Neural regulation multi-mode anti-depression therapeutic apparatus

Abstract

The invention relates to the technical field of medical equipment, in particular to a nerve regulation multi-mode anti-depression therapeutic apparatus, and aims to solve the problem that depression treatment generally only relates to a single treatment means in the prior art. According to the scheme, multi-modal data are dynamically adjusted through real-time collection and analysis of the electroencephalogram signals so as to achieve personalized depression treatment, and the multi-modal data comprise the electroencephalogram signals, the stimulation frequency or intensity of transcranial magnetic stimulation, the stroboscopic frequency, the illumination intensity, the illumination color, the music rhythm, the music frequency band and the volume. Besides, according to the scheme, through an innovative artifact elimination algorithm and an electromagnetic shielding technology, the accuracy of EEG signal acquisition is greatly improved, and the problem that an existing TMS and EEG combined device is often subjected to electromagnetic interference and artifacts is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical equipment, and in particular to a neuromodulatory multimodal antidepressant therapeutic apparatus. Background Art

[0002] Most existing depression treatment devices can only apply a single technology and lack effective integration of multimodal therapy. At the same time, most existing devices do not combine electroencephalogram (EEG) signals for real-time monitoring and feedback adjustment, resulting in insufficient personalized treatment. Since traditional devices lack real-time monitoring of biological signals such as EEG, it is difficult to optimize treatment intensity and parameters based on neural feedback during treatment. In addition, during the synchronous acquisition of TMS and EEG, electromagnetic interference and motion artifacts have a significant impact on signal quality and are difficult to effectively eliminate. Summary of the invention

[0003] The technical purpose of the present invention is to solve the problems existing in the current treatment of depression, such as insufficient integration of multimodal treatment methods, low personalization, and difficulty in real-time monitoring and adjustment. In order to achieve the above technical purpose, the specific technical solution is as follows.

[0004] A neuro-regulated multimodal antidepressant therapeutic apparatus, wherein the apparatus dynamically adjusts multimodal data according to an electroencephalogram (EEG) signal analysis result to achieve personalized depression treatment; the multimodal data includes electroencephalogram (EEG) signals, stimulation frequency or intensity of transcranial magnetic stimulation, stroboscopic frequency, light intensity, light color, music rhythm, music frequency band, and volume; wherein the EEG signals are collected by an EEG signal collection circuit, the stimulation frequency or intensity of transcranial magnetic stimulation is adjusted by a transcranial magnetic stimulation circuit, the stroboscopic frequency, light intensity or light color is adjusted by a stroboscopic therapy control circuit, and the music rhythm and music frequency band are adjusted by an audio DAC analysis circuit to achieve expected music playback and volume adjustment; the transcranial magnetic stimulation circuit, stroboscopic therapy control circuit, audio DAC analysis circuit, and EEG signal collection circuit are integrated by a single-chip microcomputer.

[0005] In one implementation of the above technical solution, the therapeutic apparatus further includes a Bluetooth module and a host computer. The Bluetooth module exchanges data with the single-chip microcomputer via serial port communication and exchanges data with the host computer in a transparent transmission manner.

[0006] In one implementation of the above technical solution, the EEG signal acquisition circuit adopts the ADS1299 chip, and uses a shielded cable to connect the electrodes and the front-end amplifier to reduce the electromagnetic interference of the transcranial magnetic stimulation magnetic pulse to the circuit, and the shielding layer should be grounded to ensure effective shielding of external electromagnetic interference; the EEG signal collected by the EEG signal acquisition circuit uses an artifact elimination algorithm to eliminate artifacts.

[0007] In one implementation of the above technical solution, the antidepressant therapeutic device is in the form of a helmet and is worn on the head during use.

[0008] In one implementation of the above technical solution, the multimodal data is recorded with a timestamp and uploaded to a host computer in real time. The data of different modalities are stored in a queue through a data buffer and matched and merged according to the timestamp.

[0009] In one implementation of the above technical solution, a machine learning model is deployed in the host computer, and the machine learning model adjusts the stimulation parameters in real time according to the multimodal data.

[0010] In one embodiment of the above technical solution, the dynamic adjustment of multimodal data based on the results of EEG signal analysis includes: performing frequency analysis on the collected EEG signals to extract the amplitude information of α waves, β waves, γ waves, δ waves, and θ waves; when the β waves and γ waves exceed the set threshold, increasing the frequency and intensity of transcranial stimulation, the frequency and intensity of light therapy stroboscopic light, and playing fast-paced music; when the α waves and θ waves exceed the set threshold and the β waves and γ waves are lower than the set threshold, maintaining a low stimulation intensity, and the stimulation intensity is determined according to the set intensity threshold.

[0011] In one embodiment of the above technical solution, the multimodal data is dynamically adjusted, including: the frequency of the transcranial magnetic stimulation is adjusted to 15Hz as the beta wave is enhanced, to 18-20Hz as the gamma wave is enhanced, and to 1-5Hz as the delta wave and theta wave increase; the intensity of the transcranial magnetic stimulation is adjusted to [60%, 70%) when the alpha wave is stable, and to [80%, 90%] with the beta wave and the gamma wave; its stimulation pulse width varies within the range of 150-400 microseconds to achieve effective stimulation of different frequency bands; the stroboscopic frequency is adjusted to 12-20Hz as the beta wave is enhanced, to 30-40Hz as the gamma wave is enhanced, and to 5-8Hz as the alpha wave and theta wave are enhanced; the light intensity is adjusted to [60%, 70%) when the alpha wave is stable, and to [80%, 90%] with the beta wave and the gamma wave; the ... light intensity is adjusted to [60%, 70%) when the alpha wave is stable, and to [80%, 90%] with the beta wave and the gamma wave; the light intensity is adjusted to [60%, 70%) when the alpha wave is stable, and to [80%, 90%] with the beta wave and the gamma wave; the light intensity is adjusted to [60%, 70%) when the alpha wave is stable, and to [80 The music rhythm is adjusted to 40-60 BPM when the α wave is stable, 80-100 BPM when the β wave is enhanced, and 100-120 BPM when the γ wave is enhanced. The music frequency band is adjusted to medium frequency music when the α wave is enhanced, and to high frequency music when the β wave is enhanced, the medium frequency is 500-1000 Hz, and the high frequency is 1000-3000 Hz. The volume is adjusted to 30%-50% when the α wave is enhanced, and to 70%-80% when the β wave is enhanced. In the same time window, if the absolute value of the amplitude change of the wave does not exceed the set threshold, the wave is judged to be stable.

[0012] In one implementation of the above technical solution, the EEG signal is visualized on a host computer.

[0013] The beneficial technical effects of the present invention are as follows: by organically combining transcranial magnetic stimulation, stroboscopic therapy and music therapy, and combining with real-time monitoring of EEG, the treatment parameters are dynamically adjusted to provide a personalized, intelligent multimodal depression treatment program. Through innovative artifact elimination algorithms and electromagnetic shielding technology, the accuracy of EEG signal acquisition is greatly improved, solving the problem of electromagnetic interference and artifacts that existing TMS and EEG combined devices are often subject to. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0015] Figure 1 , one Schematic diagram of the use of a helmet-type neuromodulatory multimodal antidepressant therapeutic device in an embodiment.

[0016] Figure 2 , one An overall block diagram of the circuit in an implementation manner.

[0017] Figure 3 , one A flowchart of an audio DAC analysis circuit in an implementation manner.

[0018] Figure 4 , one A flow chart of an integrated transcranial magnetic stimulation circuit in an embodiment.

[0019] Figure 5 , one A flow chart of a stroboscopic therapy control circuit in an embodiment.

[0020] Figure 6 , one A flow chart of the EEG acquisition circuit in this embodiment.

[0021] In the figure, 1 is a frontal EEG acquisition dry electrode, 2 is an LED array, 3 is a high-fidelity headset, and 4 is a TMS magnetic coil; E is an EEG signal, L is a light signal, M is HiFi music, P is a pulsed magnetic field signal, and D is data. 1-1 is an EEG acquisition circuit, 2-1 is a stroboscopic therapy control circuit, 3-1 is an audio DAC analysis circuit, 4-1 is an integrated transcranial magnetic stimulation circuit, 5 is a single-chip microcomputer, 6 is a Bluetooth module, 7 is an SD card storage circuit, 8 is a host computer software, 9 is a power management module, 10 is a crystal oscillator, 11 is a master music, 12 is a DAC chip, 13 is a first operational amplifier circuit, 14 is a first filter circuit, 15 is a pulse current control, 16 is a first temperature control and protection circuit, 17 is a second temperature control and protection circuit, 18 is a stroboscopic control circuit, 19 is a second operational amplifier circuit, 20 is a second filter circuit, and 21 is an analog-to-digital converter (ADC). DETAILED DESCRIPTION

[0022] The following will be combined with the accompanying drawings to clearly and completely describe how the technical solution of this case organically combines transcranial magnetic stimulation (TMS), stroboscopic therapy and music therapy, and combines real-time monitoring of EEG to dynamically adjust treatment parameters to provide a personalized, intelligent, multimodal depression treatment plan. Obviously, the described implementation is only a part of the implementation of this case, not all of the implementations. Based on the implementation in this case, all other implementations obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0023] (I) Composition of therapeutic device

[0024] In this case, the neuromodulatory multimodal antidepressant therapeutic device is designed as a helmet. The integrated input and output ends of the head include: frontal EEG acquisition dry electrodes (1), LED arrays (2), high-fidelity headphones (HiFi headphones) (3), and magnetic coils (4). Among them, the magnetic coil is a transcranial magnetic stimulation output device, which is used to generate a high-intensity magnetic field and is placed on the surface of the scalp through the coil. The generated magnetic pulses can penetrate the skull and stimulate brain neurons; the magnetic coil is generally fixed on the scalp corresponding to the left dorsolateral prefrontal cortex (DLPFC). DLPFC is a key area in the brain responsible for emotion regulation and cognitive function. Studies have shown that the DLPFC of patients with depression often has a reduced activity. Therefore, activating this area through TMS can improve mood and relieve depressive symptoms. Sometimes, low-frequency TMS is also used to stimulate the right DLPFC to inhibit overactive neural activity. This method can adjust the stimulation plan according to the specific situation of the patient. The LED array is usually placed in front of the face to ensure that light can enter the brain through the eyes and stimulate the area that regulates biological rhythms. The device is usually equipped with a light therapy lamp or headgear that shines a specific wavelength of light directly onto the patient's face, especially the area around the eyes. The light should not be directly onto the retina to prevent discomfort, and the angle and distance will be adjusted according to the device design and treatment plan. Figure 1 shown.

[0025] See also Figure 2 The therapeutic apparatus realizes data communication and control among an integrated transcranial magnetic stimulation circuit (4-1), a stroboscopic therapy control circuit (2-1), an audio DAC analysis circuit (3-1), an EEG acquisition circuit (1-1), a Bluetooth module (6) and an SD card storage circuit (7) through a single-chip microcomputer (5). The power supply is supplied to each circuit through a power management module (9). The data transmission with the host computer software is completed through data transparent transmission of the Bluetooth module. Under the control of the single-chip microcomputer, the fine control of each circuit can be realized, the mode intensity of the pulse magnetic field (P) output by the transcranial magnetic stimulation circuit can be set; the specific HiFi music (M) content and music playing time of the music therapy can be switched; the stroboscopic mode and light intensity of the LED light signal (L); the start time and stop time of the collected EEG (E) data; the data (D) of the SD card storage circuit can be stored, and the communication with the host computer software (8) can be completed through Bluetooth.

[0026] The above-mentioned Bluetooth module exchanges data with the microcontroller through serial port communication and exchanges data with the host computer software in a transparent transmission manner.

[0027] The SD card storage circuit is used to store real-time data of EEG acquisition, TMS treatment parameters, patient treatment records, and music therapy audio files. The treatment records include EEG data, TMS parameters, light therapy, and music therapy parameters during each treatment of the patient.

[0028] Next, each circuit is described in detail.

[0029] (1.1) Audio DAC analysis circuit

[0030] The core function of DAC audio analysis circuit is to convert digital audio signals into analog signals. In music therapy, outputting high-fidelity and pleasant music is crucial to the entire treatment process. Therefore, a good audio DAC analysis circuit design is very necessary, and choosing a high-quality DAC chip is the primary task of audio analysis circuit design.

[0031] In one implementation, a Texas Instruments PCM1794A chip is selected: 24-bit DAC, supports 192kHz sampling rate, suitable for high-precision audio. The input interface uses an I2S interface: widely used in audio transmission, supports high-precision and high-sampling rate audio transmission, and is suitable for audio processing.

[0032] The block diagram of the audio DAC analysis circuit is as follows: Figure 3 As shown, the dotted box is an audio DAC analysis circuit (3-1). After the master music (11) is stored through the SD card storage circuit (7), the DAC chip (12) is used to convert the digital audio signal into an analog signal, and a first operational amplifier circuit (13) is used as an output buffer circuit to amplify and filter the signal to ensure that the output audio signal is clean and distortion-free. Then, a low-pass filter is used at the analog output end through the first filter circuit (14), and a typical third-order filter is used to filter out high-frequency noise.

[0033] In one embodiment, the operational amplifier in the first operational amplifier circuit is a high-performance operational amplifier-OPA1612, which has low noise and low distortion and is suitable for high-fidelity audio systems, while the amplifier in the high-fidelity headphones (3) uses a TPA6120A2 chip to ensure high power output without distortion.

[0034] At the same time, clock jitter will affect the accuracy of the audio signal, so a high-precision clock source is essential. The low-jitter crystal oscillator (10) of CCHD-957 is used to provide a stable clock signal for the DAC through the control of the microcontroller (5) to reduce distortion.

[0035] In order to prevent power supply noise from affecting audio quality, the power provided by the power management module (9) uses a low-noise LDO regulator of TPS7A47 for DAC and operational amplifier processing to provide a stable, low-noise power supply to the audio DAC analysis circuit (3-1). At the same time, capacitors are used to decouple the power supply and filter out high-frequency noise.

[0036] (1.2) Integrated transcranial magnetic stimulation circuit

[0037] The basic principle of transcranial magnetic stimulation is to generate a pulsed magnetic field through a rapidly changing current, which in turn induces current in the cerebral cortex and affects the activity of neurons. The control of the intensity and frequency of the magnetic field directly determines the stimulation effect.

[0038] The core task of the integrated transcranial magnetic stimulation circuit is to use electromagnetic pulses to non-invasively stimulate specific areas of the brain, such as the dorsolateral prefrontal cortex, to regulate neural activity. The specific working principle is: the current passes through the magnetic coil to generate an instantaneous strong magnetic field. The strong magnetic field is usually 1-2.5 Tesla. The magnetic field penetrates the scalp and skull, generating an induced current in the cerebral cortex. The induced current stimulates neurons to achieve a therapeutic effect.

[0039] The integrated transcranial magnetic stimulation circuit is composed of the following main parts: ① High-voltage power supply: provides fast-switching high current to ensure that the coil can generate sufficient magnetic field strength. ② Pulse current control circuit (15): controls the current intensity and pulse width passing through the magnetic coil (4), thereby adjusting the intensity of the magnetic field and the intensity of stimulation. ③ Selection and design of magnetic coil (4): The shape and size of the magnetic coil directly affect the distribution of the magnetic field and the depth of stimulation. ④ The first temperature control and protection circuit (16): is used to protect the main circuit and the human body. When the current or voltage is too high, it is used to prevent damage caused by excessive current or voltage by fusing. The details are as follows.

[0040] The TMS circuit needs to generate a strong magnetic field through inductance, and must have a large voltage source that can provide instantaneous high current. The commonly used design scheme for high-voltage power supply is the capacitor discharge circuit, which selects high-quality, high-voltage capacitors and charges them through a high-voltage DC power supply. When the control circuit sends a signal, the capacitor discharges quickly, generating a large current through the magnetic coil, thereby generating a high-intensity pulse magnetic field. The high voltage range is [250V, 400V].

[0041] Next is the pulse current control circuit design. Transcranial magnetic stimulation requires current pulses that rise and fall quickly, which are achieved through a pulse generator circuit: Semiconductor switch (such as IGBT or MOSFET): used to accurately control the opening and closing of capacitor discharge, determining the frequency and duration of the pulse. Pulse control unit: The frequency and duty cycle of the pulse are controlled by a single-chip microcomputer (such as STM32), and the intensity of stimulation can be adjusted according to the treatment plan. The pulse frequency is usually between 1Hz and 10Hz, and is used in different treatment scenarios.

[0042] Output magnetic coil design: The coil usually adopts an "8" shaped coil (butterfly coil), which can concentrate the magnetic field and increase the local stimulation intensity; the number of turns and inductance of the coil are designed according to the required magnetic field strength. Too high a number of turns will lead to excessive inductance, affecting the current rise time; at the same time, the coil is wrapped with high temperature resistant materials to ensure that there will be no overheating problems during long-term use.

[0043] In addition, since high current may cause overheating of coils and other devices, a temperature monitoring circuit must be designed. When the temperature is too high, the current is adjusted by PWM or the power is directly cut off, and fuses are added to protect the equipment and users. The upper limit of the current is strictly limited to ensure that no harm is caused to the user, especially the pulse rise time and current peak value need to be controlled.

[0044] (1.3) Stroboscopic therapy control circuit

[0045] The core task of the stroboscopic therapy control circuit is to generate light waves of specific wavelengths and frequencies through LEDs for the treatment of neurological diseases such as depression. Stroboscopic therapy aims to regulate the patient's brain activity through light stimulation, especially the neural circuits related to mood and sleep regulation. The flow chart of the stroboscopic therapy control circuit is shown in the figure. Figure 5 shown.

[0046] The first is the choice of LED. For depression treatment, the commonly used wavelengths are blue light and green light, because these bands can regulate biological rhythms and improve mood. The blue light range is 450-495nm, and the green light range is 495-570nm, and each range includes both end boundary values.

[0047] Frequency selection: Different stroboscopic frequencies have different effects on the brain. Common therapeutic frequency ranges are 10Hz-40Hz: Low frequency: suitable for relaxation and mood regulation. High frequency: can activate the cognitive function of the brain and improve the level of brain activity. The low frequency range is 10-20Hz, and the high frequency range is 30-40Hz, and each range includes the boundary values ​​at both ends.

[0048] The pulse width modulation control is performed by a single chip microcomputer, and the switching frequency and brightness of the LED are controlled by a strobe control circuit (18). Various control modes can be designed or customized according to user conditions.

[0049] Security design:

[0050] 1. Eye protection: During phototherapy, it is necessary to prevent light from directly entering the retina to prevent damage to the eyes. The design can ensure that the light is concentrated in the treatment area by limiting the angle of light or designing a shading device.

[0051] 2. Overcurrent and overvoltage protection: Overcurrent and overvoltage protection functions are designed for the LED drive circuit to prevent unexpected voltage fluctuations or excessive current from damaging the LED or control circuit.

[0052] 3. Temperature monitoring: The light source may overheat if it works for a long time. By designing the second temperature control and protection circuit (17), the power will be automatically reduced or the operation will be stopped when the temperature of the LED is too high.

[0053] (1.4) EEG acquisition circuit

[0054] The function of the EEG acquisition circuit is to collect the patient's EEG signals in real time to evaluate neural activity and treatment effects. EEG signals are mainly composed of waveforms of different frequencies, including α waves, β waves, γ waves, δ waves, etc. These waveforms represent different brain activity states and can reflect the brain's attention, relaxation, anxiety and other psychological states.

[0055] Specifically, EEG is collected by highly conductive dry electrodes. When designing an EEG collection circuit, it is necessary to consider how to reduce electromagnetic interference during the TMS process to ensure the accuracy of the collected signal. The electrical signal is in the microvolt level and is very weak. The signal is amplified by a second operational amplifier circuit (19). In addition, in order to reduce electromyographic interference and high-frequency noise, a second filtering circuit (20) should be designed at the front end. A low-pass filter is used in the second filtering circuit to remove high-frequency interference. A high-pass filter can also be added to remove baseline drift. The amplified analog signal is converted into a digital signal using an analog-to-digital converter (ADC) (21). Exemplarily, the crossover point of the low-pass filter is set below 100 Hz, and the cutoff frequency of the high-pass filter is set at 0.1 Hz.

[0056] In order to reduce the impact of TMS on EEG acquisition, it is also necessary to consider dry magnetic interference. Use shielded cables to connect the electrodes and the front-end amplifier to reduce the electromagnetic interference of TMS magnetic pulses on the circuit. The shielding layer should be grounded to ensure effective shielding of external electromagnetic interference. Artifacts should also be eliminated by the artifact elimination algorithm on the host computer. The EEG acquisition circuit flow chart is as follows Figure 6 shown.

[0057] In one embodiment, a high-gain, low-noise differential amplifier is used in the second operational amplifier circuit to amplify the signal. The differential amplifier is specifically AD8237, which has low input noise and high common mode rejection ratio (CMRR), and can effectively suppress power supply noise and interference signals.

[0058] In one embodiment, the analog-to-digital converter uses an ADS1299 chip, which has a 24-bit high resolution to ensure a sufficient dynamic range, and a sampling rate between 250-1000 Hz, capable of capturing key frequency band information in EEG, such as alpha waves, beta waves, gamma waves, and delta waves.

[0059] Alpha waves: The frequency range is 8-13Hz, usually associated with a relaxed, closed-eyes resting state. When a person is relaxed, closed-eyes meditating, alpha waves increase. Moderate alpha waves can reflect a calm and focused state.

[0060] Beta waves: The frequency range is 13-30Hz, usually associated with wakefulness, thinking, concentration, and tension. When a person is focused on a task, beta wave activity increases, especially in the frontal and parietal regions.

[0061] Gamma waves: The frequency range is 30-100Hz, which is related to higher cognitive functions, learning and memory. Gamma waves are active when the brain is in a state of high concentration and information processing.

[0062] Delta Waves: The frequency range is 0.5-4Hz, usually associated with deep sleep. Increased delta wave activity usually reflects the brain's repair and recovery process. Theta Waves: The frequency range is 4-8Hz, associated with light sleep, relaxation, meditation and other states. Increased theta waves usually indicate that the brain is in a state of relaxation but still alert.

[0063] (II) Therapeutic instrument data processing

[0064] (2.1) Simultaneous analysis and processing of multimodal data

[0065] Multimodal data include EEG signals, TMS parameters, light therapy frequency, and music therapy rhythm. In order to ensure the accuracy of treatment, these data need to be analyzed and processed synchronously.

[0066] In synchronous analysis, a synchronization mechanism is required for the data, including timestamp synchronization, data buffering and synchronous transmission. The timestamp synchronization means that all collected EEG signals, TMS trigger signals, phototherapy stroboscopic signals and music playback data should be recorded by a unified clock source (realized by the crystal oscillator of the hardware circuit, clock source) for timestamp recording to ensure that all data are synchronously analyzed on the same timeline. A high-precision crystal oscillator can be used as the main clock source for the entire system. The data buffering and synchronous transmission refer to the real-time transmission of each data source to the host computer software, the storage of data of different modes in the form of queues through the data buffer, and the matching and merging according to the timestamp.

[0067] When processing multimodal data, it means to perform fusion analysis on multimodal data, and the steps include:

[0068] (2.1.1) Fast Fourier Transform: Perform frequency domain analysis on EEG data and extract the power spectrum intensity of α, β, γ, θ, and δ waves.

[0069] (2.1.2) Multi-source data fusion algorithm: Through weighted fusion algorithms, such as Kalman filtering and Bayesian fusion, comprehensive analysis is performed on EEG frequency band signals, TMS parameters, phototherapy frequency, and music rhythm to obtain information such as the patient's attention, relaxation level, and cognitive state.

[0070] (2.1.3) Joint analysis of frequency domain and time domain: This includes analyzing the frequency domain components of EEG and the time domain signals to capture transient EEG changes and the immediate effects of TMS pulses on EEG.

[0071] In one embodiment, in the EEG signal analysis, a radar chart is used to display the amplitudes of different brain waves. For example, each corner represents a brain wave component, such as alpha wave, beta wave, gamma wave, etc. The amplitude (power) of each waveform represents its share in the entire EEG activity. Through the radar chart, the strength of the brain's activities in different frequency bands at a certain moment can be intuitively observed, which is convenient for assessing the patient's emotions and attention state. The radar chart is a commonly used visualization tool for displaying multidimensional data.

[0072] In one embodiment, in the analysis of EEG signals, attention is specifically analyzed. The analysis of attention is mainly based on the activity of beta waves and gamma waves. The following is an idea for attention analysis based on different EEG waves: Beta wave activity: Beta waves are usually associated with wakefulness, concentration, and cognitive tasks. When performing focused tasks such as reading, calculating, or operating, the beta waves in the frontal and parietal regions are significantly enhanced. Therefore, the state of attention can be analyzed by detecting the intensity of beta wave activity. Gamma wave activity: Gamma waves are associated with advanced cognitive functions, information processing, and learning. When attention is highly focused, the frequency and intensity of gamma waves increase. Therefore, the increase in gamma wave activity usually reflects a high level of attention. Alpha wave suppression: When the brain switches from a relaxed state to a focused state, the alpha wave is suppressed. Therefore, if the alpha wave activity is low and the beta and gamma waves are strong, it means that the brain is in a state of high concentration.

[0073] In one embodiment, when analyzing attention, an attention index is calculated. An attention index can be calculated based on the power of different waveforms. For example, a baseline value is set, and a quantitative attention level is obtained according to the strength ratio of α wave, β wave, and γ wave as a reference for real-time analysis.

[0074] In one embodiment, the above analysis of EEG signal components, attention analysis, and calculation of attention index can be completed by host computer software. Specifically, the host computer software completes the above analysis and calculation by receiving the collected EEG data and control and feedback data of the therapeutic device, reading audio files from the SD card, performing data preprocessing and eliminating TMS artifacts, storing and displaying EEG signal time domain graphs and frequency domain graphs, etc., and stores the analysis results for subsequent comparison and long-term tracking. In addition, the host computer software also provides a platform for human-computer interaction. The host computer software monitors and controls the treatment process, adjusts the treatment parameters in real time, and provides personalized intelligent feedback adjustment.

[0075] The control and feedback data of the above-mentioned treatment equipment include feedback data of the transcranial magnetic stimulation equipment, control data of the stroboscopic therapy equipment and control data of the music therapy. Among them: the feedback data of the transcranial magnetic stimulation equipment includes parameters such as the pulse frequency, intensity, and pulse width of TMS. The host computer receives these data and adjusts the parameters of TMS in real time in combination with EEG signal analysis. The control data of the stroboscopic therapy equipment includes parameters such as the stroboscopic frequency and light intensity of the phototherapy equipment. These data can also be received and controlled by the host computer software to adjust the intensity and rhythm of the phototherapy. The control data of the music therapy includes receiving and reading the music playback status, and dynamically adjusting the rhythm and volume of the music according to the changes in the EEG signal. The playback status includes the rhythm, frequency, volume, etc. of the currently playing music.

[0076] (2.2) Synchronous feedback and adjustment mechanism of multimodal data

[0077] Real-time feedback algorithm: By integrating EEG signals, TMS output, light therapy parameters and music rhythm, a real-time feedback closed-loop system is formed to continuously adjust the stimulation parameters. The machine learning model is used to predict the patient's status and optimize the stimulation parameters. The machine learning model may be LSTM, BiLSTM, RAN, etc.

[0078] Adaptive parameter adjustment: Based on the real-time EEG data of different patients, the system automatically learns the patient's response to various treatment parameters and forms a personalized treatment model. In each cycle, the system updates the adjustment strategy based on EEG data and patient feedback. For example, one cycle is set to 10 seconds.

[0079] Linkage adjustment: TMS, light therapy and music therapy are adjusted synchronously according to the EEG analysis results. For example, when the patient is detected to be in a state of high concentration, their beta and gamma waves are significantly enhanced, the TMS stimulation frequency is increased, the light therapy stroboscopic frequency is synchronously increased, and the music rhythm is accelerated, achieving the linkage effect of multimodal treatment.

[0080] (2.3) Data recording and optimization

[0081] Data recording: EEG data, TMS parameters, light therapy and music therapy parameters during each treatment process are recorded for later analysis and model optimization to form a more accurate adjustment plan.

[0082] Model training: Use personal historical data to train the neural network model and gradually optimize the multimodal parameter adjustment scheme to ensure more accurate treatment in the future.

[0083] (III) Personalized use of therapeutic devices

[0084] When the neuromodulation multimodal antidepressant therapeutic device is used, it is dynamically adjusted according to the results of EEG signal analysis. It mainly monitors the patient's EEG activity in real time and adjusts the stimulation intensity, frequency, rhythm and other parameters of TMS, stroboscopic therapy and music therapy in time to achieve personalized and precise treatment effects. The correlation between EEG signal analysis results and treatment parameters is shown below.

[0085] (3.1) When the alpha wave is between 8 and 13 Hz, it indicates a state of emotional relaxation. When the alpha wave intensity is high, it indicates that the patient is in a state of relaxation, and treatment can focus on maintaining or strengthening this state of relaxation. Adjustment measures, TMS: reduce the intensity or frequency of TMS stimulation to avoid overstimulation and maintain the patient's state of relaxation. Light therapy: reduce the frequency and intensity of light therapy to keep the patient relaxed. Music therapy: play slow, soothing music to maintain a relaxing atmosphere.

[0086] (3.2) When the beta wave is between 13-30Hz, it indicates a state of concentration. When the beta wave intensity increases, it indicates that the patient is concentrating or is in a state of wakefulness. Adjustment measures: TMS: Increase the stimulation frequency of TMS to enhance the stimulation of the prefrontal lobe, promote attention and cognitive ability. Light therapy: Moderately increase the frequency and light intensity of light therapy to stimulate the visual cortex and enhance the patient's alertness. Music therapy: Choose music with a faster rhythm to enhance the brain's alertness and attention.

[0087] (3.3) When the gamma wave is between 30-100Hz, it indicates that the brain is engaged in advanced cognitive activities. When the gamma wave activity is enhanced, it indicates that the patient's brain is in a state of advanced cognition and information processing. Adjustment measures: TMS: Maintain a high stimulation frequency to support advanced cognitive activities and ensure that the stimulation is not excessive. Light therapy: Moderately increase the flashing frequency to synchronize the activity of the gamma wave and enhance cognitive efficacy. Music therapy: Select music with complex rhythms and melodies to further activate the brain's cognitive functions.

[0088] (3.4) When the delta wave is between 0.5-4Hz and the theta wave is between 4-8Hz, it indicates a state of rest and meditation. When the delta wave and theta wave are enhanced, it means that the patient may be in a state of deep relaxation, rest or sleep. Adjustment measures: TMS: Reduce or pause TMS stimulation to avoid disturbing the patient's deep rest. Light therapy: Reduce the light intensity and adjust the frequency to a lower level to avoid stimulating the patient. Music therapy: Play meditation music to assist the patient in entering a deeper state of relaxation.

[0089] In one embodiment, the treatment parameters are dynamically adjusted in combination with real-time monitoring of EEG. The dynamic adjustment process is as follows.

[0090] First, the EEG acquisition system collects EEG signal data in real time and transmits it to the host computer software for processing. The "Fast Fourier Transform (FFT)" algorithm is used to perform frequency analysis on the EEG signal to extract the amplitude information of the frequency components of each brain wave, such as α, β, γ, δ, and θ waves.

[0091] Next, according to the amplitude of different brain waves, the threshold range is set to determine the patient's current neurological state. When the beta wave and gamma wave exceed the set threshold, it means that the patient is in a state of concentration, and the TMS frequency, light therapy stroboscopic frequency and music rhythm are increased. When the alpha wave is higher than the set threshold and the beta wave and gamma wave are lower than the threshold, it means that the patient is relaxed or has slight attention and needs to maintain a low stimulation intensity. The stimulation intensity is determined according to the set intensity threshold. The parameters of TMS, light therapy and music therapy are automatically adjusted through the control algorithm in the upper computer software.

[0092] A more specific dynamic adjustment method is shown below.

[0093] (3.4.1) TMS parameter adjustment

[0094] (3.4.1.1) Frequency range, from low frequency 1Hz to high frequency 20Hz, dynamically adjusted according to the activity of EEG gamma and beta waves:

[0095] Beta waves were significantly enhanced, indicating focused attention: the TMS frequency was gradually adjusted from the initial 10 Hz to 15 Hz to further activate the cognitive function of the prefrontal cortex.

[0096] Gamma waves are enhanced, indicating higher-level cognitive activity: TMS frequency is further adjusted to 18-20Hz to enhance higher-level cognitive processing capabilities.

[0097] Delta and theta waves increase, indicating a state of relaxation: The TMS frequency is adjusted to 1-5 Hz to reduce stimulation to the patient and maintain a state of relaxation.

[0098] (3.4.1.2) Stimulation intensity: Initially set at 70% to 100% maximum output, intensity adjustment based on real-time feedback from EEG signals:

[0099] When the α wave is stable: gradually adjust the TMS intensity to [60%, 70%) to avoid overstimulation. Within the same time window, if the absolute value of the amplitude change of the wave does not exceed the set threshold, the α wave is judged to be stable.

[0100] Beta wave and gamma wave enhancement: gradually adjusted to 80%-90% to enhance the stimulation effect.

[0101] (3.4.1.3) Stimulation pulse width: initially set to 200 μs, dynamically adjusted according to the instantaneous changes in the EEG signal, varying within the range of 150-400 μs to achieve effective stimulation of different frequency bands.

[0102] A calculation method for the above-mentioned α wave amplitude fluctuation is: by calculating the power spectral density (PSD) in the frequency band, if the absolute value of the amplitude change is within the set threshold range, the α wave signal can be considered to be stable. For example, in a relaxed state, if the power spectrum of the α wave continues to remain at a relatively high stable value and does not drop or fluctuate significantly. Exemplarily, the threshold is set to 10%, and the amplitude fluctuation does not exceed ±10%, and the signal is considered to be stable.

[0103] (3.4.2) Adjustment of phototherapy parameters

[0104] (3.4.2.1) Strobe frequency, initially set to 10 Hz, with a dynamic adjustment range of 5-40 Hz:

[0105] Relaxation state: Alpha and theta waves are enhanced, and the light therapy stroboscopic frequency is adjusted to 5-8Hz to enhance the patient's sense of relaxation.

[0106] Concentrate your attention and significantly enhance beta waves. Adjust the light therapy stroboscopic frequency to 12-20Hz to synchronize brain waves to promote concentration.

[0107] Advanced cognitive activity, gamma wave enhancement, increase the light therapy strobe frequency to 30-40Hz to activate the brain's advanced information processing functions.

[0108] (3.4.2.2) Light intensity: set within the range of 10%-100% of the light intensity, and adjust in real time according to the intensity of the α, β, and γ waves of the EEG:

[0109] Relaxation state: light intensity is maintained at 30%-50% to avoid overstimulation.

[0110] Enhanced Attention: Light intensity is increased to 60%-80%, activating the visual cortex.

[0111] Advanced cognitive activities: Light intensity can be increased to 90%-100% to enhance the stimulation effect.

[0112] (3.4.2.3) Light color: Dynamically adjust LED color based on analysis of EEG bands and emotional state:

[0113] When relaxing: choose gentle warm colors, such as yellow light and orange light.

[0114] When you need increased focus: Choose blue, green or white light for increased alertness.

[0115] (3.4.3) Music therapy parameter adjustment

[0116] (3.4.3.1) Music rhythm: The initial rhythm is set to 60BPM, which can be adjusted within the range of 40-120BPM:

[0117] Relaxation state: Alpha and theta waves are enhanced, and the music tempo is reduced to 40-60BPM to provide a soothing environment.

[0118] Concentration: Beta waves are enhanced, and the music rhythm is adjusted to 80-100BPM to enhance attention and concentration.

[0119] Advanced cognitive activities: Gamma waves are enhanced, and the music rhythm can be increased to 100-120BPM to stimulate brain activity.

[0120] (3.4.3.2) Music frequency band: Analyze the EEG spectrum and select the music frequency band that is synchronized with the brain waves:

[0121] Alpha wave enhancement: select music with medium frequency to enhance the relaxation effect. For example, the medium frequency range is [500Hz, 1000Hz].

[0122] Beta wave enhancement: Select high-frequency (1000-3000Hz) music to promote attention and cognitive ability. Exemplarily, the high-frequency range is [1000Hz, 3000Hz].

[0123] (3.4.3.3) Volume adjustment: The volume is adjusted in real time according to the EEG signal, ranging from 30% to 80%. If the reference volume is used as a reference, the user must be kept comfortable at the reference volume, and the volume cannot be too high. The reference volume is set to 50-60dB, for example.

[0124] When concentrating: adjust the volume to 70%-80% to enhance music stimulation.

[0125] Relaxed state: reduce volume to 30%-50% to avoid distractions.

[0126] The host computer software updates the results based on the EEG data of each time window (such as 5 seconds), automatically adjusts the TMS, light therapy and music parameters to optimize the treatment effect. The modes of different treatment stages (such as relaxation mode, focus mode, etc.) can be set to achieve intelligent switching of treatment plans (at the beginning, the plan can be customized for each patient in combination with the guidance of clinicians. Personal data of patients may be collected for model training and precision treatment).

[0127] In one embodiment, initially, TMS: the starting frequency is set at 10Hz and the intensity is at a medium level. Light therapy: the starting frequency is set at 12Hz and the light intensity is 50%. Music therapy: play light music with a moderate rhythm (60-80BPM). When the beta wave increases significantly (the patient is concentrating), TMS: increase to 15Hz and increase the intensity by 10%. Light therapy: the frequency is increased to 18Hz and the light intensity is increased to 70%. Music therapy: play music with a faster rhythm (80-100BPM) to enhance the patient's concentration. When the alpha wave is significantly enhanced (the patient is relaxed), TMS: reduce to 8Hz and reduce the intensity by 10%. Light therapy: reduce the frequency to 10Hz and reduce the light intensity to 40%. Music therapy: switch to more soothing music and reduce rhythm changes. When the gamma wave is enhanced (higher cognitive activity), TMS: maintain high-frequency stimulation (20Hz) to promote cognitive activity. Light therapy: the frequency is synchronized with the gamma wave to reach 30Hz. Music therapy: play music with complex melodies to support cognitive function.

[0128] In the above music therapy, the volume needs to be adjusted in real time according to the EEG signal. For example, when concentrating, the volume is adjusted to 70%-80% to enhance the music stimulation. When in a relaxed state, the volume is reduced to 30%-50% to avoid interference.

[0129] In the above-mentioned music therapy, the selected music should pay attention to the beats per minute (BPM). The higher the BPM value, the faster the music rhythm; the lower the value, the slower the music rhythm. In music therapy, adjusting the BPM can affect the patient's mood and attention state. For example, a lower BPM (such as 40-60BPM) can help patients relax, while a higher BPM (such as 80-120BPM) can enhance attention and improve cognitive activity.

[0130] The above-mentioned parameters such as the stimulation intensity, frequency, and rhythm of TMS, stroboscopic therapy, and music therapy are adjusted mainly by the user through the host computer software, which can set the treatment goals, such as relaxation, concentration, meditation, etc., and the host computer software automatically adjusts the parameters of TMS, light therapy, and music. The changes in brain wave frequency and intensity are monitored through the host computer interface, and the treatment plan is adjusted in real time to ensure the best treatment effect.

[0131] Although the embodiments of the present invention are described above in conjunction with the accompanying drawings, the present invention is not limited to the above-mentioned specific embodiments and application fields, and the above-mentioned specific embodiments are only illustrative and instructive, but not restrictive. A person skilled in the art can make many forms under the guidance of this specification and without departing from the scope of protection of the claims of the present invention, all of which belong to the protection of the present invention.

Claims

1. A neuromodulation multimodal antidepressant therapeutic device, characterized in that: The therapeutic device dynamically adjusts multimodal data according to the EEG signal analysis results to achieve personalized depression treatment; The multimodal data includes EEG signals, stimulation frequency or intensity of transcranial magnetic stimulation, stroboscopic frequency, light intensity, light color, music rhythm, music frequency band, and volume; The EEG signal is collected by an EEG signal collection circuit, the stimulation frequency or intensity of the transcranial magnetic stimulation is adjusted by a transcranial magnetic stimulation circuit, the stroboscopic frequency, light intensity or light color is adjusted by a stroboscopic therapy control circuit, and the music rhythm and music frequency band are adjusted by an audio DAC analysis circuit to achieve the expected music playback and volume adjustment; The transcranial magnetic stimulation circuit, the stroboscopic therapy control circuit, the audio DAC analysis circuit, and the electroencephalogram signal acquisition circuit are integrated through a single-chip microcomputer.

2. The antidepressant therapeutic apparatus according to claim 1, characterized in that: The therapeutic apparatus further comprises a Bluetooth module and a host computer. The Bluetooth module exchanges data with the single-chip microcomputer via serial port communication and exchanges data with the host computer in a transparent transmission manner.

3. The antidepressant therapeutic apparatus according to claim 1, characterized in that: The EEG signal acquisition circuit adopts the ADS1299 chip, and uses a shielded cable to connect the electrode and the front-end amplifier to reduce the electromagnetic interference of the transcranial magnetic stimulation magnetic pulse on the circuit, and the shielding layer should be grounded to ensure effective shielding of external electromagnetic interference; The electroencephalogram signal collected by the electroencephalogram signal collection circuit is subjected to artifact elimination by using an artifact elimination algorithm.

4. The antidepressant therapeutic apparatus according to claim 1, characterized in that: The antidepressant therapeutic device is in the form of a helmet and is worn on the head during use.

5. The antidepressant therapeutic apparatus according to claim 1, characterized in that: The multimodal data is recorded with a timestamp and uploaded to a host computer in real time. The data of different modes are stored in a queue through a data buffer and matched and merged according to the timestamp.

6. The antidepressant therapeutic apparatus according to claim 2, characterized in that: A machine learning model is deployed in the host computer, and the machine learning model adjusts stimulation parameters in real time according to multimodal data.

7. The antidepressant therapeutic apparatus according to claim 1, characterized in that: The dynamic adjustment of multimodal data according to the EEG signal analysis results includes: Perform frequency analysis on the collected EEG signals to extract the amplitude information of α wave, β wave, γ wave, δ wave and θ wave; When the beta and gamma waves exceed the set threshold, the frequency and intensity of transcranial stimulation, the frequency and intensity of light therapy stroboscopic light, and fast-paced music are played; When the α wave and the θ wave exceed the set threshold and the β wave and the γ wave are lower than the set threshold, the stimulation intensity is maintained at a low level, and the stimulation intensity is determined according to the set intensity threshold.

8. The antidepressant therapeutic apparatus according to claim 7, characterized in that: The multimodal data is dynamically adjusted, including: The frequency of the transcranial magnetic stimulation is adjusted to 15 Hz as the beta wave increases, to 18-20 Hz as the gamma wave increases, and to 1-5 Hz as the delta and theta waves increase; The intensity of transcranial magnetic stimulation was adjusted to [60%, 70%] when the alpha wave was stable, and to [80%, 90%] with the beta and gamma waves; the stimulation pulse width varied in the range of 150-400 microseconds to achieve effective stimulation of different frequency bands; The stroboscopic frequency is adjusted to 12-20 Hz as the beta wave increases, to 30-40 Hz as the gamma wave increases, and to 5-8 Hz as the alpha and theta waves increase; The light intensity is adjusted to 60%-80% with the enhancement of beta waves and the light color is yellow or orange, adjusted to 90%-100% with the enhancement of gamma waves, and adjusted to 30%-50% with the enhancement of alpha waves and theta waves and the light color is blue or green; The music rhythm is adjusted to 40-60BPM when the α wave is stable, 80-100BPM when the β wave is enhanced, and 100-120BPM when the γ wave is enhanced; The music frequency band is adjusted to the middle frequency music when the α wave is enhanced, and is adjusted to the high frequency music when the β wave is enhanced, the middle frequency is 500-1000Hz, and the high frequency is 1000-3000Hz; The volume is adjusted to 30%-50% when the α wave is enhanced, and to 70%-80% when the β wave is enhanced; Among them, within the same time window, if the absolute value of the amplitude change of the wave does not exceed the set threshold, the wave is judged to be stable.

9. The antidepressant therapeutic apparatus according to claim 2, characterized in that: The electroencephalogram signal is visualized on a host computer.

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