A driver attention enhancement method based on low-frequency TMS

Abstract

The embodiment of the application provides a driver attention enhancement method based on low-frequency TMS, and belongs to the technical field of driving safety. The method comprises the following steps: obtaining a resting motor threshold of a driver, performing enhancement stimulation processing on the resting motor threshold to obtain a transcranial magnetic stimulation intensity; obtaining a first attention evaluation index value, the attention evaluation index value being used for measuring the driving attention concentration degree of the driver; determining a stimulation target point of the driver, and applying low-frequency TMS stimulation of the transcranial magnetic stimulation intensity to the stimulation target point; obtaining a second attention evaluation index value after the stimulation intensity of the low-frequency TMS is applied, and if the second attention evaluation index value is greater than the first attention evaluation index value, the driver attention enhancement is completed. The application actively intervenes in the driver through low-frequency transcranial magnetic stimulation, enhances the driver attention through individualized stimulation, and is beneficial to driving safety.

Description

Technical Field

[0001] This application relates to the field of driving safety technology, and in particular to a method for enhancing driver attention based on low-frequency TMS. Background Technology

[0002] Driver attention is one of the important factors affecting road traffic safety. When drivers are distracted, have excessive cognitive load, or have decreased alertness, they are prone to slow reaction, misjudgment of traffic conditions, and unstable vehicle control, thereby increasing the risk of traffic accidents.

[0003] Currently, relevant technologies typically enhance driver attention during driving through active intervention or passive reminders. Passive reminders rely on auditory and visual cues to stimulate the driver, serving only an informing function and failing to address the underlying neural decline in alertness or inattentiveness. For drivers already fatigued or severely distracted, the reminders are of very limited effectiveness. Active intervention methods include active cognitive training; however, this training cycle is lengthy, and biofeedback relies on the driver's active learning and continuous cooperation, making it difficult to meet the intervention needs of safe driving scenarios and thus unable to guarantee driving safety.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose a driver attention enhancement method based on low-frequency TMS, which enhances driver attention through personalized and adapted stimuli, thereby improving driving safety.

[0006] To achieve the above objectives, one aspect of this application proposes a method for enhancing driver attention based on low-frequency TMS, the method comprising: The driver's stimulation target point, driving state data, and resting motion threshold are obtained, wherein the resting motion threshold represents the minimum stimulation intensity that induces the driver's abductor pollicis brevis muscle movement response. The resting motion threshold is subjected to enhanced stimulation to obtain the transcranial magnetic stimulation intensity; Attention detection is performed on the driving state data to obtain the driver's attention detection result; If the attention detection result indicates that the driver's attention is in a state of decreased attention, then low-frequency TMS stimulation of the transcranial magnetic stimulation intensity is applied to the stimulation target.

[0007] In some embodiments, obtaining the driver's resting motion threshold includes: Obtain a first stimulus intensity, which is either the initial stimulus intensity or the second stimulus intensity from the previous process; Based on the first stimulation intensity, the driver is subjected to abductor pollicis brevis muscle movement stimulation to obtain movement stimulation information; If the output of the motion stimulus information is a valid motion stimulus, the first stimulus intensity is determined as the resting motion threshold, which is the minimum stimulus intensity required to induce the driver's abductor pollicis brevis muscle movement response; or, if the output of the motion stimulus information is an invalid motion stimulus, the first stimulus intensity is updated by phase increment to obtain the second stimulus intensity of the current test process, and then the process returns to the step of obtaining the first stimulus intensity.

[0008] In some embodiments, obtaining the transcranial magnetic stimulation intensity includes: Obtain the strength coefficient corresponding to the driver; The transcranial magnetic stimulation intensity is obtained by adapting the resting motion threshold based on the intensity coefficient.

[0009] In some embodiments, obtaining the driver's stimulation target points includes: Obtain a magnetic resonance imaging (MRI) image of the driver's head; Based on the head magnetic resonance imaging, the driver's brain structure was reconstructed in three dimensions to obtain a three-dimensional brain structure image. The three-dimensional brain structure image is registered to obtain the target stimulation brain region, and the target stimulation brain region is determined as the stimulation target point for the driver.

[0010] In some embodiments, the method further includes: Obtain a first attention evaluation index value and a second attention evaluation index value. The first attention evaluation index value is used to measure the driver's level of driving attention concentration before low-frequency TMS stimulation; the second attention evaluation index value is used to measure the driver's level of driving attention concentration after low-frequency TMS stimulation. Compare the second attention evaluation index value with the first attention evaluation index value to obtain the comparison result; If the comparison result shows that the second attention evaluation index value is less than the first attention evaluation index value, the transcranial magnetic stimulation intensity is increased until the second attention evaluation index value is greater than the first attention evaluation index value.

[0011] In some embodiments, obtaining the first attention evaluation metric value includes: Acquire baseline data of the driver, including the driver's electroencephalogram (EEG) signals; Feature extraction processing is performed on the baseline data to obtain SMR band signals and θ band signals; Power analysis processing is performed on the SMR band signal and the θ band signal to obtain the driver's first attention evaluation index value.

[0012] In some embodiments, if the comparison result shows that the second attention evaluation index value is less than the first attention evaluation index value, increasing the transcranial magnetic stimulation intensity until the second attention evaluation index value is greater than the first attention evaluation index value includes: If the second attention evaluation index value is less than the first attention evaluation index value, the transcranial magnetic stimulation intensity is updated, and the process returns to the step of applying low-frequency TMS stimulation at the transcranial magnetic stimulation intensity to the stimulation target; or, if the second attention evaluation index value is greater than or equal to the first attention evaluation index value, the process returns to the step of performing attention detection on the driving state data to obtain the driver's attention detection result.

[0013] To achieve the above objectives, another aspect of this application proposes a driver attention enhancement system based on a low-frequency TMS, the system comprising: The first module is used to obtain the driver's resting motion threshold, which represents the minimum stimulus intensity that induces the abductor pollicis brevis muscle movement response; The second module is used to enhance the resting motion threshold to obtain the transcranial magnetic stimulation intensity, wherein the transcranial magnetic stimulation intensity characterizes the stimulation intensity of low-frequency TMS stimulation applied by the transcranial magnetic stimulation device. The third module is used to determine the driver's stimulation target point and apply low-frequency TMS stimulation of the transcranial magnetic stimulation intensity to the stimulation target point.

[0014] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned driver attention enhancement method based on low-frequency TMS.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned driver attention enhancement method based on low-frequency TMS.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a method for enhancing driver attention based on low-frequency TMS. This scheme first obtains the resting motion threshold and stimulation target points of an individual driver, and then adapts the transcranial magnetic stimulation intensity to suit the individual driver's situation based on these. This enables personalized low-frequency TMS stimulation. Compared with a uniform fixed stimulation intensity, this scheme has stronger stimulation adaptability and more stable stimulation effect. At the same time, this scheme can monitor the driver's attention state in real time and apply low-frequency TMS stimulation only when a decline in driver attention is detected. By applying personalized low-frequency TMS stimulation to the stimulation target points, the state of driver distraction and decreased alertness can be improved. Compared with the traditional passive reminder method, this invention actively intervenes in the driver through low-frequency transcranial magnetic stimulation and enhances driver attention through personalized stimulation, which is conducive to improving driving safety. Attached Figure Description

[0017] Figure 1 This is a flowchart of a driver attention enhancement method based on low-frequency TMS provided in an embodiment of this application; Figure 2 This is a flowchart illustrating the acquisition of driver stimulation targets in an embodiment of this application; Figure 3 This is a flowchart illustrating the process of obtaining the driver's resting motion threshold in an embodiment of this application; Figure 4 This is a schematic diagram of transcranial magnetic stimulation intensity acquisition in an embodiment of this application; Figure 5 This is a flowchart illustrating the verification of attention enhancement level in an embodiment of this application; Figure 6 This is a flowchart of obtaining the first attention evaluation index in a preferred embodiment of this application; Figure 7 This is a flowchart of the first attention evaluation index acquisition process in another preferred embodiment of this application; Figure 8 This application provides a schematic diagram of a driver attention enhancement system based on a low-frequency TMS. Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of systems and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0020] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] In related technologies, enhancing driver attention during driving is typically achieved through active intervention or passive reminders. However, passive reminders lack objectivity and real-time capability. Driving behavior monitoring is susceptible to lighting conditions, occlusion, and individual differences. Vehicle operating parameter analysis is an indirect assessment, failing to accurately reflect the driver's attentional state. Furthermore, passive reminders rely primarily on auditory and visual cues to stimulate the driver, merely providing information and reminders without addressing the underlying neural decline in alertness or distraction. For drivers already fatigued or severely inattentive, the reminders are of very limited effectiveness. Active intervention methods include active cognitive training, but this requires a long training period and relies on the driver's active learning and continuous cooperation, making it difficult to meet the intervention needs of safe driving scenarios and thus compromising driving safety.

[0023] In view of this, this application provides a method for enhancing driver attention based on low-frequency TMS. This method first obtains the resting motion threshold and stimulation target points of an individual driver, and then adapts the transcranial magnetic stimulation intensity to suit the individual driver's situation. This enables personalized low-frequency TMS, which is more adaptable and has a more stable stimulation effect compared to a uniform fixed stimulation intensity. At the same time, this method can monitor the driver's attention state in real time and apply low-frequency TMS stimulation only when a decline in driver attention is detected. By applying personalized low-frequency TMS stimulation to the stimulation target points of the target brain region, the excitability of the cerebral cortex can be regulated at the neural level, improving the driver's distracted attention and decreased alertness. Compared with traditional passive reminder methods, the intervention effect of this method is more direct and reliable. By enhancing driver attention through personalized stimulation, it can effectively meet the needs of attention enhancement in driving scenarios and improve driving safety.

[0024] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0025] Figure 1 This is an optional flowchart of a driver attention enhancement method based on low-frequency TMS provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S101 to S106.

[0026] Step S101: Obtain the driver's stimulation target point, driving state data and resting motion threshold, wherein the resting motion threshold characterizes the minimum stimulation intensity required to induce the driver's abductor pollicis brevis muscle movement response. Step S102: Enhance the resting motion threshold to obtain the transcranial magnetic stimulation intensity; Step S103: Perform attention detection on the driving state data to obtain the driver's attention detection result; Step S104: If the attention detection result indicates that the driver's attention is in a state of decreased attention, then apply low-frequency TMS stimulation of the transcranial magnetic stimulation intensity to the stimulation target.

[0027] Steps S101 to S104 of this embodiment obtain the resting motion threshold and stimulation target of an individual driver, and then adapt the transcranial magnetic stimulation intensity to suit the individual driver's situation. This adapts to the differences in neural excitability among different drivers, avoiding the problems of insufficient or excessive stimulation caused by a uniform fixed stimulation intensity. The adaptability is stronger, and the stimulation effect is more stable. At the same time, this scheme can monitor the driver's attention state in real time during driving, and apply low-frequency TMS stimulation only when a decline in attention is detected. It will not cause unnecessary interference to drivers who are driving normally. By applying personalized low-frequency TMS to preset stimulation target points to regulate the excitability of the cerebral cortex, it can directly improve the state of driver's distraction and decreased alertness at the neural level. Compared with traditional passive audio-visual reminders, the intervention effect is more direct and can effectively improve the level of attention during driving and ensure driving safety.

[0028] The stimulation target is the location of the target brain region, specifically the scalp location corresponding to the left posterior parietal cortex of the driver; driving status data is data that can characterize the driver's current driving status, specifically including at least one of the driver's electroencephalogram (EEG) signals, driver's facial image data, and vehicle driving data; the resting motion threshold is the minimum stimulation intensity that can stably induce the abductor pollicis brevis muscle motor response based on the driver's individual adaptability.

[0029] Please see Figure 2 , Figure 2 The flowchart for obtaining the driver's resting stimulation target point is as follows: In step S101, obtaining the driver's stimulation target point includes: Obtain a magnetic resonance imaging (MRI) image of the driver's head; Based on the head magnetic resonance imaging, the driver's brain structure was reconstructed in three dimensions to obtain a three-dimensional brain structure image. The three-dimensional brain structure image is registered to obtain the target stimulation brain region, and the target stimulation brain region is determined as the stimulation target point for the driver.

[0030] In this embodiment, a brain region navigation and localization method based on the driver's head magnetic resonance imaging (MRI) is used to obtain the head MRI scan data (head MRI image) corresponding to the individual driver. The head MRI image is used to complete the three-dimensional modeling of the brain structure. Specifically, the driver's brain structure is reconstructed in three dimensions using a frameless navigation system. The driver's actual head position is then registered with the three-dimensional brain structure image to determine the location of the target stimulation brain region. This target brain region is then mapped onto the driver's scalp surface to finally determine the individualized stimulation target point for the driver.

[0031] This invention preferably uses the left posterior parietal cortex as the stimulation target, but the right or bilateral posterior parietal cortex can also be selected based on individual driver differences and intervention goals. The posterior parietal cortex is closely related to spatial attention, attentional orientation, and the frontoparietal attention network. By applying low-frequency transcranial magnetic stimulation to this brain region, the activity state of the driver's attentional function network can be modulated, thereby enhancing attention. During stimulation, the transcranial magnetic stimulation coil is placed on the scalp corresponding to the left posterior parietal cortex, preferably with the coil plane aligned with the scalp section, so that the induced electric field can effectively act on the target brain region.

[0032] In this embodiment, acquiring driving status data includes: The driver's brain signals are collected in real time by wearable EEG acquisition devices, facial image data of the driver is collected by vehicle-mounted cameras, and driving parameter data of the vehicle is obtained through the vehicle's CAN bus. The data are then integrated to obtain the driver's current driving status data.

[0033] Driving status data includes one of the following: driver's electroencephalogram (EEG) signals, driver's facial image data, and vehicle driving parameters. Among them, EEG signals can directly reflect the activity state of the driver's cerebral cortex and can be directly used to extract attention-related features, which is more accurate than indirect indicators such as images and vehicle parameters. Facial image data can be used to analyze characteristics that indicate fatigue and decreased attention, such as driver blinking frequency, eye closure duration, and head nodding frequency, to help improve the accuracy of attention detection. Vehicle driving parameters can reflect the driver's operational deviations, such as lane departure frequency and steering wheel adjustment range.

[0034] In one feasible implementation, the driving status data also includes baseline data, which includes data such as driver EEG signals, task reaction time, task accuracy, vehicle speed, steering wheel angle, and vehicle lateral deviation. The baseline data provides a baseline and control basis for evaluating changes in attention before and after transcranial magnetic stimulation intervention.

[0035] Please see Figure 3 , Figure 3 The flowchart for obtaining the driver's resting motion threshold is as follows: In step S101, obtaining the driver's resting motion threshold includes: Obtain a first stimulus intensity, which is either the initial stimulus intensity or the second stimulus intensity from the previous process; Based on the first stimulation intensity, the driver is subjected to abductor pollicis brevis muscle movement stimulation to obtain movement stimulation information; If the output of the motion stimulus information is a valid motion stimulus, the first stimulus intensity is determined as the resting motion threshold, which is the minimum stimulus intensity required to induce the driver's abductor pollicis brevis muscle movement response; or, if the output of the motion stimulus information is an invalid motion stimulus, the first stimulus intensity is updated by phase increment to obtain the second stimulus intensity of the current test process, and then the process returns to the step of obtaining the first stimulus intensity.

[0036] In this embodiment, the first stimulus intensity is either the initial stimulus intensity or the second stimulus intensity of the previous process, and the initial stimulus intensity is a default minimum value. During the measurement, a stimulation coil is applied to the driver's primary motor cortex. The stimulation intensity is gradually increased to obtain the minimum stimulation intensity that can stably induce the abductor pollicis brevis muscle motor response. Specifically, the measurement starts from the initial stimulation intensity and is continuously updated until a stimulation intensity that can stably induce the abductor pollicis brevis muscle motor response is obtained. This stimulation intensity is recorded as the resting motor threshold (RMT).

[0037] In other embodiments, those skilled in the art can make appropriate adjustments to the acquisition methods of the stimulation target, driving state data, and resting motion threshold based on their understanding of the inventive concept of this application.

[0038] Please see Figure 4 , Figure 4 This is a schematic diagram illustrating the acquisition of transcranial magnetic stimulation intensity according to an embodiment of this application. In some embodiments, step S102 involves enhancing the resting motion threshold to obtain the transcranial magnetic stimulation intensity, including: Obtain the strength coefficient corresponding to the driver; The transcranial magnetic stimulation intensity is obtained by adapting the resting motion threshold based on the intensity coefficient.

[0039] In this embodiment, the strength coefficient k is set to 1.2. Alternatively, the strength coefficient k can be adjusted within the range of 0.8 to 1.2 depending on the driver's tolerance or the high safety requirements.

[0040] The transcranial magnetic stimulation intensity I during formal intervention is determined based on the resting motor threshold, and its calculation formula is as follows: ; In the formula, I represents the transcranial magnetic stimulation intensity, RMT represents the driver's resting motion threshold, and k represents the intensity coefficient. Preferably, k is 1.2, that is, the formal stimulation intensity is 120% of the driver's resting motion threshold.

[0041] In some embodiments, if the driver's resting motion threshold is 50, the transcranial magnetic stimulation intensity I = 50 * 1.2 = 60; if the driver's resting motion threshold is 60, the transcranial magnetic stimulation intensity I = 60 * 1.2 = 72.

[0042] In some embodiments, the aforementioned low-frequency TMS specifically refers to transcranial magnetic stimulation with a frequency not higher than 1 Hz. In this embodiment, low-frequency transcranial magnetic stimulation with a stimulation frequency of 1 Hz is used to intervene in the target brain region. By regulating the cortical excitability of the corresponding brain region through low-frequency TMS, the effect of enhancing attention is achieved.

[0043] The resting motion threshold varies among different subjects, and the corresponding TMS stimulation intensity also varies accordingly. Therefore, this invention does not use a uniform fixed stimulation intensity, but calculates the formal stimulation intensity based on the driver's individual resting motion threshold, thereby improving the individual suitability and safety of transcranial magnetic stimulation intervention.

[0044] In other embodiments, those skilled in the art can make appropriate adjustments to the method of obtaining the transcranial magnetic stimulation intensity based on their understanding of the inventive concept of this application.

[0045] In some embodiments, step S103 involves performing attention detection on the driving state data to obtain the driver's attention detection result, specifically including: Different methods are used to detect attention based on different types of driving state data. For example, when driving state data includes EEG signals, attention-related frequency features can be extracted to determine the attention state. When driving state data includes facial image data, driver fatigue and inattention can be identified through eye and mouth features. When driving state data includes vehicle movement data, the driver's attention state can be indirectly determined through parameters such as lane departure and steering wheel operation frequency. In practice, combining multi-source data for attention detection can further improve the accuracy of attention state judgment and more accurately grasp the timing of stimuli.

[0046] In other embodiments, those skilled in the art can make appropriate adjustments to the method of obtaining the driver's attention detection results based on their understanding of the inventive concept of this application.

[0047] In step S104 of some embodiments, if the attention detection result indicates that the driver's attention is in a state of decreased attention, then low-frequency TMS stimulation of the transcranial magnetic stimulation intensity is applied to the stimulation target.

[0048] It should be noted that after a single stimulation intervention, the driver's attention status will continue to be monitored in real time. If a decline in attention is detected again, low-frequency TMS stimulation will be applied repeatedly to ensure that the driver maintains a sufficient level of attention during driving.

[0049] Please see Figure 5 In some embodiments, the method steps of the present invention may include, but are not limited to, steps S501 to S503: Step S501: Obtain a first attention evaluation index value and a second attention evaluation index value. The first attention evaluation index value is used to measure the driver's level of driving attention concentration before low-frequency TMS stimulation; the second attention evaluation index value is used to measure the driver's level of driving attention concentration after low-frequency TMS stimulation. Step S502: Compare the second attention evaluation index value and the first attention evaluation index value to obtain the comparison result; Step S503: If the comparison result is that the second attention evaluation index value is less than the first attention evaluation index value, increase the transcranial magnetic stimulation intensity until the second attention evaluation index value is greater than the first attention evaluation index value.

[0050] After transcranial magnetic stimulation (TMS) is completed, the driver enters the attention enhancement effect verification stage. A first attention evaluation index value and a second attention evaluation index value are obtained. The first attention evaluation index value is used to measure the driver's level of driving attention concentration before low-frequency TMS stimulation; the second attention evaluation index value is used to measure the driver's level of driving attention concentration after low-frequency TMS stimulation. Please see Figure 6 , Figure 6 Here is a flowchart of a preferred embodiment for obtaining a first attention metric, wherein obtaining the first attention evaluation metric value includes: Acquire baseline data of the driver, including the driver's electroencephalogram (EEG) signals; Feature extraction processing is performed on the baseline data to obtain SMR band signals and θ band signals; Power analysis processing is performed on the SMR band signal and the θ band signal to obtain the driver's first attention evaluation index value.

[0051] The first attention index and the second attention index are obtained in the same way. In this embodiment, the first attention index is obtained as follows: bandpass filtering is performed on the EEG signal to extract the 12-15Hz SMR band signal and the 4-7Hz theta band signal, respectively; then, the average power of the two band signals is calculated within the same time window, denoted as . and Finally, the ratio of the two is calculated to obtain the driver's primary attention index A: ; In the formula, A represents the driver's primary attention index. Indicates the average power in the SMR band. The θ band represents the average power, and ε is a very small constant greater than 0, used to avoid... Too small a value leads to unstable calculations.

[0052] The comparison result is obtained by comparing the second attention evaluation index value with the first attention evaluation index value. The comparison result is used to measure the difference between the second attention evaluation index value and the first attention evaluation index value. When the difference is a positive number greater than 0, it indicates that the attention has been improved and the driver's attention enhancement effect is good.

[0053] If the comparison result shows that the second attention evaluation index value is less than the first attention evaluation index value, that is, when the difference is a negative number less than 0, the transcranial magnetic stimulation intensity is increased until the second attention evaluation index value is greater than the first attention evaluation index value, specifically including: The transcranial magnetic stimulation intensity is updated, and the process returns to the step of applying low-frequency TMS stimulation at the stimulation target with the transcranial magnetic stimulation intensity. The update method includes adjusting the stimulation frequency, stimulation pulse number, stimulation duration, stimulation target or evaluation time window within a safe range, and re-intervening and obtaining attention evaluation indicators again.

[0054] In another feasible embodiment, please refer to Figure 7 , Figure 7 Here is a flowchart of the first attention metric acquisition process according to another preferred embodiment. Obtain the driver's task behavior data and the number of task errors; The task behavior data is analyzed and processed to obtain the task response time; The driver's first attention evaluation index value is obtained by weighted fusion processing of the task reaction time and the number of task errors.

[0055] Specifically, before the driver receives intervention, a designated attention task is completed. The average reaction time and the number of task errors are recorded during the task completion process. The number of task errors includes missed errors and false alarms. The first attention evaluation index value is obtained through weighted fusion processing. If it is confirmed by comparison that attention is not effectively enhanced under the current stimulus, the transcranial magnetic stimulation intensity is gradually increased within a safe range. The stimulation and effect verification steps are repeated until a satisfactory attention enhancement effect is achieved.

[0056] In other embodiments, those skilled in the art can make appropriate adjustments to the method of obtaining the first attention index based on their understanding of the inventive concept of this application.

[0057] The following is a detailed description and explanation of the solutions in the embodiments of the present invention, using specific application examples: This application provides a method for enhancing driver attention based on low-frequency transcranial magnetic stimulation (TMS). This method can be applied to scenarios prone to driver attention decline, such as prolonged high-speed driving and monotonous driving on urban and rural roads. By monitoring the driver's attention state in real time, individualized low-frequency TMS intervention is provided promptly upon detecting a decline in attention, helping the driver quickly restore their attention level and reducing the risk of traffic accidents caused by inattention. In practical applications, this method can be integrated into vehicle intelligent driving assistance systems, working in conjunction with onboard sensing equipment and portable TMS devices to achieve automated attention monitoring and intervention. It requires no manual operation from the driver, does not add extra burden to the driver, and the individualized stimulation parameters balance intervention effectiveness and driving safety, making it suitable for drivers of different ages and physical conditions.

[0058] Specifically, in this embodiment, before transcranial magnetic stimulation (TMS), the driver first enters the attention baseline data acquisition stage. This involves using an improved ANT attention network test paradigm, which collects behavioral and EEG data related to the driver's attention function and provides a baseline and control basis for evaluating attention changes before and after TMS intervention. The driver can perform an attention network test task or a simulated driving task. The system simultaneously collects data such as the driver's EEG signals, task reaction time, task accuracy, vehicle speed, steering wheel angle, and lateral vehicle deviation, using this data as pre-intervention baseline data.

[0059] Simultaneously, the driver's stimulation target points, driving state data, and resting motion threshold are acquired. The resting motion threshold is then enhanced with transcranial magnetic stimulation (TMS) to obtain the TMS intensity. When the driver is detected to be in a state of decreased attention, low-frequency TMS stimulation at the specified TMS intensity is applied to the stimulation target points. After stimulation, the driver's baseline data is collected again. In one feasible implementation, a two-back task is used to assess the driver's attention indicators. The two-back task requires the driver to determine whether the current task is the same as the previous two tasks; if the two are the same, the driver should respond as quickly and accurately as possible; if the two are different, the driver does not need to respond. The correctness of the task result is determined based on the driver's feedback, and the corresponding reaction time and number of errors are recorded. The driver's attention state is evaluated in conjunction with vehicle operation data. If the driver's reaction time is shortened and the number of errors is reduced after intervention, it indicates that the driver's attention maintenance and task response ability have improved; if the reaction time is prolonged or the number of errors increases, it indicates that the attention enhancement effect is not significant.

[0060] While performing a simulated driving task, the driver completes a two-back task. The system simultaneously collects the driver's EEG signals, task reaction time, number of task errors, and vehicle operation data. Vehicle operation data includes vehicle speed, acceleration, steering wheel angle, lateral deviation, and lane keeping status. Driving performance can be evaluated based on vehicle control stability, specifically including indicators such as lateral deviation, steering wheel angle fluctuation, and speed fluctuation. Lateral deviation reflects the driver's ability to keep the vehicle within the lane; a smaller lateral deviation indicates better lane keeping. Steering wheel angle fluctuation reflects the smoothness of the driver's steering control; smaller fluctuations indicate more stable vehicle control. Speed ​​fluctuation reflects the driver's ability to control vehicle speed; smoother speed changes indicate better driving performance. If, after transcranial magnetic stimulation (TMS) intervention, the driver's lateral deviation decreases, steering wheel angle fluctuation decreases, and speed control becomes smoother, it indicates improved driving performance, which can be used as one of the evaluation criteria for attention enhancement. Using the above data, the effect of low-frequency TMS on driver attention enhancement can be evaluated from three aspects: EEG activity, task behavior performance, and driving performance.

[0061] After completing the post-intervention evaluation, the control processing module compares and analyzes the data collected after the intervention with the baseline data collected before the intervention. The baseline data before the intervention includes driver baseline data and vehicle baseline data. The driver baseline data includes EEG attention indicators, two-back task reaction time, and number of task errors collected before the intervention. The vehicle baseline data includes driving performance indicators such as vehicle speed, steering wheel angle, lateral deviation, speed fluctuation, and lane keeping status collected before the intervention. The control processing module calculates the changes in each indicator before and after the intervention and determines the attention enhancement effect based on the combined changes in EEG indicators, task behavior indicators, and driving performance indicators.

[0062] Specifically, when EEG attention indicators improve after intervention, and at least one of the task behavior indicators or driving performance indicators improves simultaneously, the driver's attention enhancement effect can be determined to be good. Improvements in EEG attention indicators include an increase in the SMR / θ power ratio; improvements in task behavior indicators include a shortening of two-back task reaction time or a reduction in the number of task errors; improvements in driving performance indicators include a reduction in vehicle lateral deviation, a decrease in steering wheel angle fluctuation, a decrease in speed fluctuation, or an improvement in lane keeping. If EEG attention indicators do not improve after intervention, and both task behavior indicators and driving performance indicators do not improve or even worsen, the attention enhancement effect is determined to be insignificant. If the attention enhancement effect does not meet the preset requirements, the system can adjust the stimulation frequency, number of stimulation pulses, stimulation duration, stimulation target, or evaluation time window within a safe range, and then repeat the intervention and evaluation.

[0063] This application embodiment monitors the driver's attention state in real time and sets appropriate low-frequency transcranial magnetic stimulation parameters based on individual parameters. It intervenes promptly when attention declines, and verifies the enhancement effect by comparing multi-dimensional indicators before and after intervention. Dynamically adjusting stimulation parameters effectively improves the targeting and effectiveness of driver attention enhancement intervention. This ensures the intervention effect while also considering the varying stimulation needs of different drivers, enhancing the safety of the intervention process. It effectively reduces the safety risks caused by driver inattention during long-distance driving, providing new technical support for road traffic safety. In practical applications, the monitoring frequency, stimulation triggering conditions, and stimulation parameter adjustment range can be set according to the needs of different driving scenarios, adapting to the usage requirements of different application scenarios.

[0064] Please see Figure 8 This application also provides a driver attention enhancement system based on a low-frequency TMS to implement the above method, the system comprising: The first module is used to obtain the driver's resting motion threshold, which represents the minimum stimulus intensity that induces the abductor pollicis brevis muscle movement response; The second module is used to enhance the resting motion threshold to obtain the transcranial magnetic stimulation intensity, wherein the transcranial magnetic stimulation intensity characterizes the stimulation intensity of low-frequency TMS stimulation applied by the transcranial magnetic stimulation device. The third module is used to determine the driver's stimulation target point and apply low-frequency TMS stimulation of the transcranial magnetic stimulation intensity to the stimulation target point.

[0065] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0066] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0067] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0068] Please see Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the methods described in the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0069] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0070] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0071] This application provides a method, system, electronic device, storage medium, and program product for enhancing driver attention based on low-frequency TMS. It calculates the appropriate transcranial magnetic stimulation intensity by pre-obtaining the resting motion threshold of an individual driver, and then combines this with real-time attention monitoring results. When the driver's attention declines, it promptly applies individualized low-frequency TMS stimulation to regulate the excitability of the target brain cortex. This solves the problems of existing intervention methods relying on the driver's subjective judgment and having fixed stimulation parameters with poor adaptability. It can accurately and effectively help drivers restore their attention levels and improve driving safety without increasing the driver's operational burden. At the same time, the individualized parameter settings also ensure the safety and comfort of the intervention process, making it suitable for different individuals.

[0072] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0073] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0074] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0075] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0076] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0077] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0078] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0079] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0080] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for enhancing driver attention based on low-frequency TMS, characterized in that, The method includes the following steps: The driver's stimulation target point, driving state data, and resting motion threshold are obtained, wherein the resting motion threshold represents the minimum stimulation intensity that induces the driver's abductor pollicis brevis muscle movement response. The resting motion threshold is subjected to enhanced stimulation to obtain the transcranial magnetic stimulation intensity; Attention detection is performed on the driving state data to obtain the driver's attention detection result; If the attention detection result indicates that the driver's attention is in a state of decreased attention, then low-frequency TMS stimulation of the transcranial magnetic stimulation intensity is applied to the stimulation target.

2. The method according to claim 1, characterized in that, Obtaining the driver's resting motion threshold includes: Obtain a first stimulus intensity, which is either the initial stimulus intensity or the second stimulus intensity from the previous process; Based on the first stimulation intensity, the driver is subjected to abductor pollicis brevis muscle movement stimulation to obtain movement stimulation information; If the output of the motion stimulus information is a valid motion stimulus, the first stimulus intensity is determined as the resting motion threshold, which is the minimum stimulus intensity required to induce the driver's abductor pollicis brevis muscle movement response; or, if the output of the motion stimulus information is an invalid motion stimulus, the first stimulus intensity is updated by phase increment to obtain the second stimulus intensity of the current test process, and then the process returns to the step of obtaining the first stimulus intensity.

3. The method according to claim 1, characterized in that, The process of enhancing the resting motion threshold to obtain the transcranial magnetic stimulation intensity includes: Obtain the strength coefficient corresponding to the driver; The transcranial magnetic stimulation intensity is obtained by adapting the resting motion threshold based on the intensity coefficient.

4. The method according to claim 1, characterized in that, The acquisition of the driver's stimulation target points includes: Obtain a magnetic resonance imaging (MRI) image of the driver's head; Based on the head magnetic resonance imaging, the driver's brain structure was reconstructed in three dimensions to obtain a three-dimensional brain structure image. The three-dimensional brain structure image is registered to obtain the target stimulation brain region, and the target stimulation brain region is determined as the stimulation target point for the driver.

5. The method according to claim 1, characterized in that, The method further includes: Obtain a first attention evaluation index value and a second attention evaluation index value. The first attention evaluation index value is used to measure the driver's level of driving attention concentration before low-frequency TMS stimulation; the second attention evaluation index value is used to measure the driver's level of driving attention concentration after low-frequency TMS stimulation. Compare the second attention evaluation index value with the first attention evaluation index value to obtain the comparison result; If the comparison result shows that the second attention evaluation index value is less than the first attention evaluation index value, the transcranial magnetic stimulation intensity is increased until the second attention evaluation index value is greater than the first attention evaluation index value.

6. The method according to claim 5, characterized in that, The process of obtaining the first attention evaluation index value includes: Acquire baseline data of the driver, including the driver's electroencephalogram (EEG) signals; Feature extraction processing is performed on the baseline data to obtain SMR band signals and θ band signals; Power analysis processing is performed on the SMR band signal and the θ band signal to obtain the driver's first attention evaluation index value.

7. The method according to claim 5, characterized in that, If the comparison result shows that the second attention evaluation index value is less than the first attention evaluation index value, increasing the transcranial magnetic stimulation intensity until the second attention evaluation index value is greater than the first attention evaluation index value includes: If the second attention evaluation index value is less than the first attention evaluation index value, the transcranial magnetic stimulation intensity is updated, and the process returns to the step of applying low-frequency TMS stimulation at the transcranial magnetic stimulation intensity to the stimulation target; or, if the second attention evaluation index value is greater than or equal to the first attention evaluation index value, the process returns to the step of performing attention detection on the driving state data to obtain the driver's attention detection result.

8. A driver attention enhancement system based on a low-frequency TMS, characterized in that, The system includes: The first module is used to obtain the driver's resting motion threshold, which represents the minimum stimulus intensity that induces the abductor pollicis brevis muscle movement response; The second module is used to enhance the resting motion threshold to obtain the transcranial magnetic stimulation intensity, wherein the transcranial magnetic stimulation intensity characterizes the stimulation intensity of low-frequency TMS stimulation applied by the transcranial magnetic stimulation device. The third module is used to determine the driver's stimulation target point and apply low-frequency TMS stimulation of the transcranial magnetic stimulation intensity to the stimulation target point.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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