Questionnaire data synchronization method and system based on electroencephalogram equipment and browser

Abstract

The invention relates to the cross technical field of electroencephalogram signal processing and questionnaire investigation, and discloses a questionnaire data synchronization method and system based on an electroencephalogram device and a browser, and the method comprises the steps: connecting an EEG collection device with a browser end in real time; collecting time domain EEG signal data and operation events and timestamps corresponding to the operation events in real time when a user answers questionnaires; according to the operation event and the timestamp corresponding to the operation event, determining a time section of each question, and according to the obtained time sections, performing data division on the time domain EEG signal data to obtain time domain EEG signal data corresponding to each question; and performing data processing on the time domain EEG signal data corresponding to each question by using a fast Fourier transform algorithm to obtain frequency domain feature data corresponding to each question. According to the method, manual data export and timestamp alignment are not needed, the problems of tedious process and large error in the prior art are solved, and the data processing time is greatly saved.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of EEG signal processing and questionnaire surveys, and particularly to a method and system for synchronizing questionnaire data based on EEG devices and browsers. Background Technology

[0002] Electroencephalogram (EEG) signals contain rich information about brain activity and have significant applications in psychological experiments, emotion analysis, and cognitive state assessment. The conventional approach to combining EEG research with psychological experiments involves recording continuous time-domain signals using independent EEG acquisition software, then synchronizing these signals with stimulus presentations or behavioral events using timestamps. The specific process includes: first, acquiring continuous time-domain EEG signals using independent EEG acquisition software; then, recording the raw signals using dedicated software; exporting the recorded EEG data; processing the exported time-domain data offline; aligning the processed data with the stimulus presentation records or participant behavior logs from the experiment using timestamps; and finally, extracting frequency domain features from the aligned data to support subsequent analysis.

[0003] Although multimodal synchronous research exists in existing technologies, such research mainly focuses on the connection between EEG and specialized research equipment such as eye-tracking and electromyography, and does not involve direct linkage with user questionnaire response systems, resulting in the following significant shortcomings of existing technologies: EEG signals and questionnaire data cannot be linked in real time. Data needs to be manually exported and timestamps aligned, which is a cumbersome process and prone to human error. The lack of a mechanism to automatically segment EEG data based on the time period of each question's answer makes it impossible to accurately reflect the user's emotional or cognitive changes under different questions. At the same time, there is no data supplementation algorithm for the user's question-correction behavior, resulting in incomplete EEG analysis corresponding to the questions. The browser's real-time EEG processing capability is relatively weak. Performing high-frequency calculations such as Fast Fourier Transform (FFT) directly on the webpage can easily cause questionnaire lag, making it difficult to balance user experience and analysis accuracy. Most existing solutions rely on professional experimental environments or dedicated clients, making them impossible to deploy directly on general questionnaire platforms. Their application scenarios are limited, and the setup costs are high. Data collection requires participants to go to offline laboratories for cooperation. Summary of the Invention

[0004] This invention provides a method and system for synchronizing questionnaire data based on EEG devices and browsers, in order to solve the aforementioned technical problems in the prior art.

[0005] According to a first aspect of the present invention, a method for synchronizing questionnaire data based on EEG devices and browsers is provided.

[0006] The method for synchronizing questionnaire data between EEG devices and browsers includes: Connect the EEG acquisition device to the browser in real time; Real-time collection of time-domain EEG signal data and operation events, as well as the timestamps corresponding to the operation events, during user questionnaire responses; Based on the operation event and the timestamp corresponding to the operation event, the time segment of each question is determined, and the time domain EEG signal data is divided according to the obtained time segment to obtain the time domain EEG signal data corresponding to each question. The fast Fourier transform algorithm is used to process the time-domain EEG signal data corresponding to each question to obtain the frequency-domain feature data corresponding to each question.

[0007] In this process, the EEG acquisition device is connected to the browser in real time via WebSocket or WebUSB interface.

[0008] Furthermore, the aforementioned method for synchronizing questionnaire data between EEG devices and browsers also includes: Create a separate thread on the browser side and use this separate thread to perform asynchronous data processing on the time-domain EEG signal data; The asynchronous data processing includes: performing data segmentation processing on time-domain EEG signal data based on a predetermined time, and performing filtering and noise reduction processing on time-domain EEG signal data.

[0009] In addition, the aforementioned method for synchronizing questionnaire data between EEG devices and browsers also includes: Store the frequency domain feature data corresponding to each question, and visualize the questionnaire sentiment based on the frequency domain feature data corresponding to each question.

[0010] The visualization includes: band analysis display, sentiment trend display, and question behavior tracking display.

[0011] According to a second aspect of the present invention, a questionnaire data synchronization system based on EEG devices and browsers is provided.

[0012] The questionnaire data synchronization system based on EEG devices and browsers includes: The port connection unit is used to connect the EEG acquisition device to the browser in real time; The real-time acquisition unit is used to collect time-domain EEG signal data and operation events, as well as the timestamps corresponding to the operation events, when users answer questionnaires in real time. The data processing unit is used to determine the time segment of each question based on the operation event and the timestamp corresponding to the operation event, and to divide the time-domain EEG signal data according to the obtained time segment to obtain the time-domain EEG signal data corresponding to each question. The data synchronization unit is used to process the time-domain EEG signal data corresponding to each question using the Fast Fourier Transform algorithm to obtain the frequency-domain feature data corresponding to each question.

[0013] In this process, the EEG acquisition device is connected to the browser in real time via WebSocket or WebUSB interface.

[0014] In addition, the questionnaire data synchronization system based on EEG devices and browsers also includes: An asynchronous thread processing unit is used to create an independent thread on the browser side and use the independent thread to perform asynchronous data processing on time-domain EEG signal data; wherein, the asynchronous data processing includes: performing data segmentation processing on time-domain EEG signal data based on a predetermined time and filtering and denoising processing on time-domain EEG signal data.

[0015] In addition, the questionnaire data synchronization system based on EEG devices and browsers also includes: The visualization unit stores the frequency domain feature data corresponding to each question and visualizes the questionnaire sentiment based on the frequency domain feature data corresponding to each question.

[0016] The visualization includes: band analysis display, sentiment trend display, and question behavior tracking display.

[0017] The technical solution provided by this invention may include the following beneficial effects: By directly accessing EEG device data through the browser and combining behavioral event timestamps, the system achieves automatic segmentation of EEG data at the question level, eliminating the need for manual data export and timestamp alignment. This solves the problems of cumbersome processes and large errors in existing technologies, and significantly saves data processing time.

[0018] By processing time-domain data and FFT transformation asynchronously through an independent thread, high-frequency calculations are decoupled from real-time questionnaire responses, avoiding blocking of the browser's main thread, ensuring the smoothness of questionnaire responses for users, and guaranteeing the accuracy of frequency domain feature analysis, thus achieving a dual optimization of user experience and analysis results.

[0019] This invention does not require a professional laboratory environment or a dedicated client. It can directly complete the collection, caching, processing and synchronization of EEG data in the browser. It can be deployed on any online questionnaire platform. Participants only need to wear an EEG device and access the questionnaire through a browser to participate in the experiment. There is no need to go to an offline laboratory, which significantly reduces the application cost and scenario limitations.

[0020] By accurately mapping the EEG frequency domain characteristics of each question to the answering time, we can conduct in-depth analysis of users' emotional changes when answering questions, providing strong data support for scenarios such as psychological experiments, user experience evaluation, and cognitive state monitoring.

[0021] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0022] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0023] Figure 1 This is a flowchart illustrating a method for synchronizing questionnaire data between an EEG device and a browser, according to an exemplary embodiment. Figure 2 This is a structural block diagram illustrating a questionnaire data synchronization system based on an EEG device and a browser, according to an exemplary embodiment. Figure 3 This is a schematic diagram of the structure of a computer device according to an exemplary embodiment. Detailed Implementation

[0024] The following description and accompanying drawings fully illustrate specific embodiments described herein to enable those skilled in the art to practice them. Some embodiments may include or substitute parts and features of other embodiments. The scope of the embodiments herein encompasses the entire scope of the claims and all available equivalents thereof. Throughout this document, the terms “first,” “second,” etc., are used only to distinguish one element from another without requiring or implying any actual relationship or order between the elements. Indeed, a first element can also be referred to as a second element, and vice versa. Furthermore, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a structure, apparatus, or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a structure, apparatus, or device. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the structure, apparatus, or device that includes said element. The various embodiments described herein are presented in a progressive manner, with each embodiment focusing on its differences from other embodiments; similar or identical parts between embodiments can be referred to interchangeably.

[0025] The terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer" used in this document to indicate orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings. They are used solely for the convenience of describing the document and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In the description herein, unless otherwise specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to mechanical or electrical connections, or internal connections between two elements; they can be direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0026] In this document, unless otherwise stated, the term "multiple" means two or more.

[0027] In this article, the character " / " indicates that the objects before and after it are in an "or" relationship. For example, A / B means: A or B.

[0028] In this article, the term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0029] It should be understood that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order constraint on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the diagram may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0030] The modules in the apparatus or system of this application can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0031] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0032] Figure 1An embodiment of a questionnaire data synchronization method based on EEG devices and browsers according to the present invention is shown.

[0033] In this optional embodiment, the method for synchronizing questionnaire data between the EEG device and the browser includes: Step S101: Connect the EEG acquisition device to the browser in real time; Step S102: Real-time collection of time-domain EEG signal data and operation events, as well as the timestamps corresponding to the operation events, during the user's questionnaire answering process; Step S103: Based on the operation event and the timestamp corresponding to the operation event, determine the time segment of each question, and divide the time domain EEG signal data according to the obtained time segment to obtain the time domain EEG signal data corresponding to each question. Step S104: Use the Fast Fourier Transform algorithm to process the time-domain EEG signal data corresponding to each question to obtain the frequency-domain feature data corresponding to each question.

[0034] Figure 2 An embodiment of a questionnaire data synchronization system based on EEG devices and browsers according to the present invention is shown.

[0035] In this optional embodiment, the questionnaire data synchronization system based on EEG device and browser includes: The port connection unit 201 is used to connect the EEG acquisition device to the browser in real time; The real-time acquisition unit 202 is used to collect time-domain EEG signal data and operation events, as well as the timestamps corresponding to the operation events, when the user answers the questionnaire. The data processing unit 203 is used to determine the time segment of each question based on the operation event and the timestamp corresponding to the operation event, and to divide the time domain EEG signal data according to the obtained time segment to obtain the time domain EEG signal data corresponding to each question. The data synchronization unit 204 is used to process the time-domain EEG signal data corresponding to each question using the fast Fourier transform algorithm to obtain the frequency-domain feature data corresponding to each question.

[0036] In the above optional embodiments, the EEG acquisition device is connected to the browser in real time via a WebSocket or WebUSB interface. Furthermore, an independent thread is created on the browser side to perform asynchronous data processing on the time-domain EEG signal data. This asynchronous data processing includes: segmenting the time-domain EEG signal data based on a predetermined time interval, and filtering and denoising the time-domain EEG signal data. Simultaneously, the frequency domain feature data corresponding to each question is stored, and a questionnaire sentiment visualization is performed based on this frequency domain feature data. The visualization includes: band analysis display, sentiment trend display, and question behavior tracking display.

[0037] In practical applications, EEG acquisition equipment includes an EEG head-mounted device, acquisition sensors, amplifiers, and analog-to-digital converters. The EEG acquisition device transmits a time-domain EEG signal stream at a sampling rate of 256 Hz (approximately 256 sampling points per second), while operational events include entering the questionnaire, starting to answer questions, submitting each question, and correcting questions.

[0038] During data processing, the browser caches continuous EEG time-domain data while simultaneously launching an independent thread to process the data asynchronously. This independent thread segments and preprocesses the time-domain data (filtering, denoising) to avoid blocking the main thread and improve the questionnaire's interactive experience.

[0039] The main thread receives EEG device data and uses the WebUSB / WebSocket interface to obtain the EEG string data stream. Each data item is stored in the browser's local cache array in real time. Every 2.5 seconds, an independent thread reads the local cached time-domain data and organizes it into an array using regular expressions. If there are missing data, the previous combination is used. The device itself filters out some noisy data, i.e., the missing data mentioned above. If data garbled characters or anomalies still occur, the data is supplemented with the previous normal data.

[0040] If necessary, data gain calibration can be performed on the preprocessed data to calibrate the voltage of the acquired EEG time-domain raw signal according to the sensor gain parameters. Specifically, this includes: calculating a uniform gain factor based on the sensor's voltage-to-digital conversion ratio and the amplifier system gain; multiplying the raw digital data by this gain factor to uniformly convert the signal units to microvolts; and eliminating the impact of hardware gain differences on subsequent analysis through calibration, thus giving the spectral characteristics practical physical meaning.

[0041] During data transformation, a fixed window length of 512 points is used. For each time-domain point, the first 511 points are taken to calculate the frequency domain data for that point, and a Fast Fourier Transform (FFT) is used to convert it into data for each band. The calculated frequency domain data is stored. When answering the questionnaire, data is extracted from the processed frequency domain data. If there is unprocessed time-domain data in the original data, the remaining time-domain data is first converted into frequency domain data before extraction. At the final submission, this frequency domain data is organized into the expected value and variance for each band. The publisher can subsequently use the expected value and variance to judge the respondent's focus and emotional state during questionnaire responses.

[0042] When performing visualized emotion analysis and display based on the frequency domain characteristic data corresponding to each topic, the emotional states corresponding to the wavebands can be as follows: Delta waves (1~3Hz) usually appear during deep sleep or unconscious states. Theta waves (4~7Hz) usually appear during deep physical relaxation, drowsiness, or mental confusion. Alpha-Low waves (8~9Hz) usually appear before falling asleep, with a blank mind and blurred consciousness. Alpha-Mid waves (9~12Hz) usually appear when awake, quiet, and relaxed. In this state, physical and mental energy consumption is minimal, which is conducive to the emergence of inspiration. Alpha-High waves (12~14Hz) usually appear when highly alert and unable to focus on anything else. Beta-Low waves (12.5~16Hz) usually appear when relaxed and focused. Beta-Mid waves (16.5~20Hz) usually appear when thinking or processing external information, with focused attention. Beta-high waves (20.5~28Hz) typically occur during periods of tension, excitement, or anxiety, and can deplete physical and mental energy, leading to fatigue. Gamma waves (above 28Hz) typically occur when engaging in extremely difficult tasks, maintaining high concentration, or in a meditative state.

[0043] To better understand the above-mentioned technical solutions of the present invention, the following detailed description of the above-mentioned technical solutions of the present invention is provided in conjunction with specific operating procedures and equipment parameters.

[0044] 1) Equipment Requirements EEG Device: Must support Bluetooth Low Energy 5.0 communication protocol; Device parameters: Minimum detection signal: 0.25uV; Static current consumption: <10uA, Total operating current: <700uA; Input signal range: 1uV~5mV; Input impedance: >3,000,000 ohms; Common-mode rejection: >75dB; Amplification factor: 256 (adaptive adjustment range 32~1024); Analog-to-digital conversion: 24-bit Delta-Sigma ADC; Sampling frequency: 256 SPS; Frequency response: 0.4Hz~40Hz (error less than 3dB); Gain accuracy: >98%, Gain stability: >99%; Timing accuracy: 24-hour operating error less than 2 seconds; Power supply: CR2032 battery, equipped with replaceable electrode patches.

[0045] (II) Implementation Steps Questionnaire distribution configuration: In the "External data source settings" of the questionnaire platform, the questionnaire publisher should check "Enable EEG (electroencephalogram) signal source". After the configuration is completed, only subjects with authorized EEG devices can answer the questionnaire. User preparation: When a user opens the questionnaire webpage, the system prompts "Do you have an EEG brainwave device authorized by Credamo?" The user clicks "I have" to enter the device connection process; Device Connection: Turn on the EEG device and insert the Bluetooth receiver into the terminal device (computer); find the device ID (e.g., "0070AA") on the EEG device, enter the device ID in the questionnaire webpage, select the "serial connection" method, and click "confirm"; the system prompts "Do you want to connect to the serial port (USB serial device COM3)?", click "connect" to complete the device binding; Device test: The user taps their forehead. If the EEG data displayed on the webpage changes drastically, it means the connection is successful. Click "Start Answering" to start EEG data recording. Questionnaire completion: After viewing the optional emotion activation materials, users begin to answer the questionnaire. The system records the operation timestamp and corresponding EEG data for each question in real time, and an independent thread performs data preprocessing and frequency domain conversion synchronously. If the subject changes the question, the system automatically records the EEG data for the time period of the change. Data collection: After the questionnaire is completed, the data is automatically synchronized to the platform database; Data Download: Questionnaire publishers go to the "Data Cleaning" page on the platform, click "Variable Settings, Synchronize Variables" to update the EEG data file to the download list; go to the "Data Preview" page, check "Include EEG data for each question", and click "Download Data" to obtain a file containing questionnaire answers and corresponding EEG frequency domain data (supports XLS, CSV, and SAV formats).

[0046] Figure 3 An embodiment of a computer device according to the present invention is shown. The computer device may be a server, and includes a processor, memory, and a network interface connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device stores static and dynamic information data. The network interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the steps in the above-described method embodiment.

[0047] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device to which the present invention is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0048] In addition, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0049] In addition, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0050] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0051] This invention is not limited to the structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this invention is limited only by the appended claims.

Claims

1. A method for synchronizing questionnaire data based on electroencephalographic device and browser, characterized in that, The method comprises the following steps: real-time connection between the EEG acquisition device and the browser end; real-time acquisition of time-domain EEG signal data and operation events of the user when answering the questionnaire, and time stamps corresponding to the operation events; determination of the time segment of each question according to the operation events and the time stamps corresponding to the operation events, and data division of the time-domain EEG signal data according to the obtained time segment to obtain time-domain EEG signal data corresponding to each question; data processing of the time-domain EEG signal data corresponding to each question by using a fast Fourier transform algorithm to obtain frequency domain feature data corresponding to each question.

2. The electroencephalography device and browser based questionnaire data synchronization method of claim 1, wherein, The EEG acquisition device is connected to the browser end in real time through a WebSocket or WebUSB interface. 3.The method of synchronizing EEG-based device and browser-based questionnaire data according to claim 1, wherein, Further comprising: creating an independent thread on the browser end, and using the independent thread to perform asynchronous data processing on the time-domain EEG signal data; wherein the asynchronous data processing comprises data segmentation processing of the time-domain EEG signal data based on a predetermined time, and filtering and denoising processing of the time-domain EEG signal data.

4. The electroencephalography device and browser based questionnaire data synchronization method of claim 1, wherein, Further comprising: storing the frequency domain feature data corresponding to each question, and performing visualized display of questionnaire emotions based on the frequency domain feature data corresponding to each question.

5. The electroencephalography device and browser based questionnaire data synchronization method of claim 4, wherein, The visualized display comprises wave band analysis display, emotion trend display, and question behavior tracking display.

6. A brain electrical device and browser based questionnaire data synchronization system, characterized in that, The method comprises the following steps: port connection unit for real-time connection between the EEG acquisition device and the browser end; real-time acquisition unit for real-time acquisition of time-domain EEG signal data and operation events of the user when answering the questionnaire, and time stamps corresponding to the operation events; data processing unit for determining the time segment of each question according to the operation events and the time stamps corresponding to the operation events, and performing data division of the time-domain EEG signal data according to the obtained time segment to obtain time-domain EEG signal data corresponding to each question; data synchronization unit for data processing of the time-domain EEG signal data corresponding to each question by using a fast Fourier transform algorithm to obtain frequency domain feature data corresponding to each question.

7. The electroencephalography device and browser based questionnaire data synchronization system of claim 6, wherein, The EEG acquisition device is connected to the browser end in real time through a WebSocket or WebUSB interface.

8. The electroencephalography device and browser based questionnaire data synchronization system of claim 6, wherein, Further comprising: thread asynchronous processing unit for creating an independent thread on the browser end, and using the independent thread to perform asynchronous data processing on the time-domain EEG signal data; wherein the asynchronous data processing comprises data segmentation processing of the time-domain EEG signal data based on a predetermined time, and filtering and denoising processing of the time-domain EEG signal data.

9. The electroencephalography device and browser based questionnaire data synchronization system of claim 6, wherein, Further comprising: visualization display unit for storing the frequency domain feature data corresponding to each question, and performing visualized display of questionnaire emotions based on the frequency domain feature data corresponding to each question.

10. The electroencephalography device and browser based questionnaire data synchronization system of claim 9, wherein, The visualized display comprises wave band analysis display, emotion trend display, and question behavior tracking display.

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