Brain wave signal analysis method, device, storage medium and electronic device

Abstract

The present disclosure provides a method, device, storage medium and electronic device for analyzing brain wave signals, and relates to the field of computer technology, and in particular to the field of vehicle networking. The specific implementation scheme is: obtaining brain wave signals of a subject to be tested in multiple scenarios, wherein the multiple scenarios at least include resting scenarios and non-resting scenarios; performing joint analysis on brain wave signals in multiple scenarios to obtain initial analysis results; analyzing the health status of the subject to be tested based on the initial analysis results and the object information of the subject to be tested to obtain a target analysis result, wherein the object information at least includes the physiological information and pathological information of the subject to be tested.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, in particular to the field of Internet of Vehicles, and specifically to a method, device, storage medium and electronic device for analyzing brain wave signals. Background Art

[0002] As the pace of life accelerates and stress increases, many people are faced with chronic cardiovascular and cerebrovascular diseases. However, these diseases have a long incubation period and are well concealed, making them difficult to detect through daily observation and experience. Long-term, accurate tracking of brain information is conducive to the detection of these diseases, so as to intervene in advance and reduce the harm of the disease to the human body.

[0003] In the related art, brain wave signals can be detected by regular physical examinations or targeted physical examinations to detect diseases in a timely manner. However, regular physical examinations or targeted physical examinations are expensive, and they are usually not real-time physical examinations, but physical examinations are performed at regular intervals (for example, half a year or a year), so diseases cannot be detected in a timely manner.

[0004] In addition, in the related art, symptoms can be discovered through passive treatment and timely intervention can be made. However, when a patient becomes ill, the disease is usually already serious and the best treatment time may have been missed.

[0005] Moreover, in the related art, when analyzing brain wave signals, it is usually analyzed in a single scene, for example, collecting brain wave signals when the patient is in a resting state or sleeping state. Brain wave signals in other scenes can also play a certain role in analyzing the health status of the patient. Therefore, brain wave analysis in a single scene cannot accurately analyze the health status of the patient. Summary of the invention

[0006] The present invention provides a method, device, storage medium and electronic device for analyzing brain wave signals.

[0007] According to one aspect of the present disclosure, a method for analyzing brain wave signals is provided, comprising: obtaining brain wave signals of a subject to be tested in multiple scenarios, wherein the multiple scenarios include at least resting scenarios and non-resting scenarios; jointly analyzing the brain wave signals in the multiple scenarios to obtain initial analysis results; analyzing the health status of the subject to be tested based on the initial analysis results and object information of the subject to be tested to obtain a target analysis result, wherein the object information includes at least physiological information and pathological information of the subject to be tested.

[0008] According to another aspect of the present disclosure, there is also provided an analysis device for brain wave signals, including: an acquisition module, used to acquire brain wave signals of a test object in multiple scenarios, wherein the multiple scenarios include at least resting scenes and non-resting scenes; a joint analysis module, used to perform joint analysis on brain wave signals in multiple scenarios to obtain initial analysis results; and a health analysis module, used to analyze the health status of the test object based on the initial analysis results and object information of the test object to obtain a target analysis result, wherein the object information includes at least physiological information and pathological information of the test object.

[0009] According to another aspect of the present disclosure, an electronic device is also provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above-mentioned brain wave signal analysis method.

[0010] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is also provided, wherein the computer instructions are used to enable a computer to execute the above-mentioned brain wave signal analysis method.

[0011] According to another aspect of the present disclosure, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the computer program implements the above-mentioned brain wave signal analysis method.

[0012] It can be seen from the above content that the present disclosure adopts the method of analyzing brain wave signals in multiple scenes to analyze the health status of the object to be tested. In this process, the multiple brain wave signals collected are in multiple scenes. Therefore, compared with the solution of analyzing brain wave signals in a single scene in the related art, the present disclosure can improve the comprehensiveness of brain wave signal analysis, thereby improving the accuracy of brain wave analysis, and then improving the analysis accuracy of the health status of the object to be tested. In addition, in the present disclosure, it can be carried out in rest scenes and non-rest scenes, and the object to be tested does not need to go to a special institution for examination, which not only reduces the detection cost of the object to be tested, but also reduces the burden on the object to be tested. In addition, when analyzing the health status of the object to be tested, not only the analysis results of the brain wave signals are considered, but also the physiological information and pathological information of the object to be tested are considered, so that the analysis results of the health status are more accurate.

[0013] It can be seen that the solution provided by the present disclosure achieves the purpose of improving the comprehensiveness of brain wave signal analysis, thereby realizing the effect of improving the analysis accuracy of the health status of the subject to be tested, and further solving the problem of poor accuracy of health status analysis caused by the single brain wave signal collection scenario and incomplete brain wave signals in related technologies.

[0014] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0016] Figure 1 is a flow chart of a method for analyzing brain wave signals according to an embodiment of the present disclosure;

[0017] Figure 2 is a block diagram of an analysis system for brain wave signals according to an embodiment of the present disclosure;

[0018] Figure 3 is a schematic diagram of an analysis device for brain wave signals according to an embodiment of the present disclosure;

[0019] Figure 4 It is a block diagram of an electronic device used to implement the method for analyzing brain wave signals according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0020] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0021] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0022] Example 1

[0023] According to one aspect of the present disclosure, a method for analyzing brain wave signals is provided, such as Figure 1 As shown, the method comprises the following steps:

[0024] Step S102, obtaining brain wave signals of the subject to be tested in multiple scenes, wherein the multiple scenes at least include a resting scene and a non-resting scene.

[0025] In step S102, the subject to be tested may be a patient with chronic cardiovascular and cerebrovascular diseases or a non-patient. The resting scene in the above-mentioned multiple scenes may be a scene in which the subject to be tested is in a resting state, such as a sleeping scene, a massage scene, etc.; the above-mentioned non-resting scene is a scene in which the subject to be tested needs to concentrate, such as a vehicle driving scene, a work and office scene, a housework scene, a physical exercise scene, etc.

[0026] It should be noted that, in this embodiment, the brain wave signal of the object to be tested can be collected by a brain wave collection device, wherein the brain wave collection device in different scenes can be different, for example, in the sleeping scene, the brain wave collection device is a pillow; and in the physical exercise scene, the brain wave collection device can be a hat. In addition, the brain wave collection device in different scenes can also be the same, for example, in the sleeping scene and the vehicle driving scene, the brain wave collection device is a pillow.

[0027] In addition, it should be noted that in the solution provided by the present disclosure, brain wave signals of the subject to be tested can be collected in multiple scenarios, that is, by adopting the solution provided by the present disclosure, the subject to be tested does not need to go to a special institution for a physical examination or brain wave detection, and can detect brain wave signals in real time in actual life, work or study. For diseases with a long latency period and strong concealment, the solution provided by the present disclosure reduces the detection cost of the subject to be tested and also reduces the burden on the subject to be tested, avoiding the high time cost and high economic cost of collecting brain wave signals in related technologies, and also avoiding delays in disease intervention time.

[0028] In addition, through step S102, the multiple brain wave signals collected are in multiple scenarios. Therefore, compared with the solution of analyzing brain wave signals in a single scenario in the related art, the present disclosure can improve the comprehensiveness of brain wave signal analysis, thereby improving the accuracy of brain wave analysis, and further improving the accuracy of analysis of the health status of the subject to be tested.

[0029] Step S104, jointly analyzing the brain wave signals in multiple scenarios to obtain an initial analysis result.

[0030] In step S104, the brain wave signals in multiple scenes are jointly analyzed, which can be to merge the brain wave signals in multiple scenes to obtain a merged brain wave signal, and then analyze the merged brain wave signal to obtain an initial analysis result. The initial analysis result indicates whether there is an abnormality in the health status of the subject to be tested, that is, whether the subject to be tested has a disease.

[0031] It should be noted that when the subject is in different states, the composition of the corresponding brain wave signal is different. For example, when the subject is awake, the brain wave signal is mainly composed of high-frequency beta waves; when the subject is asleep, the brain wave signal is mainly composed of slow waves such as alpha waves and theta waves. Therefore, collecting complete fast waves and slow waves is crucial for accurate and timely diagnosis and location of the source of the disease. That is, by jointly analyzing brain wave signals in multiple scenarios, the accuracy of the health status analysis of the subject can be improved.

[0032] Step S106, analyzing the health status of the object to be measured based on the initial analysis result and the object information of the object to be measured to obtain a target analysis result.

[0033] In step S106, the object information of the object to be tested may include physiological information and pathological information of the object to be tested, wherein the physiological information includes but is not limited to gender, age, blood type, etc., and the pathological information includes but is not limited to disease history, allergy history, etc. In addition, the above-mentioned target analysis result represents the final analysis result of analyzing the health status of the object to be tested.

[0034] In addition, after obtaining the target analysis results, professional health care institutions can also generate health warning prompt information based on the above target analysis results to remind the subjects to seek medical treatment in time when their health conditions are abnormal; professional health care institutions can also generate interference strategies based on the above target analysis results to avoid the deterioration of the disease.

[0035] It should be noted that when analyzing the health status of the subject to be measured, not only the analysis results of the brain wave signals are considered, but also the object information of the subject to be measured, so that the analysis results of the health status are more accurate.

[0036] Based on the scheme defined in the above steps S102 to S106, it can be known that the health status of the object to be tested is analyzed by analyzing the brain wave signals in multiple scenes, by obtaining the brain wave signals of the object to be tested in multiple scenes, and jointly analyzing the brain wave signals in multiple scenes to obtain the initial analysis results, and then, based on the initial analysis results and the object information of the object to be tested, the health status of the object to be tested is analyzed to obtain the target analysis results. Among them, the multiple scenes include at least rest scenes and non-rest scenes, and the object information includes at least physiological information and pathological information of the object to be tested.

[0037] It is easy to notice that in the above process, the multiple brain wave signals collected are in multiple scenarios. Therefore, compared with the solution of analyzing brain wave signals in a single scenario in the related art, the present disclosure can improve the comprehensiveness of brain wave signal analysis, thereby improving the accuracy of brain wave analysis, and then improving the accuracy of analysis of the health status of the object to be tested. In addition, in the present disclosure, it can be carried out in resting scenes and non-resting scenes, and the object to be tested does not need to go to a special institution for examination, which not only reduces the detection cost of the object to be tested, but also reduces the burden on the object to be tested. In addition, when analyzing the health status of the object to be tested, not only the analysis results of the brain wave signals are considered, but also the physiological information and pathological information of the object to be tested are considered, so that the analysis results of the health status are more accurate.

[0038] It can be seen that the solution provided by the present disclosure achieves the purpose of improving the comprehensiveness of brain wave signal analysis, thereby realizing the effect of improving the analysis accuracy of the health status of the subject to be tested, and further solving the problem of poor accuracy of health status analysis caused by the single brain wave signal collection scenario and incomplete brain wave signals in related technologies.

[0039] Example 2

[0040] According to one aspect of the present disclosure, a method for analyzing a brain wave signal is provided. In an embodiment, each step defined in the above-mentioned embodiment 1 is described in detail.

[0041] Before explaining the various steps of the brain wave signal analysis method, we first introduce the brain wave signal analysis system. Figure 2 As shown, Figure 2 The block diagram of an optional brain wave signal analysis system is shown, and the system can be used as the execution subject of the method provided in Example 1. Figure 2 It can be seen that the system includes: a data acquisition system, a data processing system and a data terminal system.

[0042] Optional, by Figure 2 It can be seen that the data acquisition system includes a vehicle-side acquisition device and an indoor-side acquisition device. The vehicle-side acquisition device is based on the headrest of the car seat, and collects fast waves (i.e., beta waves) in daily car use and wakefulness scenes, wherein the fast waves are mainly related to the cognitive reasoning and tension state of the subject to be tested; the indoor-side acquisition device is based on the pillow, and collects slow waves (for example, alpha waves) in sleep and rest scenes, wherein the slow waves are mainly related to the sleep, subconsciousness, relaxation state, etc. of the subject to be tested.

[0043] It should be noted that the above-mentioned vehicle-side collection device and indoor-side collection device are equipped with flexible electrode sheets, which are equipped with dry electrodes for collecting brain wave signals. The flexible electrode sheet is small in size, portable and detachable, healthy, safe and comfortable. It is installed in the headrest of the car seat and the pillow at home. The dry electrode has a highly sensitive conductive property and can collect μV (microvolt) level signals, but it does not interfere with the individual, and the individual cannot even perceive its existence.

[0044] Optionally, the data processing system is used to store and process brain wave signals collected by home-side data and vehicle-side data. The data processing system can realize the data processing and data storage functions of brain wave signals, and the data processing system includes a data storage cloud platform and a data processing platform. Among them, the data storage cloud platform can store brain wave signals collected by the data acquisition system by purchasing or leasing a public cloud. The main body of the data processing platform is an EEG (Electroencephalogram) electroencephalogram processing program with a built-in automatic analysis engine, which can regularly perform programmable processing on the collected EEG data.

[0045] Optionally, the data terminal system includes at least an institutional end system and a user end system. The data terminal system can exist in the form of a web page or an application program, which is used to visually display the health status of the object to be tested on mobile\PC\webpage and other ports, and can be searched and consulted by the customers corresponding to the data terminal system. The customer group corresponding to the data terminal system can be individual customers, such as the object to be tested or the car owner; the customer group corresponding to the data terminal system can also be institutional customers, such as a health care hospital that has signed a contract with the object to be tested. Among them, different customer groups have different rights to access data. For example, for user-end customers, they can have full data rights; while for institutional-end customers, they have partial data access rights, and the partial data rights are related to the degree to which the object to be tested opens rights to the institutional-end customers.

[0046] In addition, the subject to be tested can authorize permissions to the institution-side system through the user-side system, and the institution-side system can generate health warnings or health management strategies, and send the health warnings or health management strategies to the user-side system for user review.

[0047] The specific method of the specific embodiment 1 is explained below.

[0048] In an optional embodiment, the data acquisition system in the brain wave signal analysis system executes step S102, that is, the data acquisition system obtains the brain wave signals of the object to be tested in multiple scenarios.

[0049] Specifically, the data acquisition system collects the first brain wave signals of the subject under different driving conditions through a first brain wave acquisition device located in a target vehicle in a vehicle driving scene, and collects the second brain wave signals of the subject under resting conditions through a second brain wave acquisition device located in a resting scene. The non-resting scene includes at least a vehicle driving scene.

[0050] Optionally, the first brain wave acquisition device mentioned above is a vehicle-side acquisition device, and the second brain wave acquisition device is an indoor-side acquisition device. In this embodiment, the first brain wave acquisition device can be a seat pillow in the vehicle, and the second brain wave acquisition device can be a sleeping pillow. Install a portable brain wave signal acquisition device on the car seat headrest and the pillow at home, and the devices at both ends are connected. The car seat headrest (i.e., the first brain wave acquisition device) is responsible for collecting EEG data in daily, awake states; and the pillow at home (i.e., the second brain wave acquisition device) collects EEG data in sleeping and resting states. Physiological data acquisition in both states is automatic and painless data collection without interference in daily life.

[0051] In addition, the first brain wave signals collected are brain wave signals of the subject to be tested under different driving conditions, for example, brain wave signals under driving conditions such as sudden braking, turning, going straight, and high-speed driving.

[0052] It should be noted that by collecting the brain wave signals of the subjects to be tested in different scenarios, the brain wave signals can be obtained more accurately and comprehensively, thereby improving the accuracy of health status analysis. In addition, since the brain wave signals of the subjects to be tested can be collected in real time in different scenarios, the subjects to be tested do not need to enter a specialized institution for testing, which not only reduces the cost of collecting brain wave signals, but also reduces the burden on the subjects to be tested, and improves the convenience of analyzing brain wave signals.

[0053] In an optional embodiment, if Figure 1 As shown, after acquiring the brain wave signals of the subject to be tested in multiple scenes, the data processing system executes step S104 to jointly analyze the brain wave signals in multiple scenes to obtain initial analysis results.

[0054] Specifically, the data processing system merges the first brain wave signal and the second brain wave signal to obtain a merged brain wave signal, then preprocesses the merged brain wave signal to obtain a preprocessed brain wave signal, and analyzes the preprocessed brain wave signal to obtain an initial analysis result.

[0055] Optionally, the data processing system first stores the first brain wave signal and the second brain wave signal in a shared cloud so that other clients can call the brain wave signal later. Then, the data processing system can merge the first brain wave signal and the second brain wave signal detected over a period of time. For example, the data processing system automatically merges all the brain wave signals collected last or this month.

[0056] In actual applications, the brain waves collected by the data acquisition system may have defects, for example, the collected brain wave signals contain noise. In order to improve the accuracy of brain wave signal analysis and thus improve the accuracy of health status analysis of the subject to be tested, the data processing system pre-processes the combined brain wave signals and then analyzes the pre-processed brain wave signals to obtain the initial analysis results.

[0057] It should be noted that the combined processing of the first brain wave signal and the second brain wave signal can obtain complete fast waves and slow waves, which is crucial for accurate and timely diagnosis and location of the source of the disease. Preprocessing the brain wave signal can avoid the influence of defects in the brain wave signal on the brain wave analysis results, thereby improving the accuracy of the health status analysis of the object to be tested, that is, by jointly analyzing the first brain wave signal and the second brain wave signal, the accuracy of the health status analysis of the object to be tested can be improved.

[0058] In the process of preprocessing the combined brain wave signal to obtain the preprocessed brain wave signal, the data processing system may preprocess the combined brain wave signal by the following steps:

[0059] Step S1, denoising the combined brain wave signal to obtain a denoised brain wave signal.

[0060] It should be noted that since the collection scenarios of brain wave signals are relatively complex, including resting scenarios (for example, bedrooms) and vehicle driving scenarios (such as vehicle driving scenarios and parking scenarios), a lot of noise will be caused by the external and physiological conditions of the subject to be tested (such as mental tension during high-speed driving, blinking, etc.). Therefore, it is necessary to filter out the noise in the brain wave signal to correct the artifacts of the merged brain wave signal, for example, correcting the eye movement artifacts. Among them, the data processing system can use the filtering models corresponding to different scenarios to perform targeted denoising on the merged brain wave signal. For example, the filtering model of the vehicle driving scenario is used to filter the first brain wave signal in the merged brain wave signal, and the filtering model of the rest scenario is used to filter the second brain wave signal in the merged brain wave signal.

[0061] Step S2, segmenting the denoised brain wave signal according to preset time periods to obtain brain wave signals corresponding to multiple time periods.

[0062] In this step, the data processing system can select an appropriate time period for monitoring brain waves, such as N200 or P300, according to the detection requirements.

[0063] Step S3, converting the brain wave signals corresponding to the multiple time periods into digital signals to obtain converted brain wave signals.

[0064] In this step, the data processing system can convert the continuous brain wave signal into a digital signal, and at the same time eliminate the interference of the 50Hz mains power on the brain wave signal.

[0065] Step S4, performing baseline correction on the converted brain wave signal to obtain a corrected brain wave signal.

[0066] In this step, the data processing system may select the waves within the first 1 / 10-1 / 5 of the EEG segment as the baseline, and adjust the brain wave signal based on the baseline to eliminate the deviation of the brain wave signal from the baseline.

[0067] Step S5, averaging the corrected brain wave signal to obtain a pre-processed brain wave signal.

[0068] In this step, the data processing system can perform superposition and average processing on the brain wave signals of the subject in two scenarios and time periods: when the subject is sleeping and when the subject is awake using the car.

[0069] It should be noted that by preprocessing the brain wave signal through the above steps, the influence of defects in the brain wave signal on the brain wave analysis results can be avoided, thereby improving the accuracy of the health status analysis of the object to be tested, that is, by jointly analyzing the first brain wave signal and the second brain wave signal, the accuracy of the health status analysis of the object to be tested can be improved.

[0070] In an optional embodiment, if Figure 1 As shown, after obtaining the initial analysis result, the data terminal system in the brain wave signal analysis system executes step S106, that is, the data terminal system analyzes the health status of the object to be measured based on the initial analysis result and the object information of the object to be measured to obtain the target analysis result.

[0071] Specifically, the data terminal system sends the initial analysis result to the preset platform, and obtains the target analysis result of the preset platform analyzing the object information and the initial analysis result of the object to be tested. The preset platform has the target authority granted by the object to be tested, and the target authority at least includes the authority to obtain the object information and the authority to obtain the initial analysis result.

[0072] It should be noted that the above-mentioned preset platform can be the platform of the health care institution that has signed a contract with the subject to be tested, wherein the authority obtained by the health care institution must be based on the authorization of the subject to be tested. The health care institution that has signed a contract with the subject to be tested can strive to obtain the trust and full authorization of the subject to be tested to collect data, so as to provide more targeted high-quality services when the customer visits for diagnosis and treatment, so as to improve the service level and income level.

[0073] Optionally, the object information that can be obtained by the preset platform may include but is not limited to gender, age, blood type, medical history, brain cognitive function data (based on brain wave collection) and other information. In addition, the subject to be tested can set the data transmission frequency. For example, the subject to be tested can choose to transmit data to the preset platform monthly, quarterly, semi-annually, etc. The subject to be tested with abnormal health conditions can also increase the above data transmission frequency to weekly or daily, so as to track and monitor health data in a timely and real-time manner.

[0074] It should be noted that when analyzing the health status of the subject to be tested, not only the analysis results of the brain wave signals are considered, but also the subject information of the subject to be tested, so that the analysis results of the health status are more accurate. Moreover, the preset platform can only obtain the data information authorized by the subject to be tested, thereby ensuring the security of the data information of the subject to be tested.

[0075] Furthermore, when the target analysis result indicates that the health condition of the subject to be measured is in an abnormal state, the brain wave signal analysis system can obtain a health management strategy generated by a preset platform based on the subject information of the subject to be measured and the initial analysis result.

[0076] Optionally, after completing the data processing of brain wave signals, the brain wave signal analysis system can generate health warnings or health management strategies (for example, medical advice) by combining the object information of the subject to be tested that is already on the preset platform, such as medical history, age and other data. If a health care institution reads that a user's data is abnormal, it can arrange for examination or treatment in advance. During this period, information flows quickly in a closed loop without delays or obstructions, ensuring that user health management is best protected.

[0077] It should be noted that the introduction of authoritative pathological judgments from professional health care institutions, combining brain wave signals with the basic information of the subject to be tested to analyze the user's health status (i.e., subject information), further improves the accuracy of health status analysis. In addition, health care institutions can provide health management strategies for the cases of the subjects to be tested, thereby preventing the disease from worsening and endangering the life of the subjects to be tested.

[0078] In addition, the brain wave signal analysis system can also send the initial analysis results and / or health management strategies to the target terminal device, and display the initial analysis results and / or health management strategies in a visual form in the target terminal device.

[0079] It should be noted that the above-mentioned initial analysis results, target analysis results and health management strategies can all be stored on the shared cloud, so that the subject to be tested can query through the target terminal device, or query by the health care institution. In addition, the subject to be tested can query the above-mentioned initial analysis results and health management strategies through the target terminal device, so that the subject to be tested can understand their own health status in time, and when the health status is abnormal, they can save themselves or seek medical treatment based on the health management strategy, thereby reducing the harm of the deterioration of the disease to the human body.

[0080] As can be seen from the above content, the solution provided by the present disclosure can realize health data processing and data management, and the collection, conversion, and authorized use of precision EEG data involve complex data analysis engines and data management methods. The data collection in this solution can comprehensively cover multiple scenes (sleep, driving, etc.), covering a variety of waveform data, thereby improving the comprehensiveness of brain wave signal analysis, and then improving the analysis accuracy of the health status of the object to be tested. Moreover, the cost of data collection is low, and users do not need to experience data collection specifically, and data collection can be completed only in daily life, saving time and economic costs. In addition, using the solution provided by the present disclosure, during the data collection process, the user experience is better, the whole process is in a natural state, without interference, and will not cause tension and burden to the user. Finally, in the solution provided by the present disclosure, monitoring is more timely, agile, and effective, data is connected to health care institutions, and questionnaires are found to intervene in time to avoid damage to the human body caused by the deterioration of the disease.

[0081] Example 3

[0082] According to one aspect of the present disclosure, there is also provided a device for analyzing brain wave signals, such as Figure 3 As shown, the device includes: an acquisition module 301, a joint analysis module 303 and a health analysis module 305.

[0083] Among them, the acquisition module 301 is used to obtain the brain wave signals of the object to be tested in multiple scenarios, wherein the multiple scenarios include at least resting scenes and non-resting scenes; the joint analysis module 303 is used to jointly analyze the brain wave signals in multiple scenarios to obtain initial analysis results; the health analysis module 305 is used to analyze the health status of the object to be tested based on the initial analysis results and the object information of the object to be tested to obtain the target analysis results, wherein the object information includes at least the physiological information and pathological information of the object to be tested.

[0084] Optionally, the acquisition module includes: a first acquisition module and a second acquisition module. The first acquisition module is used to acquire the first brain wave signal of the subject to be tested in different driving states through a first brain wave acquisition device of the target vehicle located in a vehicle driving scene, wherein the non-resting scene at least includes a vehicle driving scene; the second acquisition module is used to acquire the second brain wave signal of the subject to be tested in a resting scene through a second brain wave acquisition device located in a resting scene.

[0085] Optionally, the joint analysis module includes: a merging module, a preprocessing module and a first analysis module. The merging module is used to merge the first brain wave signal and the second brain wave signal to obtain a merged brain wave signal; the preprocessing module is used to preprocess the merged brain wave signal to obtain a preprocessed brain wave signal; the first analysis module is used to analyze the preprocessed brain wave signal to obtain an initial analysis result.

[0086] Optionally, the health analysis module includes: a first sending module and a second analysis module. The first sending module is used to send the initial analysis result to a preset platform, wherein the preset platform has the target authority granted by the object to be tested, and the target authority at least includes the authority to obtain the object information and the authority to obtain the initial analysis result; the second analysis module is used to obtain the target analysis result of the preset platform analyzing the object information and the initial analysis result of the object to be tested.

[0087] Optionally, the brain wave signal analysis device also includes: a first acquisition module, which is used to obtain a health management strategy generated by a preset platform based on the object information of the object to be tested and the initial analysis result when the target analysis result indicates that the health status of the object to be tested is in an abnormal state.

[0088] Optionally, the brain wave signal analysis device also includes: a second sending module, used to send the initial analysis results and / or health management strategies to the target terminal device, and display the initial analysis results and / or health management strategies in a visual form in the target terminal device.

[0089] Optionally, the preprocessing module includes: a denoising module, a segmentation module, a conversion module, a correction module and a first processing module. Among them, the denoising module is used to perform denoising on the merged brain wave signal to obtain the denoised brain wave signal; the segmentation module is used to perform segmentation processing on the denoised brain wave signal according to the preset time period to obtain the brain wave signals corresponding to multiple time periods; the conversion module is used to convert the brain wave signals corresponding to multiple time periods into digital signals to obtain the converted brain wave signals; the correction module is used to perform baseline correction on the converted brain wave signal to obtain the corrected brain wave signal; the first processing module is used to perform averaging processing on the corrected brain wave signal to obtain the preprocessed brain wave signal.

[0090] Example 4

[0091] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0092] Figure 4 A schematic block diagram of an example electronic device 400 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0093] like Figure 4 As shown, the device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the device 400 can also be stored. The computing unit 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0094] A number of components in the device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the device 400 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0095] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as the analysis method of brain wave signals. For example, in some embodiments, the analysis method of brain wave signals may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the analysis method of the brain wave signals described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the analysis method of brain wave signals by any other appropriate means (e.g., by means of firmware).

[0096] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0097] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0098] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0099] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0100] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0101] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0102] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0103] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for analyzing brain wave signals, comprising: Acquiring brain wave signals of the subject to be tested in multiple scenes, wherein the multiple scenes at least include a resting scene and a non-resting scene; Performing joint analysis on the brain wave signals in the multiple scenarios to obtain an initial analysis result; Analyze the health status of the subject to be tested based on the initial analysis result and the subject information of the subject to be tested to obtain a target analysis result, wherein the subject information at least includes physiological information and pathological information of the subject to be tested; Among them, obtaining brain wave signals of the object to be tested in multiple scenarios includes: collecting the first brain wave signal of the object to be tested in different driving states through a first brain wave acquisition device of a target vehicle located in a vehicle driving scene, wherein the non-resting scene at least includes the vehicle driving scene; and collecting the second brain wave signal of the object to be tested in the resting scene through a second brain wave acquisition device located in the resting scene.

2. The method according to claim 1, wherein: The brain wave signals in the multiple scenarios are jointly analyzed to obtain initial analysis results, including: Combining the first brain wave signal and the second brain wave signal to obtain a combined brain wave signal; Preprocessing the combined brain wave signal to obtain a preprocessed brain wave signal; The preprocessed brain wave signal is analyzed to obtain the initial analysis result.

3. The method according to claim 1, wherein: Analyzing the health status of the object to be tested based on the initial analysis result and the object information of the object to be tested to obtain a target analysis result, including: Sending the initial analysis result to a preset platform, wherein the preset platform has target permissions granted by the object to be tested, and the target permissions at least include permissions to obtain the object information and permissions for the initial analysis result; A target analysis result is obtained by analyzing the object information of the object to be tested and the initial analysis result by the preset platform.

4. The method according to claim 3, further comprising: When the target analysis result indicates that the health condition of the object to be measured is in an abnormal state, a health management strategy generated by the preset platform based on the object information of the object to be measured and the initial analysis result is obtained.

5. The method according to claim 4, further comprising: The initial analysis result and / or the health management strategy are sent to a target terminal device, and the initial analysis result and / or the health management strategy are displayed in a visual form in the target terminal device.

6. The method according to claim 2, wherein: Preprocessing the combined brain wave signal to obtain a preprocessed brain wave signal includes: Performing denoising processing on the combined brain wave signal to obtain a denoised brain wave signal; Segmentally process the denoised brain wave signal according to preset time periods to obtain brain wave signals corresponding to multiple time periods; Converting the brain wave signals corresponding to the multiple time periods into digital signals to obtain converted brain wave signals; Performing baseline correction on the converted brain wave signal to obtain a corrected brain wave signal; The corrected brain wave signal is averaged to obtain the preprocessed brain wave signal.

7. An analysis device for brain wave signals, comprising: An acquisition module, used for acquiring brain wave signals of the subject to be tested in multiple scenes, wherein the multiple scenes at least include a resting scene and a non-resting scene; A joint analysis module, used to jointly analyze the brain wave signals in the multiple scenarios to obtain an initial analysis result; A health analysis module, configured to analyze the health status of the subject to be tested based on the initial analysis result and the subject information of the subject to be tested, to obtain a target analysis result, wherein the subject information at least includes the physiological information and pathological information of the subject to be tested; Wherein, the acquisition module includes: a first acquisition module, used to collect the first brain wave signal of the object to be tested in different driving states through a first brain wave acquisition device of the target vehicle located in a vehicle driving scene, wherein the non-resting scene at least includes the vehicle driving scene; a second acquisition module, used to collect the second brain wave signal of the object to be tested in the resting scene through a second brain wave acquisition device located in the resting scene.

8. The device according to claim 7, wherein: The joint analysis module includes: a merging module, used for merging the first brain wave signal and the second brain wave signal to obtain a merged brain wave signal; A preprocessing module, used for preprocessing the combined brain wave signal to obtain a preprocessed brain wave signal; The first analysis module is used to analyze the preprocessed brain wave signal to obtain the initial analysis result.

9. The device according to claim 7, wherein: The health analysis module includes: A first sending module, configured to send the initial analysis result to a preset platform, wherein the preset platform has a target authority granted by the object to be tested, and the target authority at least includes an authority to obtain the object information and an authority to obtain the initial analysis result; The second analysis module is used to obtain a target analysis result obtained by the preset platform analyzing the object information of the object to be tested and the initial analysis result.

10. The device according to claim 9, further comprising: The first acquisition module is used to obtain the health management strategy generated by the preset platform based on the object information of the object to be tested and the initial analysis result when the target analysis result indicates that the health status of the object to be tested is in an abnormal state.

11. The device according to claim 10, further comprising: The second sending module is used to send the initial analysis result and / or the health management strategy to a target terminal device, and display the initial analysis result and / or the health management strategy in a visual form in the target terminal device.

12. The device according to claim 8, wherein: The preprocessing module comprises: A denoising module, used for denoising the combined brain wave signal to obtain a denoised brain wave signal; A segmentation module, used to segment the denoised brain wave signal according to preset time periods to obtain brain wave signals corresponding to multiple time periods; A conversion module, used for converting the brain wave signals corresponding to the multiple time periods into digital signals to obtain converted brain wave signals; A correction module, used for performing baseline correction on the converted brain wave signal to obtain a corrected brain wave signal; The first processing module is used to perform averaging processing on the corrected brain wave signal to obtain the pre-processed brain wave signal.

13. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the method for analyzing brain wave signals according to any one of claims 1 to 6.

14. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause a computer to execute the electroencephalogram signal analysis method according to any one of claims 1 to 6. 15 . A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method for analyzing an electroencephalogram signal according to claim 1 .

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