Transcranial focused ultrasound stimulation system and method for cognitive impairment patient

Abstract

The invention belongs to the technical field of transcranial ultrasonic stimulation. A transcranial focused ultrasound stimulation system and method for cognitive impairment patients is provided. The system comprises a main control module, a communication module, a display module, a signal source module, a driving module, an impedance matching module, an ultrasonic transducer module and an ultrasonic coupling module. According to the method, the personalized target spot can be determined according to the actual illness state of the target patient, and the appropriate treatment intensity can be determined, so that the optimal treatment effect can be obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of transcranial ultrasound stimulation, and in particular to a transcranial focused ultrasound stimulation system and method for patients with cognitive impairment. Background Art

[0002] For patients with cognitive impairment, current treatment methods are generally divided into drug treatment and non-drug treatment. Among non-drug treatments, neuromodulation technology is an important treatment method.

[0003] Neuromodulation technology and its application have always been a research hotspot in the field of neuroscience and engineering. In recent years, researchers have gradually become interested in brain therapeutic stimulation through implanted electrodes or non-invasive transcranial electromagnetic field delivery, and these technologies have gradually been widely used in brain disease treatment and brain science research.

[0004] At present, the more mature neuromodulation technologies include implanted electrodes, transcranial electric field and magnetic field stimulation. Transcranial magnetic stimulation (TMS) can safely regulate cortical function, but its spatial resolution is limited and it cannot accurately stimulate specific deep brain areas. Transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS) are also common neuroelectric stimulation technologies. Among them, tDCS shows potential in chronic headaches and memory, but its spatial resolution is low and the stimulation position is shallow. DBS, as an important clinical treatment technology, has been used to suppress tremors in Parkinson's disease, but this technology requires deep brain electrode implantation surgery, which increases the risk of surgical infection. In addition, optogenetics can accurately manipulate the neural activity of single neurons transfected with photosensitive proteins through light of specific wavelengths, which can achieve targeted effects and have unparalleled action accuracy, but it also requires surgery to achieve genetic manipulation.

[0005] In 2010, Tufail et al. published a study on transcranial ultrasound regulation of neural activity in mice. Transcranial focused ultrasound stimulation (tFUS) has rapidly attracted widespread attention and has developed rapidly in recent years due to its non-invasive, safe, high spatial resolution, good penetration and easy combination with other technologies. Ultrasound refers to sound waves with a frequency exceeding 20kHz. This type of high-frequency sound wave has a short wavelength and strong energy, good directionality and penetration, and is therefore widely used in medical, military and industrial fields. Transcranial ultrasound stimulation uses low-frequency and low-intensity ultrasound to act on specific areas of the brain, thereby inducing activation or inhibition of neural activity in that area. Unlike medical treatment that relies on the thermal effect of ultrasound, transcranial ultrasound stimulation mainly uses the mechanical effect of ultrasound to regulate neural activity. The resolution of transcranial focused ultrasound stimulation reaches the millimeter level, which can achieve targeted stimulation of specific brain areas, and the maximum stimulation depth can reach more than 5 cm. In addition, ultrasound is a mechanical wave, so transcranial ultrasound neural stimulation does not interfere with neural electrode technology or magnetic resonance imaging technology, which is conducive to the synchronous recording of neural point activity or neural imaging data under transcranial ultrasound neural stimulation. The following table compares transcranial focused ultrasound stimulation with other common neuromodulation technologies. From the data in the table, it can be seen that transcranial focused ultrasound stimulation technology has the advantages of being non-invasive, high spatial resolution, deep stimulation, and good compatibility with neural monitoring technology.

[0006]

[0007] Currently, neuroregulation for patients with cognitive impairment is mainly based on transcranial magnetic stimulation and transcranial electrical stimulation. There is no mature transcranial focused ultrasound stimulation treatment method, and the regulated area is mostly the prefrontal cortex, which does not have the characteristics of personalized intervention. Summary of the invention

[0008] In this regard, the present invention provides a transcranial focused ultrasound stimulation system, working method, electronic device, computer storage medium and computer program product for patients with cognitive impairment to solve the above-mentioned technical problems.

[0009] The present invention discloses a transcranial focused ultrasound stimulation system for patients with cognitive impairment, the system comprising a main control module, a communication module, a display module, a signal source module, a drive module, an impedance matching module, an ultrasonic transducer module, and an ultrasonic coupling module; wherein the main control module is the core control module of the entire system, and is used to provide the required timer resources for the signal source module, provide the required display data for the display module, provide the required communication data for the communication module, and receive data transmitted by the communication module.

[0010] The signal source module is responsible for generating an online adjustable original signal, which is a pair of PWM signals with complementary polarities and dead time output by the advanced timer of the main control module.

[0011] The driving module is used to amplify the original signal to obtain a driving signal capable of driving the ultrasonic transducer module.

[0012] The impedance matching module is composed of an LC matching network, and its input is the driving signal output by the driving module, and its output is the driving signal after impedance matching.

[0013] The ultrasonic transducer module: its input is the driving signal after impedance matching, which is used to convert the driving signal of the electrical signal into an acoustic signal, that is, to emit focused ultrasonic waves that meet the requirements; wherein the target position of the focused ultrasonic wave stimulation is confirmed based on resting-state functional magnetic resonance imaging.

[0014] The ultrasonic coupling module is responsible for effectively transmitting ultrasonic waves between the ultrasonic transducer module and the object to be measured, and helps to eliminate the difference in acoustic impedance in the air.

[0015] The display module is used to display the parameter information and other stimulation information of the original signal in real time.

[0016] The communication module is used to record and store stimulation logs and communicate with the host computer.

[0017] In some embodiments, the system also includes a target position determination module, which is connected to the communication module; the target position determination module is used to perform the following steps: S1, using resting-state functional magnetic resonance imaging technology to measure the blood oxygen level-dependent signal changes in the target patient's brain at rest, and dividing the brain into several brain regions: frontal lobe, parietal lobe, temporal lobe and occipital lobe.

[0018] S2. For each of the brain regions, calculate the functional connection strength between it and other brain regions, and average the functional connection strengths between each of the brain regions and other brain regions, so as to determine the brain region with the weakest average connection strength, and use it as the target brain region; wherein the functional connection strength is achieved by calculating the correlation between the blood oxygen level-dependent signals between the two brain regions.

[0019] S3, dividing the target brain region into smaller sub-brain regions, repeating the above step S2 for each sub-brain region, and taking the sub-brain region with the weakest average functional connectivity as the target of neural regulation.

[0020] S4. Transmitting the target point to the main control module through the communication module, so that the main control module displays the information of the target point on the display module.

[0021] In some embodiments, any one of Pearson correlation coefficient, local consistency, seed-based functional connectivity, and functional network connectivity analysis methods is used to calculate the correlation of blood oxygen level dependent signals between two brain regions.

[0022] In some embodiments, the system also includes a treatment intensity determination module, which is connected to the communication module; the treatment intensity determination module is used to perform the following steps: collecting first treatment big data of similar patients with the same level of cognitive impairment as the target patient, and second treatment big data of similar patients with a higher level of cognitive impairment than the target patient; wherein the first treatment big data and the second treatment big data contain a number of transcranial focused ultrasound stimulation data, and each of the transcranial focused ultrasound stimulation data contains target information, treatment intensity, cognitive impairment level, and treatment effect information.

[0023] The target information, the treatment intensity and the cognitive impairment level are used as the training data ontology, and the treatment effect information is used as the training data label. The first training data set and the second training data set are constructed based on the first treatment big data and the second treatment big data respectively.

[0024] A pre-constructed first depth prediction model is trained using the first training data set, a pre-constructed second depth prediction model is trained using the second training data set, and a pre-constructed third depth prediction model is trained using the first training data set and the second training data set.

[0025] The target point information and the target cognitive impairment level of the target patient are respectively input into the trained first deep prediction model, the second deep prediction model, and the third deep prediction model to obtain the predicted first treatment intensity, second treatment intensity, and third treatment intensity, respectively, calculate the difference between the second treatment intensity and the third treatment intensity, and determine the matching first attenuation coefficient based on the difference.

[0026] A fourth treatment intensity is calculated according to the first attenuation coefficient and the first treatment intensity, and the fourth treatment intensity is the final treatment intensity.

[0027] In some embodiments, determining the matched first weakening coefficient according to the difference includes: performing a matching calculation according to the difference and preset comparison relationship data to obtain the matched first weakening coefficient.

[0028] In some embodiments, the fourth treatment intensity is calculated based on the first attenuation coefficient and the first treatment intensity, and the fourth treatment intensity is the final treatment intensity, including: obtaining historical treatment data of the target patient, calculating the number of times transcranial focused ultrasound stimulation is used for treatment based on the historical treatment data, and determining the second attenuation coefficient based on the number of times; and using the first attenuation coefficient, the second attenuation coefficient, and the first treatment intensity to calculate the fourth treatment intensity, and the fourth treatment intensity is the final treatment intensity.

[0029] The present invention also discloses a working method of a transcranial focused ultrasound stimulation system for patients with cognitive impairment, the method comprising the following steps: a target position determination module determines information of a target corresponding to a target patient, and transmits it to a main control module through a communication module; a treatment intensity determination module determines treatment intensity, and transmits it to the main control module through a communication module; the main control module generates a treatment start instruction according to the target information and treatment intensity, and a signal source module, a driving module, an impedance matching module, an ultrasonic transducer module, and an ultrasonic coupling module are enabled in sequence according to the treatment start instruction to achieve transcranial focused ultrasound stimulation of the above-mentioned target of the target patient.

[0030] The present invention also discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in any of the preceding items.

[0031] The present invention also discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement any of the above methods.

[0032] The present invention also discloses a computer program product. When the computer program product is run on a terminal, the terminal implements any of the above methods when executing the computer program product.

[0033] The beneficial effect of the present invention is that the present invention can determine personalized targets according to the actual condition of the target patient, and determine the appropriate treatment intensity, thereby facilitating obtaining the best treatment effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0035] Figure 1 It is a structural schematic diagram of a transcranial focused ultrasound stimulation system for patients with cognitive impairment disclosed in an embodiment of the present invention.

[0036] Figure 2 It is the shape of one of the original signals disclosed in the embodiment of the present invention.

[0037] Figure 3 It is a flow chart of a transcranial focused ultrasound stimulation method for patients with cognitive impairment disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0039] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0040] like Figure 1 As shown, an embodiment of the present invention discloses a transcranial focused ultrasound stimulation system for patients with cognitive impairment, wherein the system includes a main control module, a communication module, a display module, a signal source module, a driving module, an impedance matching module, an ultrasonic transducer module, and an ultrasonic coupling module; wherein the main control module is the core control module of the entire system, and is used to provide the required timer resources for the signal source module, provide the required display data for the display module, provide the required communication data for the communication module, and receive data transmitted by the communication module.

[0041] Among them, the MCU of the main control module can adopt the STM32F1 series.

[0042] The signal source module is responsible for generating an online adjustable original signal, which is a pair of PWM signals with complementary polarities and dead time output by the advanced timer of the main control module.

[0043] The above original signal is a pair of PWM signals with complementary polarity and dead time output by the MCU advanced timer. The signal is actually a series of pulse groups. A single pulse group consists of several pulses, and a single pulse consists of several fundamental waves. The specific shape of one of the complementary signals is as follows: Figure 2 As shown, the other signal has the opposite polarity.

[0044] The signal has the following parameters: fundamental frequency: the basic square wave frequency that constitutes the signal; pulse duration (TBD): the duration of a single pulse; pulse repetition frequency (PRF): the frequency of pulse repetition; pulse group duration (SD): the duration of a single pulse group; stimulus interval (ISI): the interval between pulse groups. All the above parameters of the signal can be adjusted online by controlling the advanced timer of the MCU through keystrokes.

[0045] The driving module is used to amplify the original signal to obtain a driving signal capable of driving the ultrasonic transducer module.

[0046] The driving module, for example, is a full-bridge driving circuit with the IR2110 chip as the core and connected to a transformer, which is used to amplify the original signal to meet the requirements of driving the ultrasonic transducer. The input of the driving module is the original signal output by the signal source module, and the output is the driving signal formed after amplification.

[0047] The impedance matching module is composed of an LC matching network, and its input is the driving signal output by the driving module, and its output is the driving signal after impedance matching.

[0048] The function of the impedance matching module is to reduce reflections, improve efficiency, and ensure that the output impedance of the signal source matches the input impedance of the load. According to the maximum power transfer theorem, maximum power transfer can be achieved when the source impedance and the load impedance are equal.

[0049] The ultrasonic transducer module: its input is the driving signal after impedance matching, which is used to convert the driving signal of the electrical signal into an acoustic signal, that is, to emit focused ultrasonic waves that meet the requirements; wherein the target position of the focused ultrasonic wave stimulation is confirmed based on resting state functional magnetic resonance imaging; the ultrasonic coupling module is responsible for effectively transmitting ultrasonic waves between the ultrasonic transducer module and the object under test, helping to eliminate the acoustic impedance differences in the air.

[0050] The main function of the ultrasonic coupling module is to achieve low-loss transmission of ultrasonic signals. It is usually composed of water or special ultrasonic coupling glue. By selecting a suitable coupling medium, the ultrasonic coupling module can significantly improve the transmission efficiency of the signal and reduce the loss of the signal during the transmission process.

[0051] The display module is used to display the parameter information and other stimulation information of the original signal in real time.

[0052] The display module can use a TFT-LCD screen, which is connected to the main control module through an 80 serial port, and can display the parameter information of the original signal and other stimulus information in real time. The TFT-LCD screen has the characteristics of high resolution, bright colors, fast response, and energy saving, and is widely used in the field of medical display.

[0053] The communication module is used to record and store stimulation logs and communicate with the host computer.

[0054] The communication storage flash uses W25Q64, which communicates with the main control chip through the SPI protocol to record the time and stimulation parameters of each stimulation. Through the USB to serial port, the host computer can communicate with the stimulation system and read the stimulation log information.

[0055] In some embodiments, the system also includes a target position determination module, which is connected to the communication module; the target position determination module is used to perform the following steps: S1, using resting-state functional magnetic resonance imaging technology to measure the blood oxygen level-dependent (BOLD) signal changes of the target patient's brain in a resting state, and dividing the brain into several brain regions: frontal lobe, parietal lobe, temporal lobe and occipital lobe.

[0056] These brain regions have different functional divisions in the brain. For example, the frontal lobe is responsible for higher cognitive functions, the parietal lobe is responsible for processing sensory information, the temporal lobe is related to hearing and language, and the occipital lobe is related to visual processing.

[0057] S2. For each of the brain regions, calculate the functional connection strength between it and other brain regions, and average the functional connection strengths between each of the brain regions and other brain regions, so as to determine the brain region with the weakest average connection strength, and use it as the target brain region; wherein the functional connection strength is achieved by calculating the correlation between the blood oxygen level-dependent signals between the two brain regions.

[0058] The higher the correlation between two brain regions, the stronger the functional connection between the two brain regions. The target brain region may be the area that is most affected or functionally abnormal in the disease state.

[0059] S3, dividing the target brain region into smaller sub-brain regions, repeating the above step S2 for each sub-brain region, and taking the sub-brain region with the weakest average functional connectivity as the target of neural regulation.

[0060] The above-mentioned smaller sub-brain regions are, for example, gyri, sulci, etc. The above-mentioned targets may be the most critical abnormal areas in the disease state, and neuromodulation thereof may help improve the patient's symptoms.

[0061] S4. Transmitting the target point to the main control module through the communication module, so that the main control module displays the information of the target point on the display module.

[0062] In some embodiments, any one of Pearson correlation coefficient, local consistency, seed-based functional connectivity, and functional network connectivity analysis methods is used to calculate the correlation of blood oxygen level dependent signals between two brain regions.

[0063] In resting-state functional magnetic resonance imaging (rs-fMRI), the functional connectivity strength (or connectivity value) usually refers to the correlation measure of the time series data of blood oxygen level dependent (BOLD) signals between different brain regions. This correlation can reflect the relationship between different brain regions or tissues and is a key indicator for analyzing brain functional connectivity.

[0064] Specifically, the strength of functional connectivity can be calculated in the following ways: Pearson correlation coefficient: This is one of the most commonly used methods to measure the degree of linear correlation between two time series. The value range of the Pearson correlation coefficient is -1 to 1, where 0 indicates no correlation, positive values ​​indicate positive correlation, and negative values ​​indicate negative correlation. In rs-fMRI, by calculating the Pearson correlation coefficient of the time series of the BOLD signal between two regions of interest (ROI), the strength of the functional connectivity between the two regions can be obtained.

[0065] Local coherence (ReHo): This is a measure of local connectivity within a specific region, calculated by analyzing whether the activity of a specific voxel is correlated with that of its nearby voxels (usually using Kendall’s coefficient of coherence test).

[0066] Seed-based FC: In this method, one or more seed points (ROIs) are first selected, and then the correlation between the average time series of all voxels within these seed points and the time series of other voxels in the whole brain is calculated to obtain a whole-brain functional connectivity map (FC map).

[0067] Functional network connectivity analysis (FNC): This method combines model-driven and data-driven approaches. It first obtains subject-specific functional networks and their associated fluctuations through group independent component analysis (ICA), and then calculates the functional connectivity between these networks to produce a functional connectivity matrix containing the connectivity strength between all networks.

[0068] In some embodiments, the system also includes a treatment intensity determination module, which is connected to the communication module; the treatment intensity determination module is used to perform the following steps: collecting first treatment big data of similar patients with the same level of cognitive impairment as the target patient, and second treatment big data of similar patients with a higher level of cognitive impairment than the target patient; wherein the first treatment big data and the second treatment big data contain a number of transcranial focused ultrasound stimulation data, and each of the transcranial focused ultrasound stimulation data contains target information, treatment intensity, cognitive impairment level, and treatment effect information.

[0069] The target information, the treatment intensity and the cognitive impairment level are used as the training data ontology, and the treatment effect information is used as the training data label. The first training data set and the second training data set are constructed based on the first treatment big data and the second treatment big data respectively.

[0070] A pre-constructed first depth prediction model is trained using the first training data set, a pre-constructed second depth prediction model is trained using the second training data set, and a pre-constructed third depth prediction model is trained using the first training data set and the second training data set.

[0071] The target point information and the target cognitive impairment level of the target patient are respectively input into the trained first deep prediction model, the second deep prediction model, and the third deep prediction model to obtain the predicted first treatment intensity, second treatment intensity, and third treatment intensity, respectively, calculate the difference between the second treatment intensity and the third treatment intensity, and determine the matching first attenuation coefficient based on the difference.

[0072] A fourth treatment intensity is calculated according to the first attenuation coefficient and the first treatment intensity, and the fourth treatment intensity is the final treatment intensity.

[0073] In this embodiment, in transcranial focused ultrasound stimulation, treatment intensity is a key parameter related to treatment safety and effectiveness, which refers to the energy level of ultrasound. Specific parameters include spatial peak time average intensity (ISPTA), spatial average time average intensity (ISATA) and spatial peak pulse average intensity (ISPPA), which are specifically introduced as follows: Spatial peak time average intensity (ISPTA): This is the time average intensity of ultrasound at the spatial peak position, which is used to describe the average energy level of ultrasound in the action area.

[0074] Spatially Averaged Temporal Intensity (ISATA): This is the time-averaged intensity over the entire area of ​​action and is used to describe the energy distribution of ultrasound over the entire treatment area.

[0075] Spatial Peak Pulse Average Intensity (ISPPA): This is the average pulse intensity at the spatial maximum position of the ultrasound pulse and is related to the short-term mechanical bioeffect.

[0076] The present invention adopts a combination of big data and deep prediction algorithms to determine the targeted treatment intensity for the target patient, as follows: First, collect the first treatment big data of similar patients with the same level of cognitive impairment as the target patient, and the second treatment big data of similar patients with a higher level of cognitive impairment than the target patient. Among them, cognitive impairment can be divided into different levels according to its severity. For example: Subjective cognitive decline (SCD): This is considered to be an earlier stage than mild cognitive impairment (MCI). SCD refers to a personal complaint or complaint of memory or other cognitive function decline, but the objective cognitive test is still within the normal range. Mild cognitive impairment (MCI): This is a transitional state between normal and dementia in cognitive function. MCI involves impairment of one or more functions in multiple cognitive domains such as memory, attention, language, execution, reasoning, calculation and orientation, which can affect the patient's social function and quality of life to varying degrees. Dementia: This is a more serious stage of cognitive impairment, involving severe damage to cognitive function and seriously affecting daily living ability. In addition, cognitive impairment can also be classified according to etiology and pathological mechanisms, such as Alzheimer's disease (AD), vascular cognitive impairment (VCI), dementia with Lewy bodies (DLB), frontotemporal lobar degeneration (FTD), etc. In vascular cognitive impairment, according to the severity of cognitive impairment, it can be further divided into mild VCI and severe VCI (including post-stroke dementia PSD, subcortical ischemic vascular dementia SIVaD, multi-infarct dementia MID and mixed dementia MixD). The cognitive impairment level of the target patient is predetermined. On this basis, similar patients with the same cognitive impairment level as the target patient and similar patients with higher cognitive impairment level (i.e. more severe) than the target patient can be screened out according to any of the above-mentioned level classification methods. The treatment big data of these similar patients are collected through multiple data source channels. The collected treatment big data contains several transcranial focused ultrasound stimulation data, and each transcranial focused ultrasound stimulation data contains target information, treatment intensity, cognitive impairment level, and treatment effect information. It should be noted that “similar patients” refer to patients with the same or different degrees of the same type of cognitive impairment. For example, both are patients with vascular cognitive impairment, the former has mild VCI and the latter has severe VCI.

[0077] Then, the target information, treatment intensity and cognitive impairment level in each piece of transcranial focused ultrasound stimulation data are used as the training data ontology, and the treatment effect information is used as the training data label, so as to construct the first training data set and the second training data set respectively. The pre-constructed first depth prediction model is trained using the first training data set, the pre-constructed second depth prediction model is trained using the second training data set, and the pre-constructed third depth prediction model is trained using the first training data set and the second training data set. The first depth prediction model, the second depth prediction model and the third depth prediction model are preferably constructed based on the Transformer algorithm.

[0078] The first deep prediction model, the second deep prediction model, and the third deep prediction model that have been fully trained can be used to infer the treatment intensity that can achieve the best treatment effect based on the target information of the target patient and the target cognitive impairment level (obtained in advance). On this basis, the present invention further calculates the difference (absolute value) between the third treatment intensity and the second treatment intensity, and then determines the matching first weakening coefficient based on the difference. The first weakening coefficient is used to moderately reduce the first treatment intensity obtained by the above prediction, that is, a fourth treatment intensity with higher safety is obtained, and the fourth treatment intensity is used as the initial treatment intensity for the target patient. If the subsequent treatment effect is good, the treatment intensity can be gradually reduced.

[0079] It should be noted that the second deep prediction model and the third deep prediction model in the present invention are trained with different training data respectively, and the difference between the treatment intensities obtained by analyzing the same input data, i.e., the target information of the target patient and the target cognitive impairment level, reflects the "divergence" of the treatment intensity of the same patient by different models. Therefore, in order to ensure the safety of treatment, the present invention is set to set the first weakening coefficient smaller (for example, 0.8) correspondingly when the "divergence" or the difference is larger, that is, a smaller first weakening coefficient is used to reduce the predicted first treatment intensity to a greater extent; when the "divergence" or the difference is smaller, a larger first weakening coefficient is set correspondingly (for example, 0.9), that is, a larger first weakening coefficient is used to reduce the predicted first treatment intensity to a smaller extent.

[0080] In some embodiments, determining the matched first weakening coefficient according to the difference includes: performing a matching calculation according to the difference and preset comparison relationship data to obtain the matched first weakening coefficient.

[0081] In this embodiment, the comparison relationship data between the difference and the first weakening coefficient can be established by actual measurement or simulation model inference. After obtaining the above difference, the corresponding first weakening coefficient can be quickly obtained by matching analysis with the preset comparison relationship data.

[0082] In some embodiments, the fourth treatment intensity is calculated based on the first attenuation coefficient and the first treatment intensity, and the fourth treatment intensity is the final treatment intensity, including: obtaining historical treatment data of the target patient, calculating the number of times transcranial focused ultrasound stimulation is used for treatment based on the historical treatment data, and determining the second attenuation coefficient based on the number of times; and using the first attenuation coefficient, the second attenuation coefficient, and the first treatment intensity to calculate the fourth treatment intensity, and the fourth treatment intensity is the final treatment intensity.

[0083] In this embodiment, the target patient may have received transcranial focused ultrasound stimulation treatment in other medical institutions before, so the initial treatment intensity can be appropriately weakened again based on this. Specifically, the historical treatment data of the target patient is first obtained, and the treatment record using transcranial focused ultrasound stimulation is extracted from the historical treatment data, and the number of records is counted, and the second weakening coefficient is determined based on the number of records. Then, the first treatment intensity is weakened simultaneously using the first weakening coefficient and the second weakening coefficient to obtain the final fourth treatment intensity.

[0084] Among them, the first weakening coefficient and the second weakening coefficient are both values ​​less than or equal to 1, and the second weakening coefficient is negatively correlated with the above number, that is, the larger the above number is, the smaller the second weakening coefficient is (for example, 0.8), and the smaller the above number is, the larger the second weakening coefficient is (for example, 0.9). However, the present invention does not limit the correspondence between the second weakening coefficient and the above number, which can be a conversion formula or, for example, the aforementioned preset comparison relationship data.

[0085] In addition, some usage details of the above system of the present invention are specifically introduced as follows: EEG data collection before stimulation: collect resting EEG, including five minutes of eyes-open state and five minutes of eyes-closed state.

[0086] Stimulation plan: Continuous stimulation for 5 days followed by a 2-day rest, with a total of 1 week as one cycle. Three consecutive cycles of stimulation is three weeks, with 15 minutes of stimulation per day.

[0087] EEG data collection after stimulation: After the complete stimulation protocol, resting-state EEG was collected, including five minutes of eyes-open state and five minutes of eyes-closed state.

[0088] EEG data preprocessing: For the EEG collected before and after stimulation, filtering, downsampling, bad segment deletion, interpolation of bad leads, ICA component removal, re-reference, and data segmentation are performed in sequence for subsequent processing.

[0089] EEG data processing: For the pre-processed EEG data, processing and analysis are performed from three perspectives: EEG complexity, EEG power spectrum, and brain network functional connectivity.

[0090] (1) EEG complexity: The EEG complexity of patients with cognitive impairment is generally lower than that of healthy people. Calculate the multi-scale entropy of EEG data before and after stimulation to analyze whether the EEG complexity after stimulation is higher than that before stimulation. If it is higher, the stimulation is effective.

[0091] (2) EEG power spectrum: The EEG power spectrum of patients with cognitive impairment is different from that of healthy people. Specifically, compared with healthy people, the power of the α and β frequency bands of patients with cognitive impairment is lower, and the power of the δ and θ frequency bands is higher. The power of each frequency band of the EEG data before and after stimulation was calculated to analyze whether there was any improvement in the power spectrum.

[0092] (3) Brain network functional connectivity: The brain network functional connectivity of patients with cognitive impairment is weaker than that of healthy people. The functional connectivity indicators of EEG data before and after stimulation, such as COH and PLI, were calculated to analyze whether the brain network functional connectivity was enhanced after stimulation.

[0093] like Figure 3 As shown, an embodiment of the present invention also discloses a working method of a transcranial focused ultrasound stimulation system for patients with cognitive impairment, the method comprising the following steps: a target position determination module determines information of a target corresponding to a target patient, and transmits it to a main control module through a communication module.

[0094] The treatment intensity determination module determines the treatment intensity and transmits it to the main control module through the communication module.

[0095] The main control module generates a treatment start instruction based on the target information and treatment intensity. The signal source module, drive module, impedance matching module, ultrasonic transducer module, and ultrasonic coupling module are enabled in sequence according to the treatment start instruction to achieve transcranial focused ultrasound stimulation of the above-mentioned targets of the target patient.

[0096] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, characterized in that: the processor executes the computer program to implement the method described in the above embodiment.

[0097] An embodiment of the present invention further discloses a computer storage medium, wherein the computer storage medium stores a computer program, and is characterized in that: the computer program is executed by a processor to implement the method described in the above embodiment.

[0098] The embodiment of the present invention further discloses a computer program product. When the computer program product is run on a terminal, the terminal implements the method described in the above embodiment.

[0099] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0100] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0101] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A transcranial focused ultrasound stimulation system for patients with cognitive impairment, characterized in that: The system includes a main control module, a communication module, a display module, a signal source module, a driving module, an impedance matching module, an ultrasonic transducer module, and an ultrasonic coupling module; wherein the main control module is the core control module of the entire system, and is used to provide the required timer resources for the signal source module, provide the required display data for the display module, provide the required communication data for the communication module, and receive the data transmitted by the communication module; the signal source module is responsible for generating an online adjustable original signal, which is a pair of PWM signals with complementary polarity and dead time output by the advanced timer of the main control module; the driving module is used to amplify the original signal to obtain a driving signal capable of driving the ultrasonic transducer module; The impedance matching module is composed of an LC matching network, and its input is the driving signal output by the driving module, and its output is the driving signal after impedance matching; the ultrasonic transducer module, whose input is the driving signal after impedance matching, is used to convert the driving signal of the electrical signal into an acoustic signal, that is, to emit focused ultrasonic waves that meet the requirements; wherein the target position of the focused ultrasonic wave stimulation is confirmed based on the resting state functional magnetic resonance imaging; the ultrasonic coupling module is responsible for effectively transmitting ultrasonic waves between the ultrasonic transducer module and the object under test, and helping to eliminate the acoustic impedance difference in the air; the display module is used to display the parameter information and other stimulation information of the original signal in real time; the communication module is used to record and store the stimulation log and communicate with the host computer.

2. A transcranial focused ultrasound stimulation system for patients with cognitive impairment according to claim 1, characterized in that: The system also includes a target location determination module, which is connected to the communication module; the target location determination module is used to perform the following steps: S1, using resting state functional magnetic resonance imaging technology to measure the changes in the blood oxygen level-dependent signals of the target patient's brain in a resting state, and dividing the brain into several brain regions, namely, the frontal lobe, parietal lobe, temporal lobe and occipital lobe; S2, for each of the brain regions, calculating the functional connection strength between it and other brain regions, averaging the functional connection strengths of each brain region with other brain regions, thereby determining the brain region with the weakest average connection strength, and taking it as the target brain region; wherein the functional connection strength is achieved by calculating the correlation of the blood oxygen level-dependent signals between two brain regions; S3, dividing the target brain region into smaller sub-brain regions, repeating the above step S2 for each of the sub-brain regions, and taking the sub-brain region with the weakest average functional connection as the target of neural regulation; S4, transmitting the target to the main control module through the communication module, so that the main control module displays the information of the target on the display module.

3. The transcranial focused ultrasound stimulation system for patients with cognitive impairment according to claim 1, characterized in that: The correlation of blood oxygen level-dependent signals between two brain regions was calculated using any of the Pearson correlation coefficient, local consistency, seed-based functional connectivity, and functional network connectivity analysis methods.

4. The transcranial focused ultrasound stimulation system for patients with cognitive impairment according to claim 1, characterized in that: The system also includes a treatment intensity determination module, which is connected to the communication module; the treatment intensity determination module is used to perform the following steps: collecting first treatment big data of similar patients with the same cognitive impairment level as the target patient, and second treatment big data of similar patients with a higher cognitive impairment level than the target patient; wherein the first treatment big data and the second treatment big data contain a number of transcranial focused ultrasound stimulation data, and each of the transcranial focused ultrasound stimulation data contains target information, treatment intensity, cognitive impairment level, and treatment effect information; using the target information, the treatment intensity, and the cognitive impairment level as training data ontology, and using the treatment effect information as training data label, and constructing a first training data set and a second training data set based on the first treatment big data and the second treatment big data, respectively. set; use the first training data set to train a pre-constructed first deep prediction model, use the second training data set to train a pre-constructed second deep prediction model, and use the first training data set and the second training data set to train a pre-constructed third deep prediction model; input the target information and the target cognitive impairment level of the target patient into the trained first deep prediction model, the second deep prediction model, and the third deep prediction model, respectively, to obtain the predicted first treatment intensity, second treatment intensity, and third treatment intensity, calculate the difference between the second treatment intensity and the third treatment intensity, and determine the matching first attenuation coefficient according to the difference; calculate the fourth treatment intensity according to the first attenuation coefficient and the first treatment intensity, and the fourth treatment intensity is the final treatment intensity.

5. A transcranial focused ultrasound stimulation system for patients with cognitive impairment according to claim 4, characterized in that: Determining the first matching weakening coefficient according to the difference includes: performing a matching calculation according to the difference and preset comparison relationship data to obtain the first matching weakening coefficient.

6. A transcranial focused ultrasound stimulation system for patients with cognitive impairment according to claim 5, characterized in that: The fourth treatment intensity is calculated based on the first attenuation coefficient and the first treatment intensity, and the fourth treatment intensity is the final treatment intensity, including: acquiring historical treatment data of the target patient, calculating the number of times transcranial focused ultrasound stimulation is used for treatment based on the historical treatment data, and determining the second attenuation coefficient based on the number of times; and using the first attenuation coefficient, the second attenuation coefficient, and the first treatment intensity to calculate the fourth treatment intensity, and the fourth treatment intensity is the final treatment intensity.

7. A method for operating a transcranial focused ultrasound stimulation system for patients with cognitive impairment according to any one of claims 1 to 6, characterized in that: The method comprises the following steps: a target position determination module determines information of a target corresponding to a target patient, and transmits the information to a main control module through a communication module; a treatment intensity determination module determines treatment intensity, and transmits the information to a main control module through a communication module; the main control module generates a treatment start instruction according to the target information and treatment intensity, and a signal source module, a driving module, an impedance matching module, an ultrasonic transducer module, and an ultrasonic coupling module are sequentially enabled according to the treatment start instruction to achieve transcranial focused ultrasound stimulation of the above-mentioned target of the target patient.

8. An electronic device, comprising: At least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method according to claim 7.

9. A computer storage medium storing a computer program, characterized in that: The computer program is executed by a processor to implement the method according to claim 7.

10. A computer program product comprising a computer program stored on a non-transitory computer readable medium, characterized in that: When the computer program is executed by a processor, the method according to claim 7 is implemented.

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