System and method for reducing power consumption of electroencephalogram acquisition equipment

Abstract

The invention discloses a system and a method for reducing power consumption of electroencephalogram acquisition equipment. The system comprises a visual stimulation module, a label synchronization module, an electroencephalogram signal classification module and an upper computer module, the system further comprises a low-power-consumption electroencephalogram acquisition module, the low-power-consumption electroencephalogram acquisition module completes acquisition and wireless transmission of electroencephalogram signals in a multi-core awakening working mode, and in the multi-core awakening working mode, time parameters including wireless communication connection intervals are calculated and set, so that the real-time performance and integrity of data are ensured; wherein the low-power-consumption electroencephalogram acquisition module is composed of an electroencephalogram acquisition electrode unit, an analog acquisition front-end unit, a master control and wireless transmission chip unit, a first clock, a second clock and a power management unit, and the master control and wireless transmission chip unit is composed of a main processor, a radio frequency processor and a coprocessor. The power consumption of the wearable electroencephalogram machine is reduced, and the endurance of the electroencephalogram machine under a small-capacity battery is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of electroencephalogram (EEG) signal acquisition, and in particular to a system and method for reducing power consumption of an EEG acquisition device. Background Art

[0002] Brain-Computer Interface (BCI) is a system that directly converts central nervous system activity into artificial output. It can replace, repair, enhance, supplement or improve the normal output of the central nervous system, thereby improving the interaction between the central nervous system and the internal and external environment. A typical brain-computer interface system includes four parts: signal acquisition, signal processing, control equipment and feedback link. As the main part of the brain-computer interface, the EEG signal acquisition system has become a hot topic in current instrument science. At present, there are many EEG signal mapping technologies such as electroencephalography, magnetoencephalography, and near-infrared spectroscopy. Among them, electroencephalography (EEG) is a non-invasive method to measure brain electrical activity.

[0003] Wearable EEG devices are the research focus of EEG devices. They integrate amplifiers, analog-to-digital converters, and wireless transceivers to collect signals in real time. Wireless EEG acquisition devices have long battery life and portable design requirements. Long battery life means that the device can continue to work for a long time without frequent charging, which is crucial for application scenarios that require long-term monitoring of EEG activity. However, in order to meet the needs of long battery life, most existing wireless EEG machines use large-capacity lithium batteries as power sources. Although large-capacity lithium batteries can provide enough energy to support long-term EEG acquisition, this also brings about the problem of increased device size. Large-capacity lithium batteries are usually large in size and weight, which causes the volume of the entire EEG machine to increase, thereby reducing the portability of the device. Summary of the invention

[0004] In view of the difficulties in the prior art, the present invention provides a method for reducing the power consumption of EEG acquisition equipment. This method aims at the current situation that traditional EEG acquisition equipment usually relies on large-capacity batteries to ensure the continuous operation of the equipment, and solves the problem that traditional EEG acquisition equipment is large in size, which limits its portability and application scenarios. The present invention studies the key technologies of low-power EEG acquisition equipment, and proposes a method for EEG acquisition equipment to reduce power consumption by using hetero-core communication. Based on the proposed method and the low-power Bluetooth communication protocol, the present invention uses low-power chips to design low-power EEG acquisition equipment. The present invention is expected to reduce the power consumption of wearable EEG machines, enhance the battery life of EEG machines with small-capacity batteries, replace large-capacity and large-volume batteries to reduce the size of EEG machines, broaden the application scenarios, and provide a new design idea for the practical application of scalable multi-lead brain-computer interfaces.

[0005] In order to solve the problems of the prior art, the present invention adopts the following technical solutions:

[0006] A system for reducing the power consumption of an electroencephalogram (EEG) acquisition device, the system comprising a visual stimulation module, a label synchronization module, an electroencephalogram (EEG) signal classification module and a host computer module; the system further comprising a low-power EEG acquisition module, the low-power EEG acquisition module completes the acquisition and Bluetooth transmission of EEG signals through a multi-core wake-up working mode, and in the multi-core wake-up working mode, the time parameters including the Bluetooth communication connection interval are calculated and set; wherein: the low-power EEG acquisition module is composed of an EEG acquisition electrode unit, an analog acquisition front-end unit, a main control and Bluetooth transmission chip unit, a first clock, a second clock and a power management unit; the analog acquisition front-end unit amplifies, samples and performs AD conversion processing on the EEG signal transmitted by the EEG acquisition electrode unit; the main control and Bluetooth transmission chip caches and transmits the EEG type digital signal transmitted by the analog acquisition front-end unit, and completes the calculation and setting of the time parameters in the multi-core wake-up working mode; the power management unit is used to supply power to the low-power EEG acquisition module; wherein: the main control and Bluetooth transmission chip unit is composed of a main processor, a radio frequency processor and a coprocessor, including:

[0007] The main processor manages the Bluetooth protocol and EEG acquisition tasks, and completes the calculation and setting of time parameters in the multi-core wake-up work;

[0008] The coprocessor interacts with the analog acquisition front-end unit in an ultra-low power consumption manner, controls the EEG acquisition task, and realizes the initialization and data transmission of the analog acquisition front-end unit;

[0009] The radio frequency processor completes the Bluetooth transmission task and transmits the data collected by the coprocessor through the underlying Bluetooth communication task.

[0010] Furthermore, the low-power EEG acquisition module completes the calculation and setting process of time parameters including the acquisition of EEG signals and the communication connection interval sent by Bluetooth through a multi-core wake-up working mode, including:

[0011] Step 201. Select a low power consumption EEG acquisition module sampling rate of Fs;

[0012] Step 202. The main processor obtains the connection interval T through the following formula during the initialization of the main control and Bluetooth transmission chip units;

[0013] T=t1+t2=7.5+1.25×α(ms) (1)

[0014] Where α is an unknown number, t1 is 7.5ms, which represents the minimum connection interval specified by the Bluetooth protocol, and t2 is 1.25×α, which is the calculation step size. The two addends in the formula are both integer multiples of 1.25ms, which meets the requirement of the Bluetooth protocol that the Bluetooth connection interval time is an integer multiple of 1.25ms;

[0015] For α, when the sampling rate is Fs, (t1+t2)×F s is an integer, that is

[0016]

[0017] Step 203: The main processor sets the coprocessor cache threshold N=T×Fs during the initialization of the main control and Bluetooth transmission chip units;

[0018] Step 204: The RF processor completes the establishment of a connection with the Bluetooth host during Bluetooth communication initialization;

[0019] Step 205: The RF processor modifies the connection interval with the Bluetooth host to T in the Bluetooth connection determination;

[0020] Step 206: After the connection interval is modified to 1 / Fs / 10, the coprocessor controls the EEG acquisition task to start executing.

[0021] Furthermore, the first clock is a 24 MHz crystal oscillator; the second clock is a 32.768 KHz crystal oscillator.

[0022] The present invention can also adopt the following technical solutions:

[0023] A method for reducing power consumption of an electroencephalogram (EEG) acquisition device, comprising:

[0024] Step 101: The main processor initializes the main control and Bluetooth transmission chip units;

[0025] Step 102: The radio frequency processor initializes Bluetooth communication;

[0026] Step 103: After the master control unit and the Bluetooth transmission chip unit are initialized and the communication is initialized, wait for the Bluetooth communication connection to be established;

[0027] After the Bluetooth connection is confirmed in step 104, the main processor and the radio frequency processor are in sleep mode;

[0028] Step 105: The coprocessor initializes the analog acquisition front-end unit, configures acquisition parameters, and controls the EEG acquisition task;

[0029] Step 106: After the EEG acquisition task is started, wait for the analog acquisition front-end unit to acquire data at the sampling point;

[0030] Step 107: The coprocessor periodically reads and caches the data of the analog acquisition front-end unit;

[0031] Step 108 waits for the data in the coprocessor cache to reach the cache threshold;

[0032] Step 109: When the amount of data cached by the coprocessor reaches a data threshold N, the main processor is awakened;

[0033] Step 110: The main processor wakes up the Bluetooth transmission task, that is, wakes up the radio frequency processor, and then the main processor enters the sleep mode again;

[0034] Step 111: The radio frequency processor sends the collected EEG data via Bluetooth and enters sleep mode after the data transmission is completed;

[0035] When the coprocessor cache data reaches a predetermined threshold, steps (106) to (111) are repeated and executed cyclically.

[0036] In the step 109, after the data cached by the coprocessor is specified to be cached, during the process of waking up the main processor, the number of data cached in the coprocessor N and the two connection intervals T between the RF processor should satisfy the basic relationship of N=T×Fs, where the connection interval T is the interval between two Bluetooth communication parties for data transmission; the sampling rate Fs is the basis for selecting the connection interval T.

[0037] Beneficial Effects

[0038] Compared with the traditional technical solution, the beneficial effects brought by the present invention are:

[0039] 1. The multi-core wake-up method for EEG acquisition of the present invention designs a low-power EEG acquisition module, which can reduce the power consumption of the EEG acquisition module, thereby reducing the battery and overall volume of the EEG acquisition module.

[0040] 2. The present invention can collect EEG data with lower power consumption in the data collection stage and transmit EEG data via Bluetooth with lower power consumption in the TX stage. When the sampling rate of the EEG collection module is 1000Hz, the Bluetooth connection interval is 10ms, and the device is powered by a 45mAh battery, the working time of the device using this method is increased by about 80min compared to the device not using this method. At this time, the volume of the EEG collection module is less than 8cm 3 , total amount <8g.

[0041] 3. The low-power EEG acquisition module of the present invention is quick to wear, portable, and can meet the characteristics of long-term recording. It can solve the problem that traditional desktop EEG acquisition equipment often uses cap-type acquisition electrodes, is large in size, and is powered by AC power, and can only be used in laboratories; portable EEG equipment is relatively large in size and weight, and uses headbands, helmets and other fixing methods, which have poor confidentiality and wearability and are not easily accepted by consumers. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Multi-core wake-up system process for EEG acquisition;

[0043] Figure 2 Multi-core wake-up method based on CC2640R2F;

[0044] Figure 3 Low power consumption EEG acquisition module composition;

[0045] Figure 4 Calculation and setting of time parameters for multi-core wake-up system process;

[0046] Figure 5 Working current diagram of low power EEG acquisition module;

[0047] Figure 6 Diagram of the online experimental architecture of the low-power EEG acquisition system SSVEP. DETAILED DESCRIPTION

[0048] The following is combined with Figure 1 ~Attached Figure 6 The present invention is described as follows:

[0049] The present invention provides a module for reducing the power consumption of an electroencephalogram (EEG) acquisition device, and is designed for a multi-core wake-up system process for EEG acquisition. The low-power EEG acquisition module consists of an EEG acquisition electrode unit, an analog acquisition front-end unit, a main control and Bluetooth transmission chip unit, a first clock, a second clock, and a power management unit. The main processor serves as the control center of the main control and Bluetooth transmission chip unit and undertakes tasks such as system control. The coprocessor is independent of the main processor and undertakes the task of EEG signal acquisition. The radio frequency processor undertakes the task of Bluetooth data communication, wherein the main processor and the radio frequency processor are in a low-power consumption mode most of the time and are awakened only when necessary to perform key task processing. The coprocessor enters a low-power consumption mode when no signal acquisition is performed and is awakened only when EEG data needs to be acquired.

[0050] The specific work process is as follows: Figure 3 As shown:

[0051] The 101 module is powered on, and the main processor initializes the main control and Bluetooth transmission chip units;

[0052] 102. The radio frequency processor initializes Bluetooth communication;

[0053] 103. After the master control unit and the Bluetooth transmission chip unit are initialized and the communication is initialized, wait for the Bluetooth communication connection to be established;

[0054] 104. After the Bluetooth connection is confirmed, the main processor and the radio frequency processor go into sleep mode;

[0055] 105. The coprocessor initializes the analog acquisition front-end unit, configures acquisition parameters, and controls the EEG acquisition task;

[0056] 106. After the EEG acquisition task is started, wait for the analog acquisition front-end unit to collect data at the sampling point;

[0057] 107. The coprocessor periodically reads and caches the data of the analog acquisition front-end unit;

[0058] 108. Wait for the data in the coprocessor cache to reach the cache threshold;

[0059] 109. When the amount of data cached by the coprocessor reaches a data threshold N, the main processor is woken up;

[0060] 110. The main processor wakes up the Bluetooth sending task, that is, wakes up the RF processor, and then the main processor enters the sleep mode again;

[0061] 111. The RF processor sends the collected EEG data via Bluetooth and enters sleep mode after the data transmission is completed;

[0062] When the coprocessor cache data reaches a predetermined threshold, steps (106) to (111) are repeated and executed cyclically.

[0063] like Figure 1 , Figure 2 As shown, under the condition that the sampling rate of the low-power EEG acquisition module is Fs, that is, the sampling rate of the analog acquisition front-end unit in the low-power EEG acquisition module is Fs, the number of cached data N in the coprocessor and the two connection intervals T between the RF processor should satisfy the basic relationship of N=T×Fs, and the number of caches N should be the number of integer point acquisitions of Fs within T. For example, when Fs is 1000Hz, T can be any integer multiple of 1ms, such as 10ms. At this time, N is 10, but T cannot be 1.1ms. If T is 1.1ms, the sampling frequency and the cache interval will not match every 10ms, resulting in data loss. At the same time, the connection interval T affects the real-time Bluetooth transmission of the low-power EEG acquisition module data. For this reason, the patent specifies the selection of T based on the sampling rate Fs, and further specifies the selection of time-related parameters in the EEG acquisition multi-core wake-up system process.

[0064] The Bluetooth communication protocol stipulates that there should be a Bluetooth host and a Bluetooth slave during the Bluetooth communication process. After each connection interval, a connection event occurs between the Bluetooth host and the Bluetooth slave, completing a Bluetooth data sending task. In this system, the host computer module plays the role of the host, and the low-power EEG acquisition module plays the role of the slave. After a connection interval T, a connection event occurs, and the N data cached by the coprocessor in the low-power EEG acquisition module are sent to the host computer module.

[0065] At the same time, the Bluetooth protocol requires that when a single Bluetooth slave is connected, that is, there is a low-power EEG acquisition module connected to the host computer module in the system, the minimum value of the connection interval T is 7.5ms-17.5ms, and T should also be an integer multiple of 1.25ms. Usually, the Bluetooth connection interval T in the Bluetooth protocol is determined by negotiation between the two communicating parties. The real-time performance of the low-power EEG acquisition module expects the EEG acquisition module to send data once it completes the data. Therefore, in order to send the sampled data of the analog acquisition front-end module in time at different sampling rates Fs, the present invention designs a method for calculating the Bluetooth connection interval T, which provides a method for calculating the connection interval of the low-power EEG acquisition module at different sampling rates:

[0066] T=t1+t2=7.5+1.25×α(ms) (1)

[0067] In the formula, α is an unknown number, t1 is 7.5ms, which represents the minimum connection interval in the single slave case, t2 is 1.25×α, which is the calculation step. The two addends in the formula are both integer multiples of 1.25ms, which meets the requirement of the Bluetooth protocol that the Bluetooth connection interval time is an integer multiple of 1.25ms. The derivation formula of α is given below.

[0068] For α, when the sampling rate is Fs, (t1+t2)×F s is an integer, that is

[0069]

[0070] At the same time, because no user event, i.e., EEG acquisition task, can occur when a Bluetooth connection event occurs, the start time of the EEG acquisition task is set to 1 / Fs / 10 after the connection interval modification is completed, i.e., after the connection interval modification is completed 1 / Fs / 10, the analog acquisition front-end unit implements the first sampling. The method for selecting time-related parameters in the EEG acquisition multi-core wake-up system process specified in the present invention is applicable to the calculation of the connection interval in the low-power EEG acquisition module of the analog acquisition front-end unit at different sampling rates, and specifies the start time of the EEG acquisition task to ensure the real-time performance of the system. The specific process is as follows: Figure 4 As shown:

[0071] Step 201. Select a low power consumption EEG acquisition module sampling rate of Fs;

[0072] Step 202: The main processor derives the connection interval T by using formulas 1 and 2 during the initialization of the main control and Bluetooth transmission chip units;

[0073] Step 203: The main processor sets the coprocessor cache threshold N=T×Fs during the initialization of the main control and Bluetooth transmission chip units;

[0074] Step 204: The RF processor completes the establishment of a connection with the Bluetooth host during Bluetooth communication initialization;

[0075] Step 205: The RF processor modifies the connection interval with the Bluetooth host to T in the Bluetooth connection determination;

[0076] Step 206: After the connection interval is modified to 1 / Fs / 10, the coprocessor controls the EEG acquisition task to start executing.

[0077] When the analog acquisition front-end module works at a sampling rate of 1KHz, the main processor of the EEG acquisition module derives α as 2 through formula 2, and the calculation formula 1 of the Bluetooth connection interval is 10 (ms). The coprocessor of the EEG acquisition module starts the EEG acquisition task after the connection interval is modified by 0.1ms, and the number of caches is 10. When the analog acquisition front-end works at a sampling rate of 250Hz, the main processor of the EEG acquisition module derives α as 10 through formula 2, and the calculation formula 1 of the Bluetooth connection interval is 20 (ms). The coprocessor of the EEG acquisition module starts the EEG acquisition task after the connection interval is modified by 0.4ms, and the number of caches is 20.

[0078] If CC2640R2F is used as the main control and Bluetooth transmission chip, its main processor is the M3 core, the RF processor is the M0 core, and it has a coprocessor. The M3 core completes the calculation and setting of the time parameters in the multi-core wake-up workflow. When the coprocessor starts the EEG acquisition task, the M3 and M0 cores are in sleep mode, and most clock signals stop. At this time, only the 32.768KHz RTC low-power clock runs. The coprocessor works with this RTC clock. When the analog acquisition front end works at the set sampling rate, the coprocessor completes the acquisition and cache at each sampling point. When the storage threshold N is reached, an interrupt request is generated to wake up the M3 main processor. After receiving the interrupt request, the M3 processor clears the interrupt request flag, wakes up the M0 core to complete the Bluetooth data transmission, and then enters the sleep state again. This multi-core wake-up working mode eliminates the need for the M3 main processor and the M0 RF processor to run continuously, thereby reducing power consumption.

[0079] The proposed method of reducing the power consumption of EEG acquisition equipment is used to design a low-power EEG acquisition module to complete the acquisition and transmission of EEG signals. The module consists of EEG acquisition electrodes, analog acquisition front end, main control and Bluetooth transmission chip, power management unit, etc. The ADS1291 chip serves as the analog acquisition front end to complete the amplification, sampling and AD conversion of EEG signals. The CC2640R2F main control and Bluetooth transmission chip caches and transmits the EEG type digital signal transmitted by the analog acquisition front end ADS1291, and completes the calculation and setting of time parameters in the multi-core wake-up workflow. The 24MHz crystal oscillator and 32.768KHz crystal oscillator provide clocks for the chip. The LM27762 power management chip provides the chip working voltage. The MCP73831 completes battery charging.

[0080] Each low-power EEG acquisition module consists of a set of reference electrodes, active electrodes, and ground electrodes. The reference electrode and the active electrode are fixed with gold cup electrodes and Ten20 conductive paste. The reference electrode is fixed in the middle of the head, and the active electrode is placed in the occipital area of ​​the head. The ground electrode is fixed at the earlobe using an ear clip electrode. The EEG signal after the ground electrode suppresses part of the common-mode signal is connected to the preprocessing circuit in a differential manner through the reference electrode and the active electrode, filtered by the filter circuit, and connected to the ADS1291. The EEG signal after AD conversion by ADS1291 passes through CC2640R2F and uses Bluetooth communication to finally send the EEG signal to the host computer module for further processing in the host computer module.

[0081] At the same time, the low-power EEG acquisition module also has the function of input impedance detection, which helps users determine the contact between the EEG acquisition electrode and the human head. Whenever the EEG acquisition function and the input impedance detection function are switched, steps 104 and 105 will be performed, that is, the connection interval is updated once, and the analog acquisition front-end unit is reinitialized, so that the EEG acquisition task is executed after the connection interval is modified by 1 / Fs / 10. When the EEG acquisition module is in the EEG signal acquisition function, the differential input of ADS1291 comes from the external electrode. When it is in the input impedance detection function, ADS1291 generates a 250Hz, 6μA DC signal. At this time, the data collected by ADS1291 is calculated as the impedance of the contact between the acquisition electrode and the human body. The smaller this value is, the better the contact between the electrode and the human body.

[0082] This example designs a low-power EEG acquisition module for collecting EEG data. The acquisition circuit includes a low-power Bluetooth MCU for logic control and data transmission, a low-power controllable gain analog acquisition front-end chip for collecting EEG signals, a charge pump and LDO with positive and negative voltage output for providing power to each chip, and a lithium battery for powering the device; the low-power EEG acquisition module completes the acquisition and transmission of EEG signals, and is composed of EEG acquisition electrodes, an analog acquisition front-end, a main control and Bluetooth transmission chip, a power management unit, etc. The ADS1291 chip serves as the analog acquisition front-end to complete the amplification, sampling, and AD conversion of EEG signals. The CC2640F2F main control and Bluetooth transmission chip complete the transmission of EEG data and the calculation and setting of time parameters in the multi-core wake-up workflow. The 24MHz crystal oscillator and the 32.768KHz crystal oscillator provide clocks for the chip. The LM27762 power management chip provides the chip working voltage, and the MCP73831 completes battery charging.

[0083] During the EEG acquisition process, this EEG acquisition module acts as a Bluetooth slave device and communicates with the Bluetooth host device, i.e., the host computer module. T1 is the current during the EEG acquisition process, and T2 is the current during data transmission during a Bluetooth connection interval. T2 is divided into several small time periods, t2.1 is the module's real-time operating system wake-up, Bluetooth settings, and crystal oscillator protection time; t2.2 is the time when the module turns on the Bluetooth radio and sets it to receive mode; t2.3 is the time when the EEG acquisition module receives host data as a slave; t2.4 is the time when the module is converted from a radio frequency receiver to a device transmitter; t2.5 is the time when the module sends the collected EEG data to the host; t2.6 is the time when the module's Bluetooth protocol stack processes the received data packet and sets the sleep timer, and then enters the standby state.

[0084] Figure 5In the figure, G1 and G2 are time-current diagrams of the same EEG acquisition module without using / using the method of reducing EEG acquisition power consumption proposed in this patent. In the T1 stage, the M3 main processor performs the acquisition task in G1, and the M3 main processor sleeps in G2. The acquisition and caching of EEG data are completed by the coprocessor. By comparing the T1 stage currents in G1 and G2, it can be seen that lower power consumption can be achieved during the acquisition process based on this method. In the t2.5 stage, the M3 processor transmits the data to be sent to the M0 RF core. Based on this method, the main processor enters sleep after coordinating the acquisition and transmission time. If the EEG acquisition module adopts a sampling rate of 1000Hz and the Bluetooth transmission interval is 10ms, the EEG data to be sent cached by the coprocessor and the protocol header and tail of the Bluetooth protocol stack in this interval are 320 bits in total. When the transmission rate of Bluetooth transmission is 1Mbps, the time difference Δt between the M3 main processor entering the sleep state and the M0 core completing the data transmission is 320us. Comparing the currents at stage t2.5 in G1 and G2, it can be seen that this method can achieve lower power consumption during the EEG data transmission phase, and ultimately reduce the overall power consumption of the EEG acquisition module.

[0085] This example is a low-power EEG acquisition system used for SSVEP online experiments. In this example, it mainly includes five parts: visual stimulation module, label synchronization module, low-power EEG acquisition module, EEG signal classification module, and host computer module. The low-power EEG acquisition module is based on multi-core wake-up work and is used to complete the acquisition and transmission of EEG signals; the visual stimulation module is used for the presentation of visual stimulation; the label synchronization module is used for the alignment of EEG data and label data; the EEG signal classification module is used to realize EEG signal classification; the host computer module is used to provide users with the application of the low-power EEG acquisition system.

[0086] The low-power EEG acquisition module communicates with the host computer module via Bluetooth; the visual stimulation module, the label synchronization module, and the host computer module realize hardware serial communication through the USB port; and the EEG signal classification module communicates with the host computer module via TCP.

[0087] The SSVEP EEG experiment application scenario of the low-power EEG acquisition module refers to the visual stimulation module running stimulations of different frequencies. The host computer sends the EEG data collected by the low-power EEG acquisition module and the label data collected by the label synchronization module to the EEG signal classification module. After classification, it can identify the flicker frequency of the current stimulus and feedback the results to the user. The experimental architecture is as follows Figure 6 As shown, the specific process is as follows:

[0088] The visual stimulation module was set to an LCD display screen. Psychopy was used to display 40 stimulation blocks in 5 rows and 8 columns on the LCD display screen. The stimulation block frequency range was 10-18 Hz, and the stimulation block step was 0.2 Hz.

[0089] Open the low-power EEG acquisition module, open the host computer module, and select the sampling rate Fs of the EEG acquisition module;

[0090] Set the EEG acquisition module to impedance detection function, install EEG acquisition electrodes, and observe the impedance value at this time;

[0091] When the impedance drops below 10K, use the host computer module to switch the EEG acquisition module to the EEG acquisition function and run the visual stimulation module;

[0092] When the stimulus of a certain frequency of the visual stimulus module starts to flash, the stimulus tag will be written to the host computer module through the tag synchronization module;

[0093] The host computer module identifies the tag event type and parses the position in the EEG data when the visual stimulus module starts flashing;

[0094] The host computer module acts as a TCP server, and the EEG signal classification module acts as a TCP client to complete the TCP transmission of data between the two processes;

[0095] The classification module receives the data and completes the recognition, and stores the classification results in the result queue;

[0096] After the visual stimulus module flashes for a certain period of time, it stops flashing and waits for the classification result;

[0097] When there is data in the result queue, the stimulus display module takes out the results, displays them, and starts the next round of stimulation;

[0098] Although the present invention has been described above, the present invention is not limited to the above-mentioned specific embodiments. The above-mentioned specific embodiments are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can make many modifications without departing from the purpose of the present invention, which are all within the protection of the present invention.

Claims

1. A system for reducing power consumption of an EEG acquisition device, the system comprising a visual stimulation module, a label synchronization module, an EEG signal classification module and a host computer module; characterized in that: The system also includes a low-power EEG acquisition module, which completes the acquisition and Bluetooth transmission of EEG signals through a multi-core wake-up working mode. In the multi-core wake-up working mode, the time parameters including the Bluetooth communication connection interval are calculated and set; wherein: the low-power EEG acquisition module is composed of an EEG acquisition electrode unit, an analog acquisition front-end unit, a main control and Bluetooth transmission chip unit, a first clock, a second clock and a power management unit; the analog acquisition front-end unit amplifies, samples and AD converts the EEG signal transmitted by the EEG acquisition electrode unit; the main control and Bluetooth transmission chip caches and transmits the EEG type digital signal transmitted by the analog acquisition front-end unit, and completes the calculation and setting of the time parameters in the multi-core wake-up work; the power management unit is used to supply power to the low-power EEG acquisition module; wherein: the main control and Bluetooth transmission chip unit is composed of a main processor, a radio frequency processor and a coprocessor, including: The main processor manages the Bluetooth protocol and EEG acquisition tasks, and completes the calculation and setting of time parameters in the multi-core wake-up work; The coprocessor interacts with the analog acquisition front-end unit in an ultra-low power consumption manner, controls the EEG acquisition task, and realizes the initialization and data transmission of the analog acquisition front-end unit; The radio frequency processor completes the data Bluetooth transmission task and transmits the data collected by the coprocessor through the underlying Bluetooth communication task.

2. A system for reducing power consumption of an EEG acquisition device according to claim 1, characterized in that: The low-power EEG acquisition module completes the collection of EEG signals and the calculation and setting of time parameters including the communication connection interval sent by Bluetooth through a multi-core wake-up working mode, including: Step 201. Select a low power consumption EEG acquisition module sampling rate of Fs; Step 202. The main processor obtains the connection interval T through the following formula during the initialization of the main control and Bluetooth transmission chip units; T=t1+t2=7.5+1.25×α(ms) (1) Where α is an unknown number, t1 is 7.5ms, which represents the minimum connection interval specified by the Bluetooth protocol, and t2 is 1.25×α, which is the calculation step size. The two addends in the formula are both integer multiples of 1.25ms, which meets the requirement of the Bluetooth protocol that the Bluetooth connection interval time is an integer multiple of 1.25ms; For α, when the sampling rate is Fs, (t1+t2)×F s is an integer, that is Step 203: The main processor sets the coprocessor cache threshold N=T×Fs during the initialization of the main control and Bluetooth transmission chip units; Step 204: The RF processor completes the establishment of a connection with the Bluetooth host during Bluetooth communication initialization; Step 205: The RF processor modifies the connection interval with the Bluetooth host to T in the Bluetooth connection determination; Step 206: After the connection interval is modified to 1 / Fs / 10, the coprocessor controls the EEG acquisition task to start executing.

3. The system for reducing power consumption of an EEG acquisition device according to claim 1, characterized in that: The first clock is a 24MHz crystal oscillator; the second clock is a 32.768KHz crystal oscillator.

4. A method for reducing power consumption of an electroencephalogram (EEG) acquisition device, characterized in that: The method realizes the collection and transmission of EEG signals in a multi-core wake-up working mode based on the system according to any one of claims 1 to 3, comprising: Step 101: The main processor initializes the main control and Bluetooth transmission chip units; Step 102: The radio frequency processor initializes Bluetooth communication; Step 103: After the master control unit and the Bluetooth transmission chip unit are initialized and the communication is initialized, wait for the Bluetooth communication connection to be established; After the Bluetooth connection is confirmed in step 104, the main processor and the radio frequency processor are in sleep mode; Step 105: The coprocessor initializes the analog acquisition front-end unit, configures acquisition parameters, and controls the EEG acquisition task; Step 106: After the EEG acquisition task is started, wait for the analog acquisition front-end unit to acquire data at the sampling point; Step 107: The coprocessor periodically reads and caches the data of the analog acquisition front-end unit; Step 108 waits for the data in the coprocessor cache to reach the cache threshold; Step 109: When the amount of data cached by the coprocessor reaches a data threshold N, the main processor is awakened; Step 110: The main processor wakes up the Bluetooth transmission task, that is, wakes up the radio frequency processor, and then the main processor enters the sleep mode again; Step 111: The radio frequency processor sends the collected EEG data via Bluetooth and enters sleep mode after the data transmission is completed; When the coprocessor cache data reaches a predetermined threshold, steps (106) to (111) are repeated and executed cyclically.

5. The method for reducing power consumption of an electroencephalogram (EEG) acquisition device according to claim 4, characterized in that: In the step 109, after the data cached by the coprocessor is specified to be cached, during the process of waking up the main processor, the number of data cached in the coprocessor N and the two connection intervals T between the RF processor should satisfy the basic relationship of N=T×Fs, where the connection interval T is the interval between two Bluetooth communication parties for data transmission; the sampling rate Fs is the basis for selecting the connection interval T.

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