A remote intelligently controlled transcranial magnetic stimulation insomnia treatment system and method

Abstract

The present invention discloses a remote intelligently controlled transcranial magnetic stimulation insomnia treatment system and a method thereof. The method is based on a remote intelligently controlled transcranial magnetic stimulation insomnia treatment system, comprising a device control end and a cloud server. The method comprises the following steps: an electroencephalogram (EEG) acquisition module of the device control end of the system regularly acquires EEG data of a sleeper, a remote transmission module of the system sends the acquired data to the cloud server, an EEG processing module of the cloud server analyzes and stores sleep state and sleep quality data, the cloud server performs AI intelligent analysis based on the current sleep state and sleep quality data as well as historical sleep data to derive a sleep intervention plan, and sends the intervention plan to the device control end at the same time. The device control end modifies the working parameters of the device according to the parameters in the intervention plan to execute transcranial magnetic stimulation, improves the sleep quality of the sleeper through transcranial magnetic stimulation, and implements a personalized sleep improvement plan through this closed-loop system.

Description

Technical Field

[0001] The invention relates to the field of transcranial magnetic stimulation, and in particular to a remote intelligently controlled transcranial magnetic stimulation insomnia treatment system. Background Art

[0002] Insomnia is a common sleep disorder that seriously affects the quality of life and work efficiency of sleepers. Traditional treatments for insomnia include medication and cognitive behavioral therapy, but these methods may have problems such as drug dependence and unstable treatment effects, and cannot meet the needs of all patients.

[0003] In recent years, transcranial magnetic stimulation has become an emerging method for treating insomnia. Transcranial magnetic stimulation is a non-invasive neuromodulation technology that can change the excitability of neurons by transmitting magnetic field stimulation to specific areas of the brain, thereby regulating neural function and affecting sleep status. Compared with traditional treatment methods, transcranial magnetic stimulation has the advantages of no drug intervention, high safety, and non-traumatic, so it has attracted much attention.

[0004] However, the traditional transcranial magnetic stimulation treatment system has some limitations. First, patients usually need to go to medical institutions for treatment, which is not convenient for long-term treatment and monitoring. Second, since the setting and adjustment of treatment parameters are usually based on the doctor's experience, the treatment effect is difficult to accurately grasp and it is impossible to achieve a personalized treatment plan. In addition, the patient's sleep state and treatment effect change over time, and the treatment plan needs to be monitored and adjusted in real time to ensure the continuity and optimization of the treatment effect.

[0005] In order to solve the above problems, the present invention proposes a remote intelligently controlled transcranial magnetic stimulation insomnia treatment system and method. The system controls transcranial magnetic stimulation through EEG data acquisition and AI intelligent algorithm. Through this closed-loop system, the sleep quality of insomnia patients can be effectively improved, and personalized treatment plans can be provided. It makes full use of modern information technology and neuromodulation technology, and provides a new, more convenient, efficient and personalized solution for insomnia treatment. Summary of the invention

[0006] The purpose of the present invention is to provide a remote intelligently controlled transcranial magnetic stimulation insomnia treatment system and method.

[0007] A remote intelligently controlled transcranial magnetic stimulation insomnia treatment system comprises two main components: a device control terminal and a cloud server.

[0008] The device control terminal includes an electroencephalogram acquisition module and a transcranial magnetic stimulation module.

[0009] The EEG acquisition module includes a single-channel EEG sensor module and acquisition electrodes, an MCU control module, and a WIFI transmission module.

[0010] Furthermore, the electrode interface of the single-channel EEG sensor module is connected to the collection electrode, the communication interface of the single-channel EEG sensor module is connected to the first communication interface of the MCU control module, and the WIFI transmission module is connected to the second communication interface of the MCU control module.

[0011] Furthermore, the MCU control chip forwards the EEG data obtained from the first communication interface to the WIFI module of the second communication interface, and the WIFI module is connected to the cloud server and sends the data to the cloud server.

[0012] The transcranial magnetic stimulation module includes a stimulation coil, a charging and discharging capacitor, a pulse power supply circuit module, and an MCU drive control circuit module.

[0013] Furthermore, the stimulation coil is connected to the charging and discharging capacitor, the pulse power supply circuit module is connected to the charging and discharging capacitor, and the MCU drive control circuit module is connected to the stimulation coil, the charging and discharging capacitor, and the pulse power supply circuit module.

[0014] Furthermore, the MCU driving control circuit module controls the pulse power circuit module to charge the charging and discharging capacitor in one cycle, and then controls the charging and discharging capacitor to discharge the stimulation coil in the same cycle. The pulse magnetic field of transcranial magnetic stimulation is realized through multiple cycles of charging and discharging.

[0015] The cloud server includes a sleep quality analysis unit, a database unit for data storage, and an AI unit for generating a sleep intervention plan based on intelligent analysis of the sleep database.

[0016] The sleep quality analysis unit extracts the uploaded raw data of the brain wave sensor, identifies the sleep stage state by analyzing the waveform characteristics, and evaluates the sleep quality.

[0017] The database unit stores historical data including sleep stage data and sleep quality.

[0018] The AI ​​unit uses deep learning algorithms and data mining technology to combine the sleep status and sleep quality data obtained by the EEG processing module with the historical sleep data stored in the database to perform large-scale data analysis and pattern recognition, establish a personalized sleep treatment model, and generate a sleep intervention plan.

[0019] Furthermore, the sleep intervention program is sent to the device control terminal via a network, and the stimulation execution parameters of the device control terminal are modified.

[0020] The insomnia treatment method of the present invention comprises the following steps: The EEG acquisition module of the device control end collects the EEG data of the sleeper at regular intervals. The device control end sends the collected EEG data to the cloud server through the remote transmission module. On the cloud server, the EEG processing module processes the EEG data and analyzes the sleep state to obtain the sleep state and sleep quality data, and stores them as a personal database. The AI ​​intelligent analysis module of the cloud server combines the current sleep state and sleep quality data with the historical sleep data to perform intelligent analysis and obtain a personalized sleep intervention plan; The cloud server sends the generated sleep intervention plan to the device control end. The transcranial magnetic stimulation device of the device control end performs corresponding transcranial magnetic stimulation operations according to the parameters in the intervention plan to improve the sleep quality of the sleeper. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A structural block diagram of a device control terminal system provided in an embodiment of the present invention.

[0022] Figure 2 A schematic diagram of a workflow provided by an embodiment of the present invention; Implementation

[0023] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several variations and improvements may be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0024] like Figure 1 As shown in the structural framework diagram, a remote intelligently controlled transcranial magnetic stimulation insomnia treatment system includes two modules: an electroencephalogram acquisition module and a transcranial magnetic stimulation module. The functions of the two modules are integrated together and share a common MCU control module A. The MCU control module A is connected to a single-channel electroencephalogram sensor B through a UART communication interface, and the single-channel electroencephalogram sensor B is connected to an acquisition electrode C through a wire. The stimulation coil G is connected to the charge-discharge capacitor F through a wire, the pulse power supply circuit module E is connected to the charge-discharge capacitor F through a wire, and the drive control circuit module H is connected to the stimulation coil G, the charge-discharge capacitor F, and the pulse power supply circuit module E. The wifi transmission module D is connected to the MCU control module A through a UART communication interface.

[0025] Among them, the single-channel EEG sensor B has its own EEG signal amplification and filtering circuit. In some embodiments, the collected signal can be the original waveform signal of the EEG or the αβ EEG band signal data.

[0026] The collection electrode C is a conductive material connected to the single-channel EEG sensor module B. It is attached to the scalp surface to achieve the conduction of EEG signals with the sensor module. A dry contact electrode is used to ensure the accurate collection of EEG signals.

[0027] The pulse power supply circuit module E is a high-power switching power supply and a boost circuit, which is connected to the charging and discharging capacitor F to form a charging circuit. The driving control circuit H controls the on and off of the charging circuit to charge the capacitor.

[0028] The charging and discharging capacitor is a thin film capacitor with a capacity between 100uf and 400uF, which is connected to the stimulation coil G to form a discharge circuit. The drive control circuit H controls the on and off of the discharge circuit to achieve rapid discharge of the capacitor. The discharged electrical energy generates a pulsed strong magnetic field through the stimulation coil. The magnetic field can penetrate the skull and enter specific areas of the brain, thereby achieving the insomnia treatment effect of transcranial magnetic stimulation.

[0029] A remote intelligent controlled transcranial magnetic stimulation insomnia treatment system and method provided by an embodiment of the present invention will be described in detail below in conjunction with the accompanying drawings. Figure 2 , Figure 2 It is a schematic diagram of the working process of a remote intelligently controlled transcranial magnetic stimulation insomnia treatment system provided by an embodiment of the present invention.

[0030] Step s1: The device control terminal collects the original signal data of the brain wave, collects the data regularly after the device is turned on, and stores the records in the local memory.

[0031] Step s2: The device control terminal sends data to the server through the transmission module. The transmission is sent regularly after the device is turned on. In some implementation cases, the transmission is sent when a certain amount of data is collected and recorded. The data is generally sent through the TCP / UDP protocol.

[0032] Step s3: The cloud server receives the connection from the device control terminal and receives the data into local storage.

[0033] Step s4: The cloud server obtains sleep quality results from the EEG data through data preprocessing, feature extraction, sleep stage identification, sleep quality assessment and other algorithmic means, and stores them in the database.

[0034] Step s5: The cloud server uses deep learning algorithms and data mining technology, combined with the sleep status and sleep quality data obtained by the EEG processing module and the historical sleep data stored in the database, to implement personalized sleep treatment models through AI intelligent analysis and generate sleep intervention plans.

[0035] Step s6: The cloud server transmits the generated sleep intervention plan back to the device control terminal, where the plan includes the configuration parameters of the transcranial magnetic stimulation required for the intervention treatment of insomnia.

[0036] Step s7: The device control terminal receives the sleep intervention plan sent by the cloud server.

[0037] Step s8: The device control terminal analyzes the specific treatment parameters and instructions obtained from the sleep intervention plan, and the device control terminal will set the relevant parameters of the transcranial magnetic stimulation device accordingly. These parameters may include the frequency, pulse width, pulse intensity, etc. of the transcranial magnetic stimulation.

[0038] Step s9: After setting the transcranial magnetic stimulation parameters, the device control terminal transmits these parameters to the transcranial magnetic stimulation module. The transcranial magnetic stimulation module performs corresponding stimulation operations according to the received parameters to generate a pulsed magnetic field for transcranial magnetic stimulation.

[0039] It should be noted that the above described embodiments are merely illustrative, wherein the modules described as separate components at the device control end may or may not be physically separated, and the cloud server may be created by an independent physical computer or may be virtualized by a cluster server. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

Claims

1. A remote intelligently controlled transcranial magnetic stimulation insomnia treatment system, comprising: The device control end has an EEG acquisition module for regularly collecting EEG data of the sleeper; The cloud server has an EEG processing module for analyzing and storing sleep status and sleep quality data.

2. The system according to claim 1, wherein the cloud server further comprises an AI intelligent analysis module for deriving a sleep intervention plan based on current sleep status and sleep quality data as well as historical sleep data.

3. The system according to claim 1, wherein the device control end further comprises a remote receiving module for receiving the sleep intervention plan sent by the cloud server.

4. The system according to claim 3, wherein the transcranial magnetic stimulation device at the device control end can modify the working parameters according to the parameters in the sleep intervention program to perform transcranial magnetic stimulation.

5. The system according to claim 1, wherein the transcranial magnetic stimulation device is used to improve the sleep quality of the sleeper through transcranial magnetic stimulation.

6. The system according to claim 1, wherein the EEG acquisition module of the device control terminal regularly collects the EEG data of the sleeper to implement a personalized sleep improvement plan.

7. The system according to claim 1, wherein the EEG processing module of the cloud server is capable of analyzing and storing sleep status and sleep quality data for long-term sleep data tracking and evaluation.

8. The method according to claim 8, wherein the sleep intervention plan is formulated based on the individual's sleep status and historical data to achieve an individualized treatment plan.

9. The method according to claim 8, wherein the transcranial magnetic stimulation insomnia treatment method can adjust the treatment parameters in real time to adapt to different stages of sleep states and treatment needs.

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