sound and light signal is used as the adjustment frequency.

[0017] Will As an adjustment parameter, among which Indicates the age-related decline index, For an exponential function with the natural constant as the base, the product of the amplitude of the adjustment frequency and the adjustment parameter is used as the restored amplitude of the adjustment frequency.

[0018] Optionally, the specific method for obtaining the restored EEG signal curves of each electrode includes:

[0019] The frequency-adjusted amplitude is replaced with the spectrum after restoring the amplitude, which is used as the adjusted spectrum. An inverse Fourier transform is then performed, and the resulting curve is used as the first frequency of the right frontal lobe. The restored EEG signal curves of each electrode.

[0020] Optionally, the method for segmenting the restored EEG signal curves of each electrode to obtain several local EEG curves includes:

[0021] With a preset segment length, the restored EEG signal curve of any electrode in the right frontal lobe is decomposed into several local EEG curves using the segment length.

[0022] Optionally, the specific method for obtaining the entrainment probability of each local EEG curve includes:

[0023] For the restored EEG signal curve of any electrode in the right frontal lobe, the first... The local EEG curves were analyzed, and their spectrograms were obtained through Fourier transform. The amplitudes of each frequency in the spectrograms were also analyzed. The frequency that matched the stimulation frequency of the audio-visual signal was selected as the [missing value]. The frequency of influence of local EEG curves;

[0024] Get the The mean amplitude of all frequencies other than the influencing frequency in a local EEG curve, minus the mean amplitude of the influencing frequency, is the difference, and this difference is compared with the mean amplitude of the first local EEG curve. The ratio of the sum of the amplitudes of all frequencies in a given local EEG curve is used as the first... The probability of a local EEG curve being included.

[0025] Optionally, the specific method for obtaining the aforementioned segments is as follows:

[0026] A preset judgment threshold is set, and the judgment starts from the first local EEG curve in the restored EEG signal curve of any electrode in the right frontal lobe. When the probability of the local EEG curve being entrained is greater than the judgment threshold, the local EEG curve is regarded as an entrainment segment.

[0027] The system identifies and obtains all local EEG curves within the reconstructed EEG signal curve, thereby generating several entrained segments.

[0028] Optionally, the specific method for obtaining several entrained EEG curves of the restored EEG signal curves of each electrode includes:

[0029] All entrained segments in the restored EEG signal curve of any electrode in the right frontal lobe are retained. If there are no entrained segments in the restored EEG signal curve in the final result, all local EEG curves of the restored EEG signal curve are retained.

[0030] For all the retained entrained segments or local EEG curves in the restored EEG signal curve, the continuous entrained segments or local EEG curves are spliced ​​together into a local signal curve, and the resulting local signal curve is used as the entrained EEG curve of the restored EEG signal curve.

[0031] Optionally, the specific method for obtaining the final EEG signal curves of each electrode includes:

[0032] For any electrode in the left or right frontal lobe, several entrained EEG curves are generated from the restored EEG signal curves. All entrained EEG curves are used to form an entrained curve set for that electrode. The spectrograms of each entrained EEG curve in the set are obtained by Fourier transform, and the amplitude of each frequency in each entrained EEG curve is obtained. The average amplitude of any frequency in the spectrograms corresponding to multiple entrained EEG curves is calculated and used as the average amplitude of each frequency in the set of entrained EEG curves. The average amplitude of all frequencies in the set of entrained EEG curves is obtained and a spectrogram is generated, which is used as the average spectrogram of the set of entrained EEG curves. The average spectrogram is then subjected to inverse Fourier transform, and the resulting curve is used as the final EEG signal curve of that electrode.

[0033] The beneficial effects of this invention are as follows: This invention uses electroencephalogram (EEG) signals as biofeedback to induce audio-visual hypnosis in elderly patients with depression. It is necessary to consider the issue that the convergence of EEG signals in the left and right frontal lobes due to decreased responsiveness in elderly patients affects the calculation of the asymmetry index. Therefore, firstly, the age-related attenuation index is calculated by analyzing the EEG signal curves of each electrode in the left and right frontal lobes under resting conditions. This is then used to reconstruct the EEG signal curve under stimulation, obtaining a reconstructed EEG signal curve for subsequent analysis. Furthermore, considering the influence of the rumination network in the brain's neural network generated by depressed patients, the reconstructed EEG signal curve is segmented to obtain several local EEG curves. The frequency domain amplitude performance of these local EEG curves under the influence of stimulation frequency is analyzed to reflect the possibility of entrainment in the local EEG curves. Entrainment segments are extracted based on this, and entrained EEG curves are obtained. Finally, based on these entrained EEG curves, the final EEG signal curves of each electrode are obtained, eliminating the influence of the rumination network and the patient's own neurosensitivity, improving the accuracy of asymmetry index analysis using EEG signal curves, and ensuring the effectiveness of audio-visual hypnosis for elderly patients with depression. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 A structural block diagram of an audio-visual hypnosis system for geriatric depression based on biofeedback provided in an embodiment of the present invention;

[0036] Figure 2 This is an example diagram of the electrode arrangement in the electrode cap of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Please see Figure 1 The diagram illustrates a structural block diagram of a biofeedback-based audio-visual hypnosis system for geriatric depression, provided by an embodiment of the present invention. The system includes:

[0039] The EEG signal acquisition module 101 acquires EEG signal curves of the patient in both resting and stimulated states using multiple electrodes via electrode caps.

[0040] The purpose of this embodiment is to conduct audio-visual hypnosis on elderly patients with depression. At the same time, it is necessary to use EEG signals for biofeedback regulation. Therefore, electrode caps are needed to collect and analyze the patient's EEG signals. First, the data collection environment needs to be set up.

[0041] Specifically, the subjects (elderly patients with depression) entered the artificial climate chamber and acclimatized for 15 minutes; after acclimatization, the subjects needed to sit quietly for 5 minutes; electrode caps were prepared, with several electrodes distributed on the caps, such as... Figure 2 As shown, this is an example diagram of electrode arrangement in each lobe region of the brain in the electrode cap; conductive paste is applied to the corresponding position on the patient's head, and the electrode cap is worn on the patient's head; EEG signals are collected using an EEG amplifier. In this embodiment, 15 minutes of EEG signals are collected and used as the EEG signal curves of each electrode in the resting state.

[0042] Furthermore, the subjects underwent audio-visual hypnosis using an eye mask and headphones integrated with LED lights. Stimulation programs were initiated at different frequencies for 10 minutes each. At the start of each stimulation session, an event marker was sent to the EEG amplifier to distinguish pulses of different frequencies. Simultaneously, the EEG amplifier collected EEG signals for 10 minutes, which served as the EEG signal curves for each electrode stimulation state (containing different stimulation frequencies corresponding to multiple time periods).

[0043] EEG signal processing module 102:

[0044] It should be noted that the use of sound and light hypnosis in young patients with depression, combined with EEG feedback for depression assessment, is based on the asymmetry of alpha waves in the two frontal lobes. Specifically, patients with depression typically exhibit relative inhibition of EEG activity in the left frontal lobe compared to the right. Sound and light hypnosis is a technique that uses specific rhythmic sound and light stimulation to guide the brain into a relaxed, focused, and sleep-like state. The main principle of sound and light hypnosis is the brain entrainment principle: when the brain receives a stable, repetitive sensory stimulus, its own EEG rhythm tends to synchronize with this external rhythm, primarily involving alpha waves (8-13.5 Hz). The principle of sound and light hypnosis lies in using devices (such as eye masks and headphones) to emit sound and light signals synchronized with the target brain waves (such as alpha or theta waves), actively "pulling" the brain from a potentially tense and chaotic beta wave state to a relaxed and peaceful alpha wave state.

[0045] (1) Based on the EEG signal curves of the three electrodes in the left and right frontal lobes in the resting state, the power spectral density of each electrode is obtained through Fourier transform and the frequency distribution of Alpha wave, and then the age decay index is obtained; for the amplitude of the frequency that is the same as the stimulation frequency of the sound and light signal in the spectrum diagram of the EEG signal curve after Fourier transform in the stimulation state, the restored amplitude is obtained according to the age decay index, and the restored EEG signal curve of each electrode is obtained through inverse Fourier transform.

[0046] It should be further noted that since the brain electrical activity of the elderly generally slows down, this is due to the decrease in the number of neurons in the brain, the decline in the integrity of white matter, and the decline in the function of neurotransmitter systems (such as acetylcholine) with increasing age. This affects the power of the electrodes on both sides. When the alpha wave signal intensity in the left frontal lobe region should be lower in the resting state, the alpha wave signal intensity on both sides tends to be consistent due to the decline of the right frontal lobe. Therefore, it is necessary to obtain the age-related attenuation index of the brain electrical signal by analyzing the inconsistency between the signal intensity of the right and left frontal lobes.

[0047] Specifically, for the EEG signal curves of three electrodes each in the left and right frontal lobes at rest, for any one of these EEG signal curves, a Fourier transform is performed to convert the EEG signal curve to the frequency domain. The result is a complex array, where each element corresponds to a frequency. Based on the frequency range of the alpha wave, this is... The mean of the squares of several elements within the frequency range corresponding to the EEG signal curve is used as the power spectral density of the corresponding electrode. The power spectral density of three electrodes in the left and right frontal lobes is obtained using the same method. The mean of the power spectral density of the three electrodes in the right frontal lobe is used as the right anterior alpha power density. The average power spectral density of the three electrodes in the left frontal lobe was used as the left anterior alpha power. .

[0048] It should be further noted that the asymmetry index of the left and right frontal lobes in the resting state... It needs to be within a fixed range, and this fixed range is... The difference between the natural logarithm of the right anterior alpha power and the natural logarithm of the left anterior alpha power is used to determine the attenuation. If the difference is not within a fixed range, there is attenuation on the surface, and the EEG signal needs to be enhanced and restored. Therefore, the age attenuation index needs to be obtained first.

[0049] Furthermore, the difference between the natural logarithm of the right anterior alpha power and the natural logarithm of the left anterior alpha power is used as the attenuation coefficient. In this embodiment, the asymmetry index is... Using 25% as a metric, the difference between the asymmetry index and the attenuation coefficient is taken as the old age attenuation index.

[0050] It should be further explained that after obtaining the age-related decline index, since age-related decline activities lead to a decrease in the power of EEG activity in the left and right frontal lobes, which can be confused with the asymmetry of alpha waves caused by depression, the EEG signals under stimulation were enhanced and restored by analyzing the differences between the two sides in the resting state. Since it is unclear whether the decline is unilateral on the right side or both sides decline simultaneously, it is necessary to restore the EEG signal intensity of the left and right frontal lobes to a relatively reasonable range. Because the actual measurement process is subject to interference from other brain activities, and the sound and light stimulation only causes a banding effect on some frequencies of EEG, that is, the stress frequency of the EEG is the same as the stimulation frequency of the sound and light signal, only the EEG signal at the stimulation frequency is restored.

[0051] Extract the stimulation frequencies of the acoustic-optic signals (multiple stimulation frequencies corresponding to different time periods under stimulation conditions need to be extracted), for the right frontal lobe... The EEG signal curves of each electrode in the stimulated state are obtained by Fourier transforming the spectrum. The frequencies in the spectrum that match the stimulation frequency of the audio-visual signal are used as adjustment frequencies. The amplitudes of these frequencies need to be reconstructed. As an adjustment parameter, among which Indicates the age-related decline index, For an exponential function with the natural constant as the base, the product of the amplitude of the adjusted frequency and the adjustment parameter is used as the restored amplitude of the adjusted frequency. The spectrum of the adjusted frequency is then replaced with the spectrum of the restored amplitude, and an inverse Fourier transform is performed. The resulting curve is used as the first curve of the right frontal lobe. The restored EEG signal curves of each electrode.

[0052] It should be further noted that the dark energy of the default mode neural network (DMN) refers to the neural activity that continues in the brain even at rest, consuming about 20% of the body's total energy. Depression is closely related to the dysfunction of specific neural networks in the brain, especially the DMN. This network is most active when people are resting and not doing tasks, and is associated with self-referential thinking and rumination (repeatedly thinking about negative events). The DMN of depressed patients is often overactive and difficult to shut down, causing them to be trapped in negative "rumination" about themselves. Sound and light hypnosis aims to guide the brain into a specific, focused, and relaxed state, but the overactive DMN of depressed patients becomes a powerful "background noise." When external sound and light stimuli try to guide attention, the strong internal rumination will constantly pull attention back. Because the brain struggles between "processing external stimuli" and "performing internal rumination," the effect of brainwave entrainment is greatly reduced, making it difficult to form stable and synchronized target brainwaves, thus reducing entrainment efficiency.

[0053] (2) The restored EEG signal curves of each electrode are segmented to obtain several local EEG curves; the amplitude of the local EEG curve at the same frequency as the stimulation frequency of the sound and light signal is analyzed and the difference between the amplitude of other frequencies in the frequency domain is analyzed to obtain the entrainment probability of each local EEG curve; based on the entrainment probability, a threshold judgment is made to screen and obtain several entrainment segments, and then several entrainment EEG curves of the restored EEG signal curves of each electrode are obtained.

[0054] It is further important to note that depression is associated with the dysfunction of multiple neurotransmitter systems (such as serotonin, norepinephrine, and dopamine). These chemicals are fundamental to efficient and coordinated communication between neurons. Neurotransmitter imbalances may lead to a decrease in the synchronized firing ability of neuronal clusters, making it more difficult for depressed patients to react slowly and with inconsistent coordination to generate a strong and stable alpha or theta rhythm. In EEG signals, this manifests as alternation between entrained and non-entrained periods in stimulation segments, leading to errors in assessing the severity of depression using the audio-visual hypnotic effect. Alternatively, the alternation between entrained and non-entrained periods may be misjudged as not having entered the entrained region. Therefore, by screening the spectrograms of EEG signals at various moments under stimulation and comparing them with the spectrograms of audio-visual stimulation pulses, the EEG signal segments under audio-visual stimulation, i.e., the entrained EEG curves, can be obtained, providing a basis for obtaining the final EEG signal curve.

[0055] Specifically, a preset segment length is used. In this embodiment, the segment length is described as 10,000 unit time units, and the unit time is described in milliseconds (ms). For the restored EEG signal curve of any electrode in the right frontal lobe, the restored EEG signal curve is decomposed into several local EEG curves using the segment length. It is worth noting that if the remaining unit time is less than the segment length, the segment of the restored EEG signal curve corresponding to the remaining unit time is also analyzed as a local EEG curve. For the first segment of the restored EEG signal curve... The local EEG curves were analyzed, and their spectrograms and amplitudes at each frequency were obtained through Fourier transform. The frequencies that corresponded to the stimulation frequency of the audio-visual signal (the stimulation frequency corresponding to the time period of the local EEG curve; here, only one stimulation frequency corresponds to a local EEG curve) were selected as the first local EEG curve. The influence frequency of the local EEG curve; obtain the first The mean amplitude of all frequencies other than the influencing frequency in a local EEG curve, minus the mean amplitude of the influencing frequency, is the difference, and this difference is compared with the mean amplitude of the first local EEG curve. The ratio of the sum of the amplitudes of all frequencies in a given local EEG curve is used as the first... The probability of a local EEG curve being included.

[0056] Furthermore, a preset judgment threshold is established. In this embodiment, the judgment threshold is described as 0.6. The judgment begins with the first local EEG curve in the reconstructed EEG signal curve. When the probability of a local EEG curve exhibiting entrainment exceeds the judgment threshold, that local EEG curve is considered an entrainment segment. All local EEG curves in the reconstructed EEG signal curve are then obtained, resulting in several entrainment segments. All entrainment segments in the reconstructed EEG signal curve are retained. If, in the final result, no entrainment segments exist in the reconstructed EEG signal curve (i.e., the probability of entrainment in all local EEG curves is less than or equal to the judgment threshold), then the reconstructed EEG signal curve is considered... All local EEG curves in the restored EEG signal curve are preserved. For all preserved entrained segments or local EEG curves in the restored EEG signal curve, the continuous entrained segments or local EEG curves are spliced ​​together to form a local signal curve, and the resulting local signal curve is used as the entrained EEG curve of the restored EEG signal curve. The restored EEG signal curves are obtained from each electrode in the left and right frontal lobes according to the above method, and the local EEG curves are judged to obtain several entrained EEG curves of each restored EEG signal curve. It should be noted that if all local EEG curves are preserved in the restored EEG signal curve, then the entire EEG signal curve is the entrained EEG curve.

[0057] It should be noted that after segmenting the reconstructed EEG signal curve, several local EEG curves are obtained. By analyzing the amplitude of the influencing frequency in the local EEG curve that is the same as the stimulation frequency of the audio-visual signal, the difference between the amplitude of the frequency and other frequencies in the local EEG curve, and the proportion of this difference in the sum of the amplitudes of all frequencies, the larger the difference and the larger the proportion, the more obvious the entrainment effect, and the greater the probability that the corresponding local EEG curve is affected by the audio-visual signal stimulation, and the greater the probability of entrainment. By using a threshold judgment on the probability of entrainment in the local EEG curves in the reconstructed EEG signal curve, entrainment segments are extracted, and several entrained EEG curves are obtained. Rumination segments are excluded from analysis, that is, the local EEG curves with delayed response are not analyzed.

[0058] At this point, the restored EEG signal curves of each electrode in the left and right frontal lobes, as well as some of the accompanying EEG curves, were obtained.

[0059] The audio-visual hypnosis analysis module 103, based on the amplitude performance of the same frequency in the frequency domain of several accompanying EEG curves of the restored EEG signal curves of each electrode, comprehensively obtains the final EEG signal curve of each electrode, thereby recalculating the asymmetry index and assisting in audio-visual hypnosis analysis and evaluation.

[0060] It should be noted that the EEG curve included in the restored EEG signal curve is the EEG signal curve after removing the rumination segment, and this is used as the final EEG signal curve. Based on the final EEG signal curve, the power spectral density of each electrode in the left and right frontal lobes is recalculated, and then the asymmetry index is recalculated to assist doctors in conducting audio-visual hypnosis assessments of depression in elderly patients.

[0061] Specifically, for any electrode in the left or right frontal lobe, several entrained EEG curves are generated from the restored EEG signal curves. All entrained EEG curves are used to form an entrained curve set for that electrode. The spectrograms of each entrained EEG curve in the set are obtained by Fourier transform, and the amplitude of each frequency in each entrained EEG curve is obtained. The average amplitude of any frequency in the spectrograms corresponding to multiple entrained EEG curves is calculated and used as the average amplitude of each frequency in the set of entrained EEG curves. The average amplitude of all frequencies in the set of entrained EEG curves is obtained and a spectrogram is generated, which is used as the average spectrogram of the set of entrained EEG curves. The average spectrogram is then subjected to inverse Fourier transform, and the resulting curve is used as the final EEG signal curve for that electrode.

[0062] Furthermore, the power spectral density of the final EEG signal curves of each electrode in the left and right frontal lobes is obtained, thereby obtaining the final right anterior alpha wave power and left anterior alpha wave power. The asymmetry index is then recalculated, and the recalculated asymmetry index is communicated to the doctor to assist the doctor in assessing the depression status and degree of elderly patients. Based on this, the doctor can also conduct audio-visual hypnosis assessments for elderly patients with depression using EEG feedback.

[0063] This concludes the embodiment.

[0064] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A biofeedback-based audio-visual hypnosis system for geriatric depression, characterized in that, The system includes: The EEG signal acquisition module is used to acquire EEG signal curves of multiple electrodes in the patient's resting and stimulated states through the electrode cap. The EEG signal processing module is used to obtain the power spectral density of each electrode based on the EEG signal curves of three electrodes in the left and right frontal lobes in the resting state, through Fourier transform and frequency distribution of alpha waves, and then obtain the age decay index; for the amplitude of the frequency that is the same as the stimulation frequency of the sound and light signal in the spectrum diagram of the EEG signal curve after Fourier transform in the stimulated state, the restored amplitude is obtained according to the age decay index, and the restored EEG signal curve of each electrode is obtained through inverse Fourier transform. The specific methods for obtaining the age-related decline index are as follows: Obtain the power spectral density of three electrodes in each of the left and right frontal lobes; the average power spectral density of the three electrodes in the right frontal lobe is taken as the right anterior alpha power. The average power spectral density of the three electrodes in the left frontal lobe was used as the left anterior alpha power. ; The difference between the natural logarithm of the right anterior alpha power and the natural logarithm of the left anterior alpha power is used as the attenuation coefficient. The difference between the asymmetry index and the attenuation coefficient is used as the aging attenuation index. The restored EEG signal curves of each electrode are segmented to obtain several local EEG curves; the amplitude of the local EEG curve at the same frequency as the stimulation frequency of the sound and light signal is analyzed, and the difference between the amplitude of the local EEG curve and the amplitude of other frequencies in the frequency domain is obtained to obtain the entrainment probability of each local EEG curve; based on the entrainment probability, a threshold judgment is made to select several entrainment segments, and then several entrainment EEG curves of the restored EEG signal curves of each electrode are obtained. The specific methods for obtaining the entrainment probability of each local EEG curve include: For the restored EEG signal curve of any electrode in the right frontal lobe, the first... The local EEG curves were analyzed, and their spectrograms were obtained through Fourier transform. The amplitudes of each frequency in the spectrograms were also analyzed. The frequency that matched the stimulation frequency of the audio-visual signal was selected as the [missing value]. The frequency of influence of local EEG curves; Get the The mean amplitude of all frequencies other than the influencing frequency in a local EEG curve, minus the mean amplitude of the influencing frequency, is the difference, and this difference is compared with the mean amplitude of the first local EEG curve. The ratio of the sum of the amplitudes of all frequencies in a given local EEG curve is used as the first... The probability of entrainment in a local EEG curve; The audio-visual hypnosis analysis module is used to synthesize the amplitude performance of the same frequency in the frequency domain of several accompanying EEG curves based on the restored EEG signal curves of each electrode, and then recalculate the asymmetry index of the left and right frontal lobes EEG signals.

2. The biofeedback-based audio-visual hypnosis system for geriatric depression according to claim 1, characterized in that, The power spectral density of each electrode is obtained using the following method: For the EEG signal curves of three electrodes each in the left and right frontal lobes at rest, for any one of the EEG signal curves, the EEG signal curve is transformed into the frequency domain by Fourier transform, and the result is a complex array. Each element in the complex array corresponds to a frequency. Based on the frequency range of the Alpha wave, the mean of the square values ​​of several elements whose corresponding frequencies are within the frequency range is used as the power spectral density of the electrode corresponding to the EEG signal curve.

3. The biofeedback-based audio-visual hypnosis system for geriatric depression according to claim 1, characterized in that, The specific method for obtaining the restored amplitude based on the age-related decline index is as follows: Extracting the stimulation frequency of the acoustic-optic signal, for the right frontal lobe... The electroencephalogram (EEG) signal curves of each electrode in the stimulated state are obtained by Fourier transform to obtain a spectrum diagram. The frequency in the spectrum diagram that is the same as the stimulation frequency of the sound and light signal is used as the adjustment frequency. Will As an adjustment parameter, among which Indicates the age-related decline index, For an exponential function with the natural constant as the base, the product of the amplitude of the adjustment frequency and the adjustment parameter is used as the restored amplitude of the adjustment frequency.

4. The biofeedback-based audio-visual hypnosis system for geriatric depression according to claim 3, characterized in that, The specific method for obtaining the restored EEG signal curves of each electrode is as follows: The frequency-adjusted amplitude is replaced with the spectrum after restoring the amplitude, which is used as the adjusted spectrum. An inverse Fourier transform is then performed, and the resulting curve is used as the first frequency of the right frontal lobe. The restored EEG signal curves of each electrode.

5. The biofeedback-based audio-visual hypnosis system for geriatric depression according to claim 1, characterized in that, The method for segmenting the restored EEG signal curves of each electrode to obtain several local EEG curves includes: With a preset segment length, the restored EEG signal curve of any electrode in the right frontal lobe is decomposed into several local EEG curves using the segment length.

6. The biofeedback-based audio-visual hypnosis system for geriatric depression according to claim 1, characterized in that, The specific method for obtaining the aforementioned segments is as follows: A preset judgment threshold is set, and the judgment starts from the first local EEG curve in the restored EEG signal curve of any electrode in the right frontal lobe. When the probability of the local EEG curve being entrained is greater than the judgment threshold, the local EEG curve is regarded as an entrainment segment. The system identifies and obtains all local EEG curves within the reconstructed EEG signal curve, thereby generating several entrained segments.

7. The biofeedback-based audio-visual hypnosis system for geriatric depression according to claim 1, characterized in that, The specific method for obtaining several entrained EEG curves from the restored EEG signal curves of each electrode includes: All entrained segments in the restored EEG signal curve of any electrode in the right frontal lobe are retained. If there are no entrained segments in the restored EEG signal curve in the final result, all local EEG curves of the restored EEG signal curve are retained. For all the retained entrained segments or local EEG curves in the restored EEG signal curve, the continuous entrained segments or local EEG curves are spliced ​​together into a local signal curve, and the resulting local signal curve is used as the entrained EEG curve of the restored EEG signal curve.

8. The biofeedback-based audio-visual hypnosis system for geriatric depression according to claim 1, characterized in that, The specific method for obtaining the final EEG signal curves for each electrode is as follows: For any electrode in the left or right frontal lobe, several entrained EEG curves are generated from the restored EEG signal curves. All entrained EEG curves are used to form an entrained curve set for that electrode. The spectrograms of each entrained EEG curve in the set are obtained by Fourier transform, and the amplitude of each frequency in each entrained EEG curve is obtained. The average amplitude of any frequency in the spectrograms corresponding to multiple entrained EEG curves is calculated and used as the average amplitude of each frequency in the set of entrained EEG curves. The average amplitude of all frequencies in the set of entrained EEG curves is obtained and a spectrogram is generated, which is used as the average spectrogram of the set of entrained EEG curves. The average spectrogram is then subjected to inverse Fourier transform, and the resulting curve is used as the final EEG signal curve of that electrode.

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