Driver state detection and vehicle control system based on in-ear EEG and PPG technologies

Abstract

The invention relates to the technical field of vehicle safety, and discloses an in-ear EEG and PPG technology-based driver state detection and vehicle control system, which comprises an acquisition module, a data processing and transmission module and a vehicle machine system which are connected in sequence, the acquisition module comprises a camera, an EEG acquisition module used for acquiring in-ear brain wave signals and a PPG acquisition module used for acquiring in-ear heart sound signals and pulse wave signals. The data processing and transmission module comprises a signal processing unit and a transmission unit, the signal processing unit is a WANDmini module, and the transmission unit is Bluetooth; the signal processing unit processes the signal acquired by the acquisition module and then transmits the signal to the vehicle machine system through the transmission unit; and the vehicle machine system receives and processes the data of the data processing and transmission module, divides the data into a normal condition and an abnormal condition, and executes operation according to different conditions. The system monitors the physiological state of a driver in real time, timely finds out dangers such as fatigue and distraction, and performs active intervention, so that the occurrence rate of traffic accidents is reduced.

Description

Technical Field

[0001] The present invention relates to the field of vehicle safety technology, and in particular to a driver state detection and vehicle control system based on in-ear EEG and PPG technology. Background Art

[0002] Vehicle safety monitoring is of great significance in preventing traffic accidents and improving driving safety, and continuous monitoring of the driver's physiological and psychological state is becoming increasingly critical. Traditional driver status monitoring relies on technologies such as cameras and steering wheel sensors, but these technologies have limitations. For example, cameras cannot accurately identify the driver's fatigue level and attention level, and steering wheel sensors can only reflect control behavior but cannot judge the psychological state. In contrast, in-ear EEG (electroencephalo-graph) and PPG (photoplethysmographic) technologies can more effectively monitor the driver's status and achieve vehicle control. At present, studies have shown that in-ear EEG and PPG technologies have higher signal quality, with a signal-to-noise ratio that is 10-20dB higher than traditional PPG, and in-ear EEG is 2-3 times higher than scalp EEG, which means that both in-ear EEG and PPG can obtain clearer extraction of the driver's EEG and pulse wave signals, and more accurately detect the driver's physiological and psychological state.

[0003] Although both in-ear EEG and PPG technologies have shown potential in driver status detection, they must undergo comprehensive and systematic debugging to accurately detect the driver's physiological and psychological state, including the type of EEG collection electrodes and the distribution of ear canal positions with PPG, the inability of PPG to estimate blood pressure, insufficient driver status segmentation, and vehicle driving assistance strategies. Currently, there are relatively few studies that combine EEG and PPG technologies and simultaneously control the vehicle accordingly. There is a lack of effective analysis methods and parameters based on ear EEG characteristic waves and PPG signal extraction, as well as feasible vehicle control strategies, which has hindered the development of the combination of in-ear EEG and PPG. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the driver state detection and vehicle control system based on in-ear EEG and PPG technology provided by the present invention can timely detect potential dangerous states such as fatigue and distraction by real-time monitoring of the driver's physiological state, such as heart rate, blood pressure, EEG signals, etc., and actively intervene.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a driver state detection and vehicle control system based on in-ear EEG and PPG technology, including a collection module, a data processing and transmission module and a vehicle system connected in sequence;

[0006] The acquisition module includes a camera, an EEG acquisition module for acquiring brain wave signals in the ear, and a PPG acquisition module for acquiring sound signals and pulse wave signals in the ear;

[0007] The data processing and transmission module includes a signal processing unit and a transmission unit. The transmission unit is Bluetooth. The signal processing unit processes the signal collected by the acquisition module and transmits it to the vehicle system through the transmission unit.

[0008] The vehicle system receives and processes the data from the data processing and transmission module and divides it into normal and abnormal situations. The vehicle system performs operations according to different situations; normal situations include fatigue, distraction and emotional state; abnormal situations include epileptic seizures, myocardial infarction and cardiovascular disease; operations performed include turning on assisted driving, seat adjustment, safety alarms and in-vehicle environment adjustment.

[0009] Furthermore, in the above-mentioned driver status detection and vehicle control system based on in-ear EEG and PPG technology, the EEG acquisition module includes a dry electrode arranged in the ear canal, and the dry electrode is a silver electrode.

[0010] Furthermore, in the above-mentioned driver state detection and vehicle control system based on in-ear EEG and PPG technology, the PPG acquisition module includes a photoplethysmography sensor and an in-ear microphone connected to the photoplethysmography sensor; the photoplethysmography sensor is arranged at the bottom or side inside the ear canal, and the photoplethysmography sensor is close to the cartilage of the ear canal.

[0011] Furthermore, in the above-mentioned driver status detection and vehicle control system based on in-ear EEG and PPG technology, the photoplethysmography sensor collects the pulse wave signal and blood pressure parameters in the ear, the pulse wave signal includes the pulse wave morphology, the pulse wave conduction time, and the pulse wave characteristic parameters; the blood pressure parameters include the systolic pressure and the diastolic pressure.

[0012] Furthermore, in the above-mentioned driver status detection and vehicle control system based on in-ear EEG and PPG technology, the in-ear microphone collects the heart sound signal in the ear, the heart sound signal includes the first heart sound and the second heart sound, the timing information of the first heart sound and the second heart sound is used to calculate the vascular conduction time; the intensity and frequency of the first heart sound and the second heart sound are used to reflect the functional state of the heart.

[0013] Furthermore, in the above-mentioned driver status detection and vehicle control system based on in-ear EEG and PPG technology, the data processing and transmission module pre-processes, segments, Fourier transforms, calculates power spectral density and extracts features on the signal through the signal processing unit, and transmits the processed signal to the vehicle system through the Bluetooth module.

[0014] Furthermore, in the above-mentioned driver status detection and vehicle control system based on in-ear EEG and PPG technology, the data processing and transmission module removes interference signals for subsequent signal processing according to the time and number of driver blinks collected by the camera, and the interference signals include electrooculogram artifacts.

[0015] Furthermore, in the above-mentioned driver status detection and vehicle control system based on in-ear EEG and PPG technology, the vehicle system performs pre-processing, SVM model training, model evaluation and classification on the data transmitted from the data processing and transmission module;

[0016] SVM model training divides fatigue status into mild fatigue, moderate fatigue and severe fatigue, and divides distraction status into concentration, mild distraction, moderate distraction and severe distraction; and divides emotional status into calm, anxiety and anger; the emotional status is judged by fusing the signals collected by the EEG acquisition module of the vehicle system with the signals collected by the PPG acquisition module.

[0017] Furthermore, in the above-mentioned driver status detection and vehicle control system based on in-ear EEG and PPG technology, the EEG acquisition module timely detects and prompts the user to adjust the wearing position through contact impedance monitoring of the dry electrode.

[0018] Furthermore, in the above-mentioned driver state detection and vehicle control system based on in-ear EEG and PPG technology, feature extraction is specifically as follows: the signal processing unit performs bandpass filtering on the EEG signal transmitted by the acquisition module through a 0.5Hz-100Hz FIR filter, uses fast Fourier transform to convert the EEG signal from the time domain to the frequency domain, calculates the power of each frequency point to obtain the power spectrum, and then calculates the average or sum of the power spectrum to obtain the power spectrum density; the signal processing unit divides the frequency range of the EEG signal into different frequency bands, and the frequency bands include delta waves, theta waves, alpha waves, beta waves and gamma waves.

[0019] The beneficial effects of the present invention are as follows: the driver status detection and vehicle control system of the in-ear EEG and PPG modules can timely detect potential dangerous conditions such as fatigue and distraction by real-time monitoring of the driver's physiological state, such as heart rate, blood pressure and EEG signals, and take active intervention, such as issuing warnings, slowing down and taking over driving, thereby effectively reducing the incidence of traffic accidents and improving driving safety.

[0020] The system uses in-ear EEG and PPG modules, which are comfortable to wear, easy to operate, highly concealed, and will not affect the driver's driving operation, thus improving the driving experience. The system can be personalized according to the individual differences of the driver, such as adjusting the warning threshold and intervention method, to further improve the effectiveness of the system.

[0021] In addition, the system can collect a large amount of driver status data to provide data support for the intelligent transportation system. The system can continuously optimize the model algorithm based on the data accumulation to improve the detection accuracy and reliability. The system can also be expanded to other application scenarios, such as fatigue driving warning, driving behavior analysis, etc., to promote the development of intelligent transportation and reduce the cost of traffic accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a module diagram of the system;

[0023] Figure 2 A schematic diagram of the wearing position of the acquisition module on the ear;

[0024] Figure 3 It is a schematic diagram of the connection relationship between the acquisition module and the data processing and transmission module;

[0025] Figure 4 This is the main program flow chart of this system;

[0026] Figure 5 It is the system subroutine flow chart under the normal condition of the driver;

[0027] Figure 6 It is a flow chart of the system subroutine under abnormal driver conditions;

[0028] Figure 7 This is a flow chart of the data signal processing by the data processing and transmission module collected by the EEG acquisition module. DETAILED DESCRIPTION

[0029] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0030] like Figure 1 As shown, this embodiment provides a driver state detection and vehicle control system based on in-ear EEG and PPG technology, including a collection module, a data processing and transmission module and a vehicle system connected in sequence;

[0031] The acquisition module includes a camera, an EEG acquisition module for collecting brain wave signals in the ear, and a PPG acquisition module for collecting intraocular sound signals and pulse wave signals in the ear; the camera mainly plays an auxiliary role, on the one hand, it improves the accuracy of eliminating blink artifacts, and on the other hand, it assists the system in determining whether the driver has been stationary for a long time.

[0032] The data processing and transmission module includes a signal processing unit and a transmission unit. The transmission unit is Bluetooth and the signal processing unit is a WANDmini module. The WANDmini module is a miniature, wireless, and interference-free neural recording module that integrates a low-noise amplifier, a high-precision ADC, a SoC FPGA, and a Bluetooth wireless transmission module. It can be used to amplify, filter, digitize, and wirelessly transmit EEG signals, and expand them to pulse signals. It can be set in the human ear. The signal processing unit processes the signals collected by the acquisition module and transmits them to the vehicle system through the transmission unit.

[0033] The vehicle system receives and processes the data from the data processing and transmission module and divides it into normal and abnormal situations. The vehicle system performs operations according to different situations; normal situations include fatigue, distraction and emotional fluctuations; abnormal situations include epileptic seizures, myocardial infarction, and cardiovascular disease attacks; operations performed include turning on assisted driving, seat adjustment, safety alarms and in-vehicle environment adjustment.

[0034] like Figures 2-3 As shown, the EEG acquisition module uses a silver electrode as a dry electrode placed in close contact with the ear canal at position E1, and a reference electrode placed at position E2 of the auricle to collect brain wave signals; the photoplethysmography (PPG) sensor is at the bottom of the ear canal, close to the cartilage part of the ear canal at position E3, and the in-ear microphone is placed at the top or side of the ear canal, close to the eardrum at position E4;

[0035] Before collecting signals, the EEG acquisition module and the PPG acquisition and in-ear microphone modules use the built-in electrode contact impedance (ESI) detection function of the signal processing unit to promptly detect and prompt the user to adjust the wearing position. Specifically, the EEG acquisition module in the signal processing unit measures the voltage and current between the electrode and the reference electrode at a sampling rate of 1000Hz, and uses these data to calculate the resistance value. When the silver electrode resistance is 5kΩ, the ESI value should be less than 10kΩ to be considered good contact. When it is greater than 10kΩ, the user is prompted to adjust the electrode position or pressure until the ESI value reaches the ideal range.

[0036] like Figure 4 As shown, Figure 4This is a system main program flow chart provided by this embodiment. The system is first initialized, and the EEG acquisition module, PPG acquisition and in-ear microphone module and camera are collected. The collected data is processed by the data processing and transmission module, that is, the signal processing unit, and the signal is transmitted to the car system for judgment operation. There are mainly two situations: the first is that the user has emotional fluctuations, and the data measured by EEG and PPG are combined to judge the type of emotion of the user. For example, when the user is anxious, the car system plays soothing music or performs relaxation training. When the user is angry, the car system automatically takes over the vehicle or provides emergency parking services. The second is that when the user is in a normal emotional state, it continues to judge whether the user is in a normal state of fatigue or distraction, or in an abnormal state such as high or low blood pressure, myocardial infarction, epilepsy, etc., and the car system will perform corresponding operations, such as Figures 5-6 As shown;

[0037] like Figure 7 As shown, the data processing logic of the signal processing unit is as follows: first, signal acquisition, converting EEG signals into electrical signals; second, preprocessing, filtering, re-referencing, segmentation, baseline correction and other signal processing; third, feature extraction, using power spectral density (PSD) to extract frequency domain features and wavelet transform (WT) to extract time-frequency domain features; fourth, feature selection, α wave power for fatigue detection, β wave power for emotion recognition, etc.; fifth, classification or analysis, using multi-class support vector machine (SVM), using one-to-many strategy for three-classification and four-classification; sixth, result output, outputting the classification or analysis results to the vehicle system via Bluetooth, and the vehicle system performs corresponding operations according to the specific situation;

[0038] In addition, the logic of judging the emotion type is as follows: negative emotions will affect the brain's neural activities, which will in turn lead to changes in the power of different bands in the EEG signal. The judgment criteria are that except for the decrease in alpha wave power, the other powers have increased. Combined with the data collected by PPG, the classification principle is that anger causes the event-related potential (ERP) P300 amplitude to increase, and the pulse wave may be sharper; anxiety causes the N400 amplitude to increase, and the pulse wave may be smoother when anxious.

[0039] like Figure 5 As shown, Figure 5 is a subroutine flow chart of a normal driver condition provided by this embodiment. Figure 4 Based on the changes in each band and the camera's eye tracking, it is determined whether the user is distracted or fatigued at this time. If it is judged as distracted driving, ① if it is mildly distracted, the car system will issue a soft prompt sound and the seat will vibrate; ② if it is moderately distracted, the car system will issue a strong prompt sound and the seat will vibrate; ③ if the driver is severely distracted, the car system will issue an emergency prompt sound and the seat will vibrate, and at the same time the emergency braking system will be prepared and the automatic driving assistance will intervene to avoid danger.

[0040] If it is judged as fatigue driving, ① if it is mild fatigue, the car system will emit a soft prompt sound and the seat vibrates; ② if it is moderate fatigue, the car system will emit a strong prompt sound, turn on the seat vibration massage and remind the driver to stop and rest, and turn off the interior ambient lighting; ③ if it is severe fatigue, the car system will emit an emergency prompt sound and the seat vibrates, the automatic driving assistance intervenes, and the system drives the car to a safe area and waits for the driver to recover.

[0041] The specific band changes are as follows: when the driver is fatigued, the θ wave power increases, the β wave power decreases, and the θ / β ratio increases; when the driver is distracted, the β wave power decreases and the γ wave power increases; the classification logic of each fatigue level is shown in Table 1; the classification logic of each distraction level is shown in Table 2;

[0042] Table 1:

[0043] Theta wave power threshold Beta wave power threshold Theta / Beta Ratio wide awake 0-5μV2 15-30μV2 0.1-0.3 Mild fatigue 5-10μV2 10-20μV2 0.3-0.5 Moderate fatigue 10-15μV2 5-10μV2 0.5-1.0 Severe fatigue 15-20μV2 0-5μV2 1.0-2.0

[0044] Table 2:

[0045] Beta wave power threshold Gamma wave power threshold Focus >100μV2 >50μV2 Mild distraction 80-100μV2 40-50μV2 Moderate distraction 60-80μV2 30-40μV2 Severe distraction <60μV2 <30μV2

[0046] The samples are labeled according to the thresholds divided by the fatigue level and distraction level, and then the support vector machine (SVM) four-classification model is continuously trained to optimize the parameters to improve the prediction accuracy. The evaluation of the SVM classification model is shown in Table 3:

[0047] Table 3:

[0048]

[0049] The model prediction results are shown in Table 4; among them, there are 100 samples for focus (A); 80 samples for mild distraction (B); 60 samples for moderate distraction (C); and 40 samples for severe distraction (D).

[0050] The actual labels are: Focused (A) with 120 samples; Mildly distracted (B) with 80 samples; Moderately distracted (C) with 60 samples; Severely distracted (D) with 40 samples

[0051] Table 4:

[0052]

[0053]

[0054] Accuracy = (100 + 80 + 60 + 40) / (120 + 80 + 60 + 40) = 0.833

[0055] Recall (A) = 100 / 120 = 0.833

[0056] Accuracy (A) = 100 / (100+0+0+0) = 1.000

[0057] F value (A) = 2*(0.833*1.000) / (0.833+1.000) = 0.917

[0058] Chi-square correlation coefficient = (0.833-0.667) / (1-0.667) = 0.667

[0059] This indicates that the consistency between the model prediction results and the true labels is high. According to the model prediction results and the set threshold, the data is classified into different levels of distraction.

[0060] See also Figure 6 , Figure 6 is a subroutine flow chart of a driver abnormal condition provided by this embodiment. Figure 4 On the basis of the information provided by the car computer system, the abnormal condition of the driver is judged according to the waveform, frequency and value of the signal received by the car computer system, mainly including high and low blood pressure, myocardial infarction and epilepsy, then the car computer system immediately issues an emergency prompt sound, such as "dangerous driving", "please take medicine immediately", etc. At the same time, the automatic driving assistance intervenes, pulls the vehicle to the side of the road and turns on the emergency lights, side lights and tail lights. At the same time, the camera extracts the driver's action information to determine whether it can recover by itself. If it cannot recover by itself within 1 minute, it will automatically call the emergency number and send the emergency address, then adjust the seat posture, open the windows for ventilation, and unlock the car to facilitate subsequent rescue; if it can recover by itself, it will wait for the driver to click on the car computer system screen to unlock the vehicle.

[0061] Among them, the changes in EEG and PPG values ​​and waveforms under different conditions are as follows:

[0062] When a driver has an epileptic seizure, spike waves with a duration of less than 70 milliseconds or sharp waves between 70 and 200 milliseconds will appear in the EEG signal waveform, which may be followed by a slow wave to form a spike-slow complex wave;

[0063] When a driver has a myocardial infarction, the heart's pumping function will be weakened and the rhythm will be disordered, the blood flow will slow down, and the heart rate variability (HRV) calculated by extracting the RR interval sequence from the pulse wave signal collected by the in-ear PPG sensor will be lower than 100ms. It will also cause the PPG waveform amplitude to decrease or deform, such as notching and widening of the peak.

[0064] At the same time, patients with hypertension are more likely to suffer from cardiovascular and cerebrovascular diseases such as cerebral hemorrhage and cerebral infarction, while hypotension may cause symptoms such as dizziness, fatigue, blurred vision, etc., affecting driving ability. Therefore, the in-ear microphone and PPG are used to collect heart sound and pulse wave signals, combined with the vascular conduction time (VTT) model, to achieve non-invasive monitoring of blood pressure. When the driver is in high blood pressure, the pulse wave amplitude of the PPG signal increases and the shape is sharp, the heart sound amplitude of the in-ear microphone signal increases, the waveform is sharp, and the time interval between the first heart sound (S1) and the second heart sound (S2) is shortened; on the contrary, when the driver is in low blood pressure, the pulse wave amplitude of the PPG signal decreases and the shape is gentle, the heart sound amplitude of the in-ear microphone signal decreases, the waveform is gentle, and the time interval between the first heart sound (S1) and the second heart sound (S2) is prolonged. The specific values ​​are shown in Table 5;

[0065] Table 5:

[0066] Diastolic blood pressure (DBP) Systolic blood pressure (SBP) Heart rate (HR) Normal people 60-80±5-10mmHg 90-140±10-15mmHg 60-100±1-2bpm Hypertensive patients ≥90±5-10 mmHg ≥140±10-15 mmHg 60-100±1-2bpm Patients with hypotension <60±5-10mmHg <90±10-15mmHg 60-100±1-2bpm

[0067] If the driver wears a pair of in-ear EEG and PPG detection, then when a stroke occurs, the driver's brain symmetry index (BSI) value is usually higher, indicating that brain symmetry is impaired. This is a measure of brain symmetry by comparing the difference in the spectral power of the EEG signal between the left and right hemispheres of the brain. The value range is 0 to 1, with 0 indicating perfect symmetry and 1 indicating maximum asymmetry. At the same time, the lateralization coefficient (LC) of the alpha band (8-13Hz) and beta band (13-30Hz) will decrease in severe stroke, which also depends on the type and location of the stroke.

[0068] This system provides a vehicle safety monitoring method based on physiological signals. EEG can capture the driver's brain activity and assess his fatigue and attention level, while PPG can measure changes in blood flow, monitor heart rate variability and emotional state, overcome the inconvenience and singleness of traditional monitoring methods, have higher portability and comfort, and are suitable for long-term monitoring. Combining this technology with the vehicle control system can identify the driver's abnormal state in real time, take safety measures in time, and provide more intelligent and comprehensive protection for vehicle safety.

Claims

1. A driver status detection and vehicle control system based on in-ear EEG and PPG technology, characterized in that: It includes a collection module, a data processing and transmission module and a vehicle computer system which are connected in sequence; The acquisition module includes a camera, an EEG acquisition module for acquiring brain wave signals in the ear, and a PPG acquisition module for acquiring sound signals and pulse wave signals in the ear; The data processing and transmission module includes a signal processing unit and a transmission unit, and the transmission unit is Bluetooth; the signal processing unit processes the signal collected by the collection module and transmits it to the vehicle system through the transmission unit; The vehicle system receives and processes data from the data processing and transmission module and divides it into normal conditions and abnormal conditions. The vehicle system performs operations according to different conditions; the normal conditions include fatigue, distraction and emotional state; the abnormal conditions include epileptic seizures, myocardial infarction and cardiovascular disease; the executed operations include turning on assisted driving, seat adjustment, safety alarm and in-vehicle environment adjustment.

2. The driver state detection and vehicle control system based on in-ear EEG and PPG technology according to claim 1 is characterized in that: The EEG acquisition module includes a dry electrode arranged in the ear canal, and the dry electrode is a silver electrode.

3. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 1 is characterized in that: The PPG acquisition module includes a photoplethysmography sensor and an in-ear microphone connected to the photoplethysmography sensor; the photoplethysmography sensor is arranged at the bottom or side of the ear canal, and the photoplethysmography sensor is close to the cartilage of the ear canal.

4. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 3 is characterized in that: The photoplethysmography sensor collects the pulse wave signal in the ear and blood pressure parameters. The pulse wave signal includes pulse wave morphology, pulse wave transmission time, and pulse wave characteristic parameters; the blood pressure parameters include systolic pressure and diastolic pressure.

5. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 3 is characterized in that: The in-ear microphone collects an in-ear heart sound signal, which includes a first heart sound and a second heart sound. The timing information of the first heart sound and the second heart sound is used to calculate the vascular conduction time; the intensity and frequency of the first heart sound and the second heart sound are used to reflect the functional state of the heart.

6. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 1, characterized in that: The data processing and transmission module performs preprocessing, segmentation, Fourier transformation, power spectrum density calculation and feature extraction on the signal through the signal processing unit, and transmits the processed signal to the vehicle system through the Bluetooth module.

7. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 6 is characterized in that: The data processing and transmission module removes interference signals for subsequent signal processing according to the time and number of driver blinks collected by the camera, and the interference signals include electrooculographic artifacts.

8. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 1, characterized in that: The vehicle computer system pre-processes, trains the SVM model, evaluates the model, and classifies the data transmitted from the data processing and transmission module; SVM model training divides fatigue status into mild fatigue, moderate fatigue and severe fatigue, and divides distraction status into concentration, mild distraction, moderate distraction and severe distraction; and divides emotional status into calm, anxiety and anger; the emotional status is judged by fusing the signal collected by the EEG acquisition module of the vehicle system with the signal collected by the PPG acquisition module.

9. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 1, characterized in that: The EEG acquisition module timely detects and prompts the user to adjust the wearing position through contact impedance monitoring of the dry electrode.

10. The driver status detection and vehicle control system based on in-ear EEG and PPG technology according to claim 6, characterized in that: The feature extraction is specifically as follows: the signal processing unit performs bandpass filtering on the EEG signal transmitted from the acquisition module through a 0.5Hz-100Hz FIR filter, uses fast Fourier transform to convert the EEG signal from the time domain to the frequency domain, calculates the power of each frequency point to obtain the power spectrum, and then calculates the average or sum of the power spectrum to obtain the power spectrum density; the signal processing unit divides the frequency range of the EEG signal into different frequency bands, which include delta waves, theta waves, alpha waves, beta waves and gamma waves.

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