A method and system for compressing electroencephalogram data, a storage medium and a processor

Abstract

The application is suitable for the technical field of electroencephalogram data transmission, and provides an electroencephalogram data compression method and system, a storage medium and a processor, wherein the method uses fewer data bits to represent the time of action potential occurrence and the channel position of action potential firing. Specifically, the original electroencephalogram data is subjected to analog-digital conversion, the data code value is preprocessed into a new value through a relative average value, and then the new value is compressed in a similar normalization manner based on a compression threshold value. When 128-channel data or even more channel data is collected each time, the wireless data transmission pressure can be effectively reduced; the Bluetooth load rate is reduced, the current consumption in the Bluetooth transmission process is reduced, data loss caused by Bluetooth at the full transmission rate is avoided, and the wireless transmission efficiency of electroencephalogram data is effectively improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of electroencephalogram data transmission, and particularly relates to a compression method and system for electroencephalogram data, a storage medium and a processor. BACKGROUND

[0002] At present, in the motor imagery decoding of brain-computer interface, the action potential (AP) signal or the field potential signal can be used to represent the electroencephalogram information. The spike potential is the main component of the action potential (AP), and the duration of the spike potential is about 1 ms. If the spike potential is detected, the currently mainstream sampling frequency is above 10,000 Hz per second. The currently mature electrode array of brain-computer interface has reached 128 channels, or even above 1,000 channels. If the collected signals are transmitted to the host computer, a considerable amount of data transmission will be caused. The wired transmission is not conducive to the research on free-moving animals in an open environment, and the signal transmission system using Bluetooth is difficult to simultaneously solve the problems of low power consumption and high-speed transmission. The prior art has defects. SUMMARY

[0003] The application aims to provide a compression method and system for electroencephalogram data, a storage medium and a processor, and aims to solve the technical problem that it is difficult to simultaneously solve the problems of low power consumption and high-speed transmission due to the wireless transmission of electroencephalogram data in the prior art.

[0004] In one aspect, the application provides a compression method for electroencephalogram data, which comprises the following steps:

[0005] s1. In each sampling period, sequentially collecting the electroencephalogram raw data according to the channel order of the electroencephalogram acquisition device; and setting a corresponding time stamp for each period;

[0006] s2. sequentially performing analog-to-digital conversion on the electroencephalogram raw data of each channel to obtain the data code value of the channel;

[0007] s3. calculating the relative average value of the data code value, and the difference between the data code value and the relative average value being a new value corresponding to the data code value;

[0008] s4. calculating the difference between the new value and the compression threshold value to determine the compression value corresponding to the data code value, wherein when the difference value is greater than or equal to 0, the compression value is 1, and when the difference value is less than 0, the compression value is 0;

[0009] s5. grouping all the compression values according to the corresponding channel order to form the compression data of the sampling period, and sending the compression data to the host computer after adding the time stamp, the new value and the compression threshold value.

[0010] In another aspect, the application also provides a compression system for electroencephalogram data, which adopts any of the methods described above, and the system comprises:

[0011] a data acquisition module for acquiring raw electroencephalogram data through an electroencephalogram acquisition chip; a corresponding time stamp is set for each acquisition cycle;

[0012] an analog-digital conversion module for performing analog-digital conversion on the acquired raw electroencephalogram data to obtain corresponding data code values;

[0013] a data preprocessing module for calculating a relative average value of the data code values, wherein the difference between the data code values and the relative average value is a new value corresponding to the data code values;

[0014] a data compression module for calculating the difference between the new value and a compression threshold value to determine a compression value corresponding to the data code values, wherein when the difference value is greater than or equal to 0, the compression value is 1, and when the difference value is less than 0, the compression value is 0;

[0015] a data packaging module for grouping all compression values in the order of corresponding channels to form compression data for the sampling cycle, and sending the compression data to a host computer after adding the time stamp, the new value and the compression threshold value.

[0016] In another aspect, the application also provides a storage medium storing a program file capable of implementing the compression method for electroencephalogram data described above.

[0017] In another aspect, the application also provides a processor for running a program, wherein the program performs the compression method for electroencephalogram data described above when running.

[0018] The application is mainly used for detecting the peak potential of electroencephalogram signals, and uses fewer data bits to represent the time of action potential occurrence and the channel position of action potential firing.

[0019] Specifically, the application performs analog-digital conversion on raw electroencephalogram data, pre-processes the data code values into new values through a relative average value, and then compresses the new values in a normalized manner based on a compression threshold value. Compared with the prior art which needs 2-3 bytes to store the data of one channel, the application only needs one bit to store the data of one channel. This can effectively reduce the pressure of wireless data transmission when collecting 128-channel data or even more channel data each time, reduce the Bluetooth load rate, reduce the current consumption in the Bluetooth transmission process, avoid data loss caused by Bluetooth at full transmission rate, and effectively improve the efficiency of wireless data transmission.

[0020] Meanwhile, the amount of compressed data also enables the Bluetooth chip to upload electroencephalogram data to the host computer with the smallest load current, thereby achieving the technical effect of prolonging the service life of the electroencephalogram acquisition chip. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating the method for compressing electroencephalogram (EEG) data provided in Embodiment 1 of this application;

[0022] Figure 2 This is a schematic diagram of the structure of the EEG data compression system provided in Embodiment 2 of this application. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0024] The specific implementation of this application will be described in detail below with reference to specific embodiments:

[0025] Example One

[0026] Figure 1 The implementation flow of the EEG data compression method provided in Embodiment 1 of this application is illustrated. For ease of explanation, only the parts related to the embodiments of this application are shown, and are described in detail below:

[0027] On the one hand, this application provides a method for compressing electroencephalogram (EEG) data, the method comprising the following steps:

[0028] s1. In each sampling cycle, raw EEG data is sequentially acquired according to the acquisition channel order of the EEG acquisition device; a corresponding timestamp is set for each cycle;

[0029] s2. Perform analog-to-digital conversion on the raw EEG data of each channel sequentially to obtain the data code value of that channel;

[0030] s3. Calculate the relative average value of the data code value. The difference between the data code value and the relative average value is the new value corresponding to the data code value.

[0031] The calculation process for the new value is represented as follows:

[0032] Among them, V ave V represents the relative average value; new Indicates the new value; v1 represents the data code value of channel 1; n represents the number of channels; i represents the current channel number;

[0033] s4. Calculate the difference between the new value and the compression threshold to determine the compression value corresponding to the data code value. When the difference is greater than or equal to 0, the compression value is 1; when the difference is less than 0, the compression value is 0.

[0034] The calculation process for the compression value is expressed as follows:

[0035] V threshold represents a compression threshold value;

[0036] s5. All compression values are grouped into compression data of the sampling period according to the corresponding channel order, and are sent to the host computer after adding a timestamp, a new value and a compression threshold value.

[0037] Further, the relative average value is obtained by summing the data code values of all channels in a period and then dividing the sum by the number of channels.

[0038] In a specific implementation, the relative average value obtained in this way does not need to consider the data code values of other periods, which is more computationally efficient for the electroencephalogram acquisition device.

[0039] Further, the relative average value is obtained by summing the data code values of one channel in multiple periods and then dividing the sum by the number of periods.

[0040] In this embodiment, the relative average value is calculated using the data code values of the same channel in multiple periods, and the relative average value is more relevant to the data of the channel. The calculated new value can more accurately reflect the trend of the data code values of the channel.

[0041] Further, the compression threshold value is greater than or equal to the average of all new values in a period, and is less than the maximum value of the new values in a period. Preferably, the compression threshold value is the sum of 60% of the difference between the maximum value of the new values and the average of the new values and the average of the new values.

[0042] Further, the compression threshold value is preset by the host computer according to the field potential of the electroencephalogram raw data.

[0043] In this embodiment, since the host computer already knows the compression threshold value, the electroencephalogram acquisition device does not need to upload the compression threshold value in step s5.

[0044] Further, the compression data is in units of bits, and each bit stores a compression value.

[0045] The present application is mainly used for detecting the peak potential of the electroencephalogram signal, and uses fewer data bits to represent the time of the occurrence of the action potential and the channel position of the action potential.

[0046] Specifically, the electroencephalogram signal generally exists in the form of waves, wherein a series of connected waveforms with an average amplitude are field potential waveforms, and a wave peak with a high amplitude can be obviously distinguished from the field potential waveforms and is called an action potential waveform. The peak potential, as the most prominent part of the action potential, is the main component of the action potential (AP).

[0047] The present application is based on the analog-digital conversion of the raw electroencephalogram data. The electroencephalogram data is converted into specific numerical values, i.e. data code values. The data code values are preprocessed into new values by the relative average values. The difference between the action potential waveform and the field potential waveform in the analog signal can be highlighted. The new values are compressed by the compression threshold value, which is similar to normalization. The peak potential in the action potential can be effectively extracted without occupying too much storage space.

[0048] Compared with the prior art, the data of one channel only needs one bit to store. The wireless data transmission pressure of 128 channels of data or even more channels of data collected each time can be effectively reduced, the Bluetooth load rate is reduced, the current consumption in the Bluetooth transmission process is reduced, data loss caused by the Bluetooth at the full transmission rate is avoided, and the wireless data transmission efficiency is effectively improved.

[0049] At the same time, the compressed data amount also enables the Bluetooth chip to upload the electroencephalogram data to the host computer with the smallest load current, thereby achieving the technical effect of prolonging the service life of the electroencephalogram acquisition chip.

[0050] Example Two

[0051] The present application also provides an electroencephalogram data compression system, which adopts any one of the above methods. The system comprises:

[0052] A data acquisition module acquires raw electroencephalogram data through an electroencephalogram acquisition chip; a corresponding time stamp is set for each acquisition period;

[0053] An analog-digital conversion module performs analog-digital conversion on the acquired raw electroencephalogram data to obtain corresponding data code values;

[0054] A data preprocessing module calculates the relative average value of the data code values, and the difference between the data code values and the relative average value is the new value corresponding to the data code value;

[0055] A data compression module calculates the difference between the new value and the compression threshold value to determine the compression value corresponding to the data code value. When the difference value is greater than or equal to 0, the compression value is 1; and when the difference value is less than 0, the compression value is 0;

[0056] A data packaging module groups all the compression values into compression data of the sampling period in the corresponding channel order, and sends the compression data to the host computer after adding the time stamp, the new value and the compression threshold value.

[0057] Further, the number of acquisition channels of the electroencephalogram acquisition chip is greater than or equal to 128; and the data packaging module is based on the wireless transmission between the Bluetooth and the host computer. The compression system adopting the compression method also has the technical effects of the compression method.

[0058] Example Three

[0059] In another aspect, the present application also provides a storage medium, which stores a program file capable of implementing the above EEG data compression method.

[0060] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiment methods can be completed by instructing relevant hardware through programs, and the programs can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc.

[0061] Example Four

[0062] In another aspect, the present application also provides a processor for running a program, wherein the program performs the above EEG data compression method when running.

[0063] In the embodiments of the present application, the EEG data compression method can be implemented by corresponding hardware or software units, each unit can be an independent software or hardware unit, or can be integrated into a software or hardware unit, which does not limit the present application. The specific implementation of each unit can refer to the description of the first embodiment, which will not be repeated here.

[0064] The above only describes the preferred embodiments of the present application and does not limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for compressing electroencephalogram (EEG) data, characterized in that, The method includes the following steps: s1. In each sampling cycle, raw EEG data is sequentially acquired according to the acquisition channel order of the EEG acquisition device; a corresponding timestamp is set for each cycle; s2. Perform analog-to-digital conversion on the raw EEG data of each channel sequentially to obtain the data code value of that channel; s3. Calculate the relative average value of the data code value, and the difference between the data code value and the relative average value is the new value corresponding to the data code value; s4. Calculate the difference between the new value and the compression threshold to determine the compression value corresponding to the data code value. When the difference is greater than or equal to 0, the compression value is 1; when the difference is less than 0, the compression value is 0. s5. Arrange all compressed values ​​in the corresponding channel order to form compressed data for the sampling period, add the timestamp, the new value and the compression threshold, and then send it to the host computer.

2. The compression method as described in claim 1, characterized in that, The relative average value is obtained by summing the data code values ​​corresponding to all channels within one period and then dividing by the number of channels.

3. The compression method as described in claim 1, characterized in that, The relative average value is obtained by summing the data code values ​​corresponding to a channel within multiple cycles and then dividing by the number of cycles.

4. The compression method as described in claim 1, characterized in that, The compression threshold is greater than or equal to the average of all new values ​​within a period, and less than the maximum value of new values ​​within a period.

5. The compression method as described in claim 1, characterized in that, The compression threshold is preset by the host computer based on the field potential of the raw EEG data.

6. The compression method as described in claim 1, characterized in that, The compressed data is stored in bits, with each bit storing a compressed value.

7. A compression system for electroencephalogram (EEG) data, characterized in that, The system employs the method as described in any one of claims 1 to 6, characterized in that it comprises: The data acquisition module collects raw EEG data through an EEG acquisition chip; a corresponding timestamp is set for each acquisition cycle; The analog-to-digital conversion module performs analog-to-digital conversion on the collected raw EEG data to obtain the corresponding data code value; The data preprocessing module calculates the relative average value of the data code value, and the difference between the data code value and the relative average value is the new value corresponding to the data code value; The data compression module calculates the difference between the new value and the compression threshold to determine the compression value corresponding to the data code value. When the difference is greater than or equal to 0, the compression value is 1; when the difference is less than 0, the compression value is 0. The data packaging module assembles all the compressed values ​​into compressed data for the sampling period according to the corresponding channel order, adds the timestamp, the new value, and the compression threshold, and then sends it to the host computer.

8. The compression system as described in claim 7, characterized in that, The number of acquisition channels of the EEG acquisition chip is greater than or equal to 128; the data packaging module transmits wirelessly to the host computer via Bluetooth.

9. A storage medium, characterized in that, The storage medium stores a program file capable of implementing the method for compressing EEG data according to any one of claims 1 to 6.

10. A processor, characterized in that, The processor includes a module for performing the method for compressing EEG data according to any one of claims 1 to 6.

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