Depression detection device based on EEG signal

Abstract

The utility model discloses a depression detection device based on EEG (electroencephalogram) signals, which comprises an acquisition front end and right leg driving circuit for acquiring the EEG signals at the front end of a testee; the pre-amplification circuit is used for amplifying the acquired weak EEG signals; the high-pass amplification filter circuit is used for performing high-pass filtering on the amplified EEG signal; the low-pass amplification filter circuit is used for carrying out low-pass filtering on the amplified EEG signal; the digital-to-analog conversion module is used for carrying out analog-to-digital conversion and sampling on the amplified and filtered EEG signals; the micro-control unit module is used for receiving the sampled EEG signals and carrying out processing and feature extraction; and the result output module is used for sending the depression result to the terminal for display. According to the utility model, the detection of depression is realized by extracting the collected EEG signal characteristics.

Description

TECHNICAL FIELD

[0001] The utility model relates to the field of depression detection, especially to a depression detection device based on EEG signal. BACKGROUND

[0002] Depression is a global mental illness, its main features include: emotional experience, communication and self-regulation interruption. Since there is no uniform standard for the identification of depression, and the individual depression performance is not the same, it is easy to miss the best intervention time, and make the symptoms worse.

[0003] Electroencephalogram (EEG) can directly or indirectly reflect the activity of human brain, and EEG has become an important indicator in the judgment of brain function and state. Therefore, how to apply electroencephalogram to the field of depression detection, and then provide objective basis for mental health professionals and patients, is expected to bring important progress for the detection, diagnosis and treatment of depression patients. UTILITY MODEL CONTENT

[0004] The utility model provides a kind of depression detection device based on EEG signal, the utility model realizes the detection of depression by extracting the features of collected EEG signal, detailed in the following description:

[0005] A kind of depression detection device based on EEG signal, the device includes:

[0006] Collecting front end and right leg driving circuit, collecting the EEG signal of tester front end;

[0007] Pre-amplification circuit, the weak EEG signal after collection is amplified;

[0008] High-pass amplification filter circuit, the amplified EEG signal is high-pass filtered;

[0009] Low-pass amplification filter circuit, the amplified EEG signal is low-pass filtered;

[0010] Digital-analog conversion module, the amplified and filtered EEG signal is analog-digital converted and sampled;

[0011] Micro control unit module, receiving the EEG signal after sampling is handled and feature extraction;

[0012] Result output module, whether the result of depression is sent to terminal and is shown.

[0013] Among them, the device further includes: power module, for pre-amplification circuit, high-pass amplification filter circuit, low-pass amplification filter circuit, digital-analog conversion module and micro control unit module provide voltage.

[0014] The digital-analog conversion module adopts AD7606 chip. The power module selects TPS62170 chip to provide ±5V voltage.

[0015] The micro control unit module adopts STM32H743 micro controller in STM32 series.

[0016] The beneficial effects of the technical scheme provided by the utility model are:

[0017] 1、The utility model discloses a kind of low cost, high precision, and the device is convenient for detecting depression state, which is realized by the feature of EEG signal to recognize and diagnose depression state.

[0018] 2、The utility model realizes the whole process from the collection, processing, analysis to result output of EEG signal, realizes effective detection of depression, just need to wear EEG collector to collect brain wave data, avoid the diagnosis of traditional depression diagnosis in dependence on patient subjective expression or doctor subjective judgment, EEG signal as a kind of objective biological index, with higher objectivity and repeatability, depression detection device based on EEG signal can provide more objective and accurate depression diagnosis result.

[0019] 3、The technology of the utility model has the characteristics of convenient construction, precision and reliability, high cost performance and strong practicability. DRAWINGS

[0020] Figure 1 It is a kind of depression detection device based on EEG signal schematic diagram;

[0021] Figure 2 It is acquisition front end and right leg drive circuit diagram;

[0022] Figure 3 It is preamplifier circuit diagram;

[0023] Figure 4 It is high-pass amplification filter circuit diagram;

[0024] Figure 5 It is low-pass amplification filter circuit diagram;

[0025] Figure 6 It is analog-digital conversion and micro control unit circuit diagram. DETAILED DESCRIPTION

[0026] To make the purpose, technical scheme and advantages of the utility model more clear, the following further detailed description is made to the utility model embodiment.

[0027] A kind of depression detection device based on EEG signal, see Figure 1 , the device includes:

[0028] The acquisition front end and the right leg driving circuit realize the acquisition of the EEG signal of the tester front end and offset the most common mode signal from the human body through the right leg driving technology.

[0029] The preamplification circuit amplifies the weak EEG signal collected.

[0030] The high-pass amplification filter circuit high-pass filters the amplified EEG signal.

[0031] The low-pass amplification filter circuit low-pass filters the amplified EEG signal.

[0032] The digital-analog conversion module converts the amplified and filtered EEG signal into an analog signal and samples it.

[0033] The micro control unit module receives the sampled EEG signal for processing and feature extraction.

[0034] The power module provides normal voltage for the preamplification circuit, the high-pass amplification filter circuit, the low-pass amplification filter circuit, the digital-analog conversion module and the micro control unit module.

[0035] The result output module sends the result of depression or not to the terminal for display.

[0036] Referring to Figure 2 , the acquisition front end and the right leg driving module are composed of two parts of the EEG acquisition electrode and the right leg driving circuit, the EEG acquisition electrode is in contact with the forehead of the brain, and the electrode is embedded in the headband, and is divided into three electrodes E1, E2 and ER, the ER end signal is offset through the right leg driving circuit to offset the most common mode signal from the human body, and the acquisition of the brain wave signal is realized.

[0037] Referring to Figure 3 , the preamplification circuit adopts the structure of a differential circuit, which can maximize the input impedance and the common mode rejection ratio. AD8639 and AD8221 are selected, which have the characteristics of low noise, low drift and high common mode rejection ratio.

[0038] Many studies show that the main component of the EEG signal of the patient with depression is between 0.5Hz and 50Hz, and in order to avoid introducing the direct current component and the high frequency noise, improve the anti-interference ability of the system, and obtain higher gain, a filter circuit is generally designed behind the preamplification circuit, referring to Figure 4 and Figure 5 The high-pass amplification filter circuit and the low-pass amplification filter circuit selected in the embodiment of the utility model are helpful to extract the EEG signal in a specific frequency range.

[0039] Referring to Figure 6The digital-analog conversion module uses an AD7606 chip to complete the analog-digital conversion function of the electroencephalogram signal. The AD7606 chip has a 16-bit signal resolution, which has a clear advantage over the 12-bit resolution of the ADC of the STM32 chip. Its sampling range is divided into ±5V and ±10V, ensuring that the amplitude of the amplified electroencephalogram signal is covered. It can complete eight-channel synchronous input and is a chip that can be applied to data acquisition. The electroencephalogram signal is sent to the micro control unit module after sampling.

[0040] In the micro control unit module, an STM32H743 microcontroller in the STM32 series is used, which carries an ARM Cortex-M7 core and provides high performance and efficiency. The STM32H743 runs at a frequency of 400MHz, providing powerful computing power. In addition, the chip integrates a large-capacity flash memory and RAM, which is helpful for storing and processing a large amount of electroencephalogram signal data. This is very useful for long-term recording and analysis of electroencephalogram signals and is suitable for analyzing the collected electroencephalogram signal data.

[0041] The power module selects the TPS62170 chip to provide ±5V voltage, and the high-pass filter circuit, low-pass filter circuit, and AD7606 chip provide 5V and ±5V voltage, respectively. The STM32H7 main control module needs to be powered by a 3.3V power supply, and the TPS62160 / 1 / 2 chip can output 3.3 / 2.5 / 1.8 / 1.5 / 1.2 / 1 / -5V voltage. The chip provides 3.3V voltage for the main control chip STM32H743.

[0042] In the result output module, the results of whether the tester is depressed or not are obtained according to the processing and analysis of the electroencephalogram signal by the micro control unit module.

[0043] Example 2

[0044] The following will be combined Figures 2-6 The scheme in Example 1 is further introduced, which is described in detail as follows:

[0045] According to Figure 2The shown acquisition front end and right leg drive module, the electroencephalogram acquisition electrode and the forehead of the brain are in contact, and the electrode is embedded in the headband, which is divided into E1, E2 and ER three electrodes, and the ER end signal is offset through the right leg drive circuit to offset most of the common mode signal from the human body. Right leg drive is a common solution to reduce common mode interference. The common mode signal is detected by the middle tap of the two gain control resistors of AD8221, and the common mode signal is sent to the inverting amplifier after being buffered and amplified by AD8639. The inverting amplifier amplifies the common mode signal and then feeds it back to the right leg through the current limiting resistor R3. The amplification factor of the inverting amplifier is set by R2 and R1, and the amplification factor is generally set to 40-200. R3 is a current limiting resistor, which plays a safety protection role. R3 is generally 5MΩ.

[0046] Among them, the preamplification filter module contains three parts: preamplification circuit, high-pass amplification filter circuit and low-pass amplification filter circuit. According to Figure 3 The shown preamplification circuit adopts the structure of differential circuit, which can maximize the input impedance and common mode rejection ratio. The double-channel self-stable zero-type amplifier AD8639 with low noise characteristics of the amplification circuit can reduce the DC drift and system noise of the circuit itself. In addition, the input impedance of AD8639 is as high as 22.5TΩ, and the common mode rejection ratio is typically 142dB. Using it as a circuit can realize the isolation of signals between different leads on the one hand, and increase the input impedance of the system on the other hand. E1 and E2 are connected to the input end of AD8639, and the output is connected to the in-phase input end and the reverse input end of the main operational amplifier AD8221. AD8221 is one of the operational amplifier products of ADI Company, which has higher common mode rejection ratio and lower current demand. RG is the resistance value of the resistance for adjusting the amplification factor. The reference end of AD8221 is connected with the output of the right leg drive circuit.

[0047] Referring to Figure 4 and Figure 5 The high-pass amplification filter circuit and the low-pass amplification filter circuit, since the main component of the electroencephalogram signal is between 0.5Hz and 50Hz, in order to avoid introducing direct current component and high frequency noise, improve the anti-interference ability of the system, and obtain higher gain, generally high-pass filter amplification circuit and low-pass filter amplification circuit are designed after the preamplification circuit.

[0048] Referring to Figure 6The analog-to-digital converter (ADC) module converts analog signals (EEGs) generated by the brain's physiological activities into digital signals. The AD7606 chip from Analog Devices (ADI) is selected to perform this EEG signal conversion. This chip can perform eight-channel synchronous input, offering a fully integrated data acquisition solution with a sampling rate of up to 200K SPS per channel and a signal-to-noise ratio of up to 95.5dB. It is a chip specifically designed for data acquisition systems. The AD7606 chip is equipped with a standard SPI serial bus interface for easy communication with a microcontroller.

[0049] This module operates at ±5V and uses eight pins (AIN1-AIN8) as inputs for EEG signals. It samples and quantizes the amplified and filtered EEG signal. Pin D7 provides parallel data or interface data, while pin D15 selects between parallel data bits or parallel byte mode, enabling the output of the sampled signal. Although the ADC chip is simple in function, it is easy to operate for complex circuits and can shorten the quantization time. This chip provides 8-bit parallel output.

[0050] The STM32H743 microcontroller from the STM32 series is used. The microcontroller module is implemented by burning the trained parameters of the model into the microcontroller, detecting the input EEG signal, outputting the judgment result, and then displaying the depressive state in the result output module.

[0051] In summary, in order to overcome the shortcomings of existing methods for detecting depression, this invention designs a depression detection device based on EEG signals. By analyzing and processing the collected EEG signals, relevant information about depression is extracted for detection and identification.

[0052] Unless otherwise specified, the model numbers of the various components in this embodiment of the invention are not limited, and any component that can perform the above functions is acceptable.

[0053] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the sequence numbers of the above-mentioned embodiments are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0054] The above description is only a preferred embodiment of the present utility model and is not intended to limit the present utility model. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present utility model should be included within the protection scope of the present utility model.

Claims

1. A depression detection device based on an EEG signal, characterized by, The device comprises: A collection front end and a right leg drive circuit, which collects the front end EEG signal of a tester; A preamplifier circuit, which amplifies the weak EEG signal collected; A high-pass amplification filter circuit, which performs high-pass filtering on the amplified EEG signal; A low-pass amplification filter circuit, which performs low-pass filtering on the amplified EEG signal; An analog-to-digital conversion module, which performs analog-to-digital conversion and sampling on the amplified and filtered EEG signal; A micro control unit module, which receives the sampled EEG signal for processing and feature extraction; A result output module, which sends the result of depression or not to a terminal for display.

2. The depression detection device based on EEG signal according to claim 1, characterized in that, The device further comprises a power module, which provides voltage for the preamplifier circuit, the high-pass amplification filter circuit, the low-pass amplification filter circuit, the analog-to-digital conversion module and the micro control unit module. 3.The depression detection device based on EEG signal of claim 1, wherein, The analog-to-digital conversion module adopts an AD7606 chip.

4. The depression detection device based on EEG signal according to claim 2, characterized in that, The power module selects a TPS62170 chip to provide a voltage of ±5V. 5.The depression detection device based on EEG signal of claim 1, wherein, The micro control unit module adopts an STM32H743 microcontroller in the STM32 series.

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