WO2019127559A1 - 一种高频射频干扰去除装置及方法 - Google Patents

一种高频射频干扰去除装置及方法 Download PDF

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WO2019127559A1
WO2019127559A1 PCT/CN2017/120370 CN2017120370W WO2019127559A1 WO 2019127559 A1 WO2019127559 A1 WO 2019127559A1 CN 2017120370 W CN2017120370 W CN 2017120370W WO 2019127559 A1 WO2019127559 A1 WO 2019127559A1
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signal
sub
eeg
threshold
detection threshold
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PCT/CN2017/120370
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English (en)
French (fr)
Inventor
张鹏
张宁玲
谢军华
金星亮
何先梁
叶志刚
罗汉源
李明
姚祖明
Original Assignee
深圳迈瑞生物医疗电子股份有限公司
深圳迈瑞科技有限公司
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Priority to CN201780085029.6A priority Critical patent/CN110290746B/zh
Priority to PCT/CN2017/120370 priority patent/WO2019127559A1/zh
Publication of WO2019127559A1 publication Critical patent/WO2019127559A1/zh
Priority to US16/916,050 priority patent/US11770146B2/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/06—Receivers
    • H04B1/10—Means associated with receiver for limiting or suppressing noise or interference
    • H04B1/1027—Means associated with receiver for limiting or suppressing noise or interference assessing signal quality or detecting noise/interference for the received signal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]

Definitions

  • the present invention relates to the field of medical device technologies, and in particular, to a high frequency radio frequency interference removing device and method.
  • the high-frequency electrosurgical knife (high-frequency scalpel) is an electrosurgical unit (ESU) that replaces a mechanical scalpel for tissue cutting. It is heated by the high-frequency and high-voltage signal generated by the effective electrode tip when it contacts the body. Separation and coagulation of the body tissue, which serves the purpose of cutting and stopping bleeding, and is increasingly used in clinical operations.
  • ESU electrosurgical unit
  • the high-frequency signal generated by the electric knife has a great influence on the physiological signal during the operation. This is the challenge of the current intraoperative monitoring. If the treatment is improper, the monitoring will be interrupted, or the wrong parameter value will be given, which will affect the doctor's judgment of the patient's state.
  • the current detection method for ESU high-frequency interference is mainly based on the frequency domain distribution difference between the interference and the physiological signal, designing the corresponding filter to remove the high-frequency interference signal, or giving the interference signal mark based on the frequency domain characteristic change;
  • Frequency domain analysis requires Fourier transform of the signal, which is computationally complex, resource intensive, and time consuming.
  • Embodiments of the present invention provide a high frequency radio frequency interference removing apparatus and method, which can remove high frequency radio frequency interference signals in an EEG signal.
  • an embodiment of the present invention provides a high frequency radio frequency interference removing apparatus, where the apparatus includes: a filtering unit, a high frequency signal extracting unit, a marking unit, an acquiring unit, and a processor, wherein
  • the filtering unit the input end of the filtering unit is connected to the original EEG signal, and is used for filtering the original EEG signal to obtain an intermediate EEG signal;
  • the high-frequency signal extracting unit is connected to an output end of the filtering unit for filtering the intermediate EEG signal to extract the intermediate EEG signal High frequency signal
  • the marking unit is connected to an output end of the high frequency signal extracting unit, configured to compare a magnitude of the high frequency signal with a magnitude of a comparison threshold, and compare the intermediate brain electrical signal according to the comparison result Classify the mark;
  • the collecting unit is connected to an output end of the filtering unit, and is configured to sample an intermediate EEG signal after the classification and marking to obtain an EEG signal, and input the EEG signal to the The processor;
  • the processor is configured to set a comparison threshold used by the marking unit, and control the collecting unit to sample the intermediate EEG signal;
  • the input end of the processor is connected to the output end of the collecting unit, the output end of the processor is connected to the input end of the marking unit, and the input end of the filtering unit is connected to the original brain electricity a signal, an output end of the filtering unit is connected to an input end of the high frequency signal extracting unit, an output end of the high frequency signal extracting unit is connected to the marking unit, an output end of the marking unit and the collecting unit
  • the input end is connected, the input end of the collecting unit is connected to the output end of the filtering unit, the output end of the collecting unit is connected to the processor, and the output end of the processor is connected to the marking unit.
  • an embodiment of the present invention provides a method for removing a high frequency radio frequency interference, the method comprising:
  • Corresponding processing is performed on the EEG signals corresponding to the sub-intermediate signals according to the determined signal type.
  • the embodiment of the present invention provides another high frequency radio frequency interference removing apparatus, where the apparatus is used to perform the method of the second aspect, including:
  • An acquisition unit for collecting an EEG signal An acquisition unit for collecting an EEG signal
  • Corresponding processing is performed on the EEG signal corresponding to the sub-intermediate signal according to the determined signal type of the sub-intermediate signal.
  • the detection threshold of the high-frequency radio frequency interference signal is obtained by analyzing the EEG signal in the time domain, and the high-frequency radio frequency interference signal is detected according to the detection threshold, so that the brain having the corresponding period of the high-frequency radio frequency interference signal can be The electrical signals are classified.
  • FIG. 1 is a schematic block diagram of a high frequency radio frequency interference removing apparatus according to an embodiment of the present invention
  • FIG. 2 is a schematic structural diagram of a high frequency radio frequency interference removing apparatus according to an embodiment of the present invention
  • FIG. 3 is a schematic structural diagram of another high frequency radio frequency interference removing apparatus according to an embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of another high frequency radio frequency interference removing apparatus according to an embodiment of the present invention.
  • FIG. 5 is a schematic flowchart of a method for removing high frequency radio frequency interference according to an embodiment of the present invention
  • FIG. 6 is a schematic flow chart of a method for removing high frequency radio frequency interference according to another embodiment of the present invention.
  • FIG. 7 is a schematic diagram of a time period relationship according to an embodiment of the present invention.
  • the term “if” can be interpreted as “when” or “on” or “in response to determining” or “in response to detecting” depending on the context.
  • the phrase “if determined” or “if detected [condition or event described]” may be interpreted in context to mean “once determined” or “in response to determining” or “once detected [condition or event described] ] or “in response to detecting [conditions or events described]”.
  • the terminals described in this embodiment of the invention include, but are not limited to, other portable devices such as mobile phones, laptop computers or tablet computers having touch sensitive surfaces (eg, touch screen displays and/or touch pads). It should also be understood that in some embodiments, the device is not a portable communication device, but a desktop computer having a touch sensitive surface (eg, a touch screen display and/or a touch pad).
  • the terminal can include one or more other physical user interface devices such as a physical keyboard, mouse, and/or joystick.
  • the high frequency radio frequency interference removing apparatus and method are used for removing a high frequency radio frequency interference signal for an EEG signal collected in a medical monitoring system, including but not limited to an alpha wave and a beta signal. Waves, ⁇ waves, and ⁇ waves.
  • FIG. 1 is a schematic diagram of a module of a high frequency radio frequency interference removing apparatus according to an embodiment of the present invention.
  • the apparatus may include: a filtering unit 101, a high frequency signal extracting unit 102, a marking unit 103, and an acquisition.
  • Unit 104 and processor 105 wherein
  • the filtering unit 101 the input end of the filtering unit 101 is connected to the original EEG signal, and is used for filtering the original EEG signal to obtain an intermediate EEG signal;
  • the high-frequency signal extracting unit 102 the input end of the high-frequency signal extracting unit 102 is connected to the output end of the filtering unit, and is configured to filter the intermediate electroencephalogram signal to extract the intermediate electroencephalogram signal High frequency signal
  • the marking unit 103 is connected to the output end of the high-frequency signal extracting unit 102 for comparing the magnitude of the high-frequency signal with the size of the comparison threshold, and comparing the result to the middle according to the comparison result.
  • EEG signals are classified and labeled;
  • the collecting unit 104 the input end of the collecting unit 104 is connected to the output end of the filtering unit 101, and is used for sampling an intermediate EEG signal after classification and marking to obtain an EEG signal, and the EEG is Signal input to the processor 105;
  • the processor 105 is connected to an output end of the collecting unit 104, and an output end of the processor 105 is connected to an input end of the marking unit 103 for setting a marking unit.
  • the threshold is compared and the acquisition unit 104 is controlled to sample the intermediate EEG signal.
  • the filtering unit 101 performs low-pass filtering on the original EEG signal input at the input end thereof to obtain an intermediate EEG signal after attenuating signals outside the EEG signal band.
  • the intermediate electroencephalogram signal is input to the high frequency signal extracting unit 102 to extract a high frequency signal therein, and the high frequency signal is input to a marking unit, and the marking unit 103 compares the high frequency signal with the The size of the comparison threshold set by the processor 105, when the comparison result indicates that the amplitude of the high frequency signal is greater than the comparison threshold, indicating that the original EEG signal corresponding to the high frequency signal is interfered, the marking unit 103
  • the intermediate EEG signal is marked to cause the acquisition unit 104 to sample an EEG signal that has been subjected to an interference marker.
  • the device may include: a filtering unit 201, a high frequency signal extracting unit 202, a marking unit 203, and an acquisition.
  • Unit 204 and processor 205 wherein
  • the filtering unit 201 the input end of the filtering unit 201 is connected to the original EEG signal, and is used for filtering the original EEG signal to obtain an intermediate EEG signal;
  • the high-frequency signal extracting unit 202 the input end of the high-frequency signal extracting unit 202 is connected to the output end of the filtering unit, and is configured to filter the intermediate electroencephalogram signal to extract the intermediate electroencephalogram signal High frequency signal
  • the marking unit 203 is connected to the output end of the high frequency signal extracting unit 202 for comparing the magnitude of the high frequency signal with the size of the comparison threshold, and comparing the middle of the comparison according to the comparison result. EEG signals are classified and labeled;
  • the collecting unit 204 the input end of the collecting unit 204 is connected to the output end of the filtering unit 201, and is used for sampling the intermediate EEG signal after the classification and marking to obtain an EEG signal, and the EEG is Signal input to the processor;
  • the processor 205 the input end of the processor 205 is connected to the output end of the collecting unit 204, and the output end of the processor 205 is connected to the input end of the marking unit 203 for setting the marking unit.
  • the threshold is compared and the acquisition unit 204 is controlled to sample the intermediate EEG signal.
  • the processor 205 can also update the comparison threshold according to the intermediate EEG signal output by the acquisition unit 204, and output the comparison threshold.
  • the filtering unit 201 includes a low-pass filter, and two inputs of the low-pass filter access the original EEG signal picked up by the EEG signal lead, wherein the original EEG signal is a difference signal.
  • the high frequency signal extraction unit 202 includes a first amplifier, a high pass filter, and a second amplifier, wherein two input ends of the first amplifier are respectively connected to two outputs of the low pass filter, the first An output of an amplifier is coupled to an input of the high pass filter; an output of the high pass filter is coupled to an input of the second amplifier.
  • the marking unit 203 includes a digital-to-analog converter, a high-speed comparator, and a switch module S, wherein an input end of the digital-to-analog converter is connected to an output end of the processor 205; a first input end of the high-speed comparator Connecting the output end of the digital-to-analog converter, the second input end of the high-speed comparator is connected to the output end of the second amplifier in the high-frequency signal extracting unit 202; the two ends of the switch module S are respectively connected to the Both ends of the output of the low pass filter, the opening and closing of the switch module S are controlled by the comparison result of the high speed comparator.
  • the collecting unit 204 includes a differential analog-to-digital converter, and two input ends of the differential analog-to-digital converter are respectively connected to two output ends of the low-pass filter in the filtering unit 201, and at the same time, the differential analog-to-digital conversion
  • the two inputs of the device are respectively connected to two ends of the switch module S in the marking unit 203, and the output of the differential analog-digital converter is connected to the processor 205.
  • the low-pass filter is configured to perform low-pass filtering on the original EEG signal picked up by the EEG signal lead to obtain an intermediate EEG signal after attenuating the signal outside the EEG signal band, wherein
  • the intermediate brain electrical signal is a differential signal.
  • the intermediate EEG signal is input to the first amplifier, the first amplifier amplifies the intermediate EEG signal, and since the intermediate EEG signal is a differential signal, the first amplifier is further used to Converting the intermediate electroencephalogram signal into a single-ended first intermediate electroencephalogram signal, and the high-pass filter performs high-pass filtering on the first intermediate electroencephalogram signal to extract a high-frequency signal therein, the second amplifier pair
  • the high frequency signal is amplified to increase the amplitude of the high frequency signal, and the increased second intermediate brain electrical signal is sent to the high speed comparator in the marking unit 203.
  • the digital-to-analog converter accesses a comparison threshold set by the processor, and converts the comparison threshold into a reference voltage, wherein the comparison threshold is obtained by statistical analysis of clinical experience data. Fixed threshold.
  • the high speed comparator compares the magnitude of the second intermediate EEG signal input by the second amplifier with the magnitude of the reference voltage, and outputs a comparison result to the switch module S.
  • the high frequency comparator When the amplitude of the high frequency signal is greater than the reference voltage, indicating that the intermediate brain electrical signal is interfered by a high frequency radio frequency signal, the high frequency comparator outputs a high level, so that the switch module S is closed, thereby Shorting the two inputs of the differential analog to digital converter to cause the differential analog to digital converter to sample a zero signal, thereby classifying the intermediate EEG signal, ie, when the high frequency signal amplitude When the value is greater than the reference voltage, the differential analog-to-digital converter samples a zero signal, causing the sampled EEG waveform to exhibit a zero pulse, thereby marking the disturbed intermediate EEG signal.
  • the differential digital-to-analog converter When the amplitude of the high frequency signal is less than the reference voltage, indicating that the intermediate brain electrical signal is not interfered by the high frequency radio frequency signal, the high frequency comparator outputs a low level, and the switch module S Disconnected, the differential digital-to-analog converter normally samples the intermediate EEG signal to obtain an EEG signal, and the differential analog-to-digital converter samples the different labeled EEG by opening and closing the switch S signal.
  • the collecting unit 204 may further include a third amplifier, wherein the third amplifier is configured to amplify the intermediate brain electrical signal, and output a third intermediate brain electrical power obtained by the intermediate brain electrical signal being amplified. a signal to facilitate sampling by the differential analog to digital converter. As shown in FIG. 3, the input of the third amplifier is connected to the output of the low pass filter, and the output of the third amplifier is connected to the input of the differential analog to digital converter.
  • the third amplifier may be disposed before the switch module S, or may be disposed after the switch module S, which is not specifically limited in the embodiment of the present invention.
  • the third amplifier includes, but is not limited to, a general-purpose amplifier, a high-speed amplifier, a low-power amplifier, a programmable gain amplifier (PGA), and the like.
  • PGA programmable gain amplifier
  • the third amplifier and the differential analog-to-digital converter may be two separate devices, or may be a dedicated EEG acquisition chip with an amplifier and an analog-to-digital conversion function, which is not limited in the embodiment of the present invention.
  • the differential analog-to-digital converter may be an 8-bit analog-to-digital converter, a 10-bit analog-to-digital converter, a 12-bit analog-to-digital converter, a 16-bit analog-to-digital converter, and a 24-bit analog-to-digital converter. Any one of the embodiments of the present invention is not specifically limited.
  • the processor 205 is further configured to perform operation processing corresponding to the classification mark on different labeled EEG signals, for example, when the amplitude of the second EEG signal is greater than the reference voltage, The switch module S is closed to short the two inputs of the differential analog to digital converter, thereby causing the analog to digital converter to sample a zero signal, but due to the differential analog to digital converter and the high frequency RF There is noise in the interference removal device, and the amplitude of the zero signal must be zero.
  • the processor 205 may set a zero threshold, and the amplitude sampled by the differential analog-to-digital converter is lower than the zero threshold.
  • the EEG signal is set to zero.
  • the low-pass filter includes, but is not limited to, a second-order passive RC filter, a third-order passive RC filter, and the like, which are not specifically limited in the embodiment of the present invention.
  • the high frequency signal in the high frequency radio frequency interference removing device extracts the high frequency signal in the EEG signal, and compares the high frequency signal with a preset comparison threshold to determine Whether the high frequency signal is an interference signal, when it is determined that the high frequency signal is an interference signal, the EEG signal corresponding to the interference signal is set to zero by the marking unit, so that the interference signal in the EEG signal can be effectively taken.
  • FIG. 4 is a schematic structural diagram of another high frequency radio frequency interference device according to an embodiment of the present invention.
  • the device may include: a filtering unit 401, a high frequency signal extracting unit 402, and a marking unit. 403.
  • the filtering unit 401 the input end of the filtering unit 401 is connected to the original EEG signal, and is used for filtering the original EEG signal to obtain an intermediate EEG signal;
  • the high-frequency signal extracting unit 402 the input end of the high-frequency signal extracting unit 402 is connected to the output end of the filtering unit 401, and is configured to filter the intermediate electroencephalogram signal to extract the intermediate brain electric power High frequency signal in the signal;
  • the marking unit 403 is connected to the output end of the high frequency signal extracting unit 402 for comparing the magnitude of the high frequency signal with the size of the comparison threshold, and comparing the middle of the threshold according to the comparison result. EEG signals are classified and labeled;
  • the collecting unit 404 the input end of the collecting unit 404 is connected to the output end of the filtering unit 401, and is used for sampling the intermediate EEG signal after the classification and marking to obtain an EEG signal, and the EEG is Signal input to the processor;
  • the processor 405, the input end of the processor is connected to the output end of the collecting unit 404, and the output end of the processor 405 is connected to the input end of the marking unit 403 for setting a comparison of the marking unit. Threshold, and controlling the acquisition unit 404 to sample the intermediate EEG signal.
  • the filtering unit 401 includes a low-pass filter, and two inputs of the low-pass filter access the original EEG signal picked up by the EEG signal lead, wherein the original EEG signal is a difference signal.
  • the high frequency signal extraction unit 402 includes a first amplifier, a high pass filter, and a second amplifier, wherein two input ends of the first amplifier are respectively connected to two outputs of the low pass filter, the first An output of an amplifier is coupled to an input of the high pass filter; an output of the high pass filter is coupled to an input of the second amplifier.
  • the marking unit 403 includes a digital-to-analog converter, a high-speed comparator, and a switching module S, wherein an input end of the digital-to-analog converter is connected to an output end of the processor 405; a first input end of the high-speed comparator Connecting an output of the digital-to-analog converter, the second input of the high-speed comparator is connected to an output of the second amplifier of the high-frequency signal extraction unit 402; the first end of the switch module S is connected to the The collecting unit 404, the opening and closing of the switch module S is controlled by the comparison result of the high speed comparator.
  • the collecting unit 404 includes a fourth amplifier and a single-ended analog-to-digital converter, wherein the fourth amplifier is an instrumentation amplifier, and two input ends of the instrumentation amplifier are respectively connected to an output end of the low-pass filter. An output of the instrumentation amplifier is coupled to an input of the single-ended analog-to-digital converter; an output of the single-ended analog-to-digital converter is coupled to the processor 405.
  • the switch module S may be connected to the fourth amplifier, or may be connected to the fourth amplifier, before the single-ended analog-to-digital converter, if the switch module S is connected to the Before the fourth amplifier, the two ends of the switch module S are respectively connected to two input ends of the fourth amplifier, and if the switch module S is connected before the single-ended analog-to-digital converter, the switch module One end of S is connected to the input end of the single-ended analog-to-digital converter, and the other end is grounded.
  • the low-pass filter is configured to perform low-pass filtering on the original EEG signal picked up by the EEG signal lead to obtain an intermediate EEG signal after attenuating the signal outside the EEG band, wherein
  • the middle EEG signal is a differential signal.
  • the intermediate EEG signal is input to the first amplifier, the first amplifier amplifies the intermediate EEG signal, and since the intermediate EEG signal is a differential signal, the first amplifier is further used to Converting the intermediate electroencephalogram signal into a single-ended first intermediate electroencephalogram signal, and the high-pass filter performs high-pass filtering on the first intermediate electroencephalogram signal to extract a high-frequency signal therein, the second amplifier pair
  • the high frequency signal is amplified to increase the amplitude of the high frequency signal, and the increased second intermediate brain electrical signal is sent to the high speed comparator of the marking unit 403.
  • the digital-to-analog converter accesses a comparison threshold set by the processor, and converts the comparison threshold into a reference voltage, wherein the comparison threshold is obtained by statistical analysis of clinical experience data. Fixed threshold.
  • the high speed comparator compares the magnitude of the high frequency signal input by the second amplifier with the magnitude of the reference voltage, and outputs a comparison result to the switch module S.
  • the high frequency comparator When the amplitude of the high frequency signal is greater than the reference voltage, indicating that the intermediate brain electrical signal is interfered by a high frequency radio frequency signal, the high frequency comparator outputs a high level, so that the switch module S is closed, thereby Grounding the input of the single-ended analog-to-digital converter to sample the single-ended analog-to-digital converter to a zero signal, thereby classifying the intermediate EEG signal, that is, when the high-frequency signal amplitude
  • the single-ended analog-to-digital converter samples a zero signal, so that the sampled EEG signal waveform exhibits a zero pulse, thereby marking the interfered intermediate EEG signal.
  • the high frequency comparator When the amplitude of the high frequency signal is less than the reference voltage, indicating that the original EEG signal is not interfered by the high frequency radio frequency signal, the high frequency comparator outputs a low level, the switch module S Disconnected, the collecting unit 404 normally samples the intermediate EEG signal, the fourth amplifier in the collecting unit 404 amplifies the intermediate EEG signal, and converts the intermediate EEG signal into a single-ended Four intermediate EEG signals for sampling by the single-ended analog-to-digital converter, the single-ended digital-to-analog converter normally sampling the intermediate EEG signal to obtain an EEG signal, through the opening and closing of the switch S, The single-ended analog-to-digital converter is sampled to differently labeled EEG signals.
  • the medical monitoring system includes an alpha wave channel, a beta wave channel, a theta wave channel, and a delta wave channel, four EEG measurement channels, and the high frequency radio frequency interference removing device pairs the EEG signals in the four EEG channels.
  • the marking and collecting process in the above embodiments are used, or the high frequency radio frequency interference removing device performs the marking and collecting processing in the above embodiment only on the EEG signals of the delta wave channel, and the other three channel pairs and the delta wave.
  • the EEG signals acquired at the same time of the channel are subjected to the same labeling process as the delta wave channel.
  • the high frequency signal in the high frequency radio frequency interference removing device extracts the high frequency signal in the EEG signal, and compares the high frequency signal with a preset comparison threshold to determine Whether the high frequency signal is an interference signal, when it is determined that the high frequency signal is an interference signal, the EEG signal corresponding to the interference signal is set to zero by the marking unit, so that the interference signal in the EEG signal can be effectively taken.
  • FIG. 5 is a schematic flowchart of a method for removing high frequency radio frequency interference according to an embodiment of the present invention. As shown in FIG. 5, the method includes:
  • the sampling frequency of the acquired EEG signal is not less than 2 kHz.
  • the frequency of the normal EEG signal is lower than 100 Hz, and the frequency of the high-frequency radio frequency interference signal is higher than 10 kHz, and the low-frequency signal in the EEG signal is attenuated by a high-pass filtering method to obtain a main The intermediate signal of the high frequency radio frequency interference signal.
  • the time domain feature includes, but is not limited to, an amplitude of the intermediate signal, an average value of the intermediate signal amplitude, a variance of the intermediate signal amplitude, and the like, which are obtained according to the time domain feature.
  • Detecting a threshold for example, if the first preset duration is ⁇ , and there are M sampling points in the first preset duration, the average value of the amplitudes of the M sampling points may be used as the detection. Threshold. It should be understood that the above examples are by way of example only and are not to be construed as limiting.
  • a sub-intermediate signal of a second duration T is obtained from the intermediate signal, and a time domain characteristic of the sub-intermediate signal is compared with the detection threshold to determine a signal of the sub-intermediate signal.
  • Types of For example, if the sub-intermediate signal amplitude is greater than or equal to the detection threshold, determining that the sub-intermediate signal is an interference signal, and if the sub-intermediate signal amplitude is less than the detection threshold, determining that the sub-intermediate signal is Non-interfering signal.
  • the EEG signal corresponding to the sub-intermediate signal is a signal subjected to high-frequency radio frequency interference
  • the sub-intermediate signal is a non-interfering signal
  • the EEG signal corresponding to the sub-intermediate signal is a normal signal.
  • Different signal processing methods are used for EEG signals and normal EEG signals subjected to high-frequency radio frequency interference. For example, if the EEG signal in a certain period of time is a signal interfered by high-frequency radio frequency, the interfered signal is used.
  • the normal EEG signal that is the same as the duration of the interfered signal before the occurrence of the signal replaces the high frequency radio frequency interference.
  • the EEG signal is high-pass filtered to obtain an intermediate signal including high-frequency radio frequency interference, and an intermediate signal is acquired at the first preset duration, and the first preset duration is calculated.
  • the sub-intermediate signal is an interference signal
  • the EEG signal corresponding to the sub-intermediate signal is an EEG signal subjected to high-frequency radio frequency interference
  • the second preset duration is within an intermediate intermediate signal amplitude If the average value is less than the detection threshold, the sub-intermediate signal is determined to be a non-interfering signal, and the EEG signal corresponding to the sub-intermediate signal is a normal EEG signal.
  • the second preset duration T may be smaller than the first preset duration ⁇ , may be equal to the first preset duration ⁇ , or may be greater than the first preset duration ⁇ , in the embodiment of the present invention. No specific limitation.
  • the detection threshold calculated according to the first preset duration in the sub-intermediate signal may be used as a detection threshold of the signal in the second preset duration in the sub-intermediate signal, or may be used as the sub-intermediate
  • the detection threshold of the signal in the next second preset duration of the signal may also be the detection threshold of the signal in the third preset duration
  • the third preset duration is a period of time in the next intermediate signal, which is implemented by the present invention.
  • the examples are not specifically limited.
  • FIG. 6 is a schematic flowchart diagram of another method for removing high frequency radio frequency interference according to an embodiment of the present invention. As shown in FIG. 6, the method includes:
  • the sampling frequency of the acquired EEG signal is not less than 2 kHz.
  • the frequency of the normal EEG signal is lower than 100 Hz, and the frequency of the high-frequency radio frequency interference signal is higher than 10 kHz, and the low-frequency signal in the EEG signal is attenuated by a high-pass filtering method to obtain a main The intermediate signal of the high frequency radio frequency interference signal.
  • the time domain feature is an envelope feature of the intermediate signal
  • the detection threshold is calculated according to an envelope feature of the intermediate signal.
  • the step of calculating the detection threshold according to the envelope feature may be:
  • the time domain characteristic change of the envelope on the intermediate signal and the lower envelope is calculated in real time in the first preset time length ⁇ , and the detection threshold is calculated according to the time domain change of the upper envelope and the lower envelope, for example, Obtaining n first preset duration intermediate signals from the intermediate signal, and counting an upper envelope feature and a lower envelope feature of the n first preset duration intermediate signals, according to the upper envelope feature and the The envelope characteristics are calculated to calculate the detection threshold.
  • the detection threshold can be determined according to the following formula,
  • C is a real number greater than 0, i, n is a positive integer, ⁇ is the first preset duration, Thd is the detection threshold, f up (t) is an upper envelope feature, and f low (t) is Lower envelope feature.
  • the upper envelope f up (t) and the lower envelope feature f low (t) may be obtained according to the following formula.
  • a and B are real numbers greater than 0, and x(t) is the amplitude of the intermediate brain electrical signal at time t.
  • FIG. 7 is a schematic diagram of a relationship between a time period according to an embodiment of the present invention, the time t 1 to a time t-tau
  • the two time periods from the time t 2 - ⁇ to the time t 2 may include mutually overlapping portions, or may be two time segments that are continuous but not overlapping, and may also be two time segments having time intervals, in the embodiment of the present invention. No specific restrictions are imposed.
  • the time domain feature is not limited to the envelope feature, and the time domain feature may also be an average value, a variance, a standard deviation, and a combined value of the average value and the maximum value of the intermediate signal amplitude.
  • the value of the feature value may be a second value maximum value or a third value maximum value, etc., which is not specifically limited in the embodiment of the present invention.
  • the signal types of the sub-intermediate signals may be determined by the following two implementation manners:
  • Embodiment 1 The first threshold and the second threshold are obtained according to the detection threshold, wherein the first threshold is obtained by multiplying the detection threshold by a first coefficient, and the second threshold is the detection threshold multiplied by The two coefficients are obtained, and the first coefficient is greater than the second coefficient.
  • the first threshold is obtained by adding the first constant
  • the second threshold is obtained by adding the second constant
  • the first constant is greater than the second constant.
  • the first threshold by multiplying the detection threshold by the first coefficient, obtaining the second threshold by multiplying the detection threshold by the second coefficient, and acquiring a second preset duration T from the intermediate signal a sub-intermediate signal, if the amplitude of the sub-intermediate signal is greater than or equal to the first threshold, determining that the sub-intermediate signal is an interference signal; if the amplitude of the sub-intermediate signal is less than a first threshold and greater than or equal to a second threshold And determining that the sub-intermediate signal is a suspected interference signal; if the amplitude of the sub-intermediate signal is less than a second threshold, determining that the sub-intermediate signal is a non-interfering signal.
  • Embodiment 2 Obtain a sub-intermediate signal of a second preset duration T from the intermediate signal, and determine that the amplitude of the sub-intermediate signal in the second preset duration is greater than the proportion of the detection threshold, if If the ratio is greater than or equal to the first ratio threshold, determining that the sub-intermediate signal is an interference signal; if the ratio is less than the first ratio threshold and greater than or equal to a second ratio threshold, determining that the sub-intermediate signal is Suspected interference signal; if the ratio is less than the second ratio threshold, it is determined that the sub-intermediate signal is a non-interfering signal.
  • the time period corresponding to the second preset duration T may be exactly the same as the time period corresponding to the n first preset durations ⁇ , or may only partially overlap, and the time corresponding to the second preset duration T
  • the time period corresponding to the n first preset durations ⁇ may not overlap, that is, the time period corresponding to the second preset duration T is after the time period corresponding to the n first preset durations ⁇ A time period.
  • the sub-intermediate signal is an interference signal
  • the sub-eEG electrical signal corresponding to the sub-intermediate signal is an EEG signal subjected to high-frequency radio frequency interference
  • the EEG subjected to high-frequency radio frequency interference Deleting the signal, or replacing the interference signal with a normal EEG signal having the same duration as the EEG signal subjected to the high frequency radio frequency interference before the occurrence of the EEG signal subjected to the high frequency radio frequency interference
  • the signal is a suspected interference signal
  • the corresponding sub-brain electrical signal is a suspected interfering EEG signal, and the suspected interfering EEG signal is output, and the suspected interfering EEG signal is not credible
  • replacing the interference signal with a non-interfering signal having the same duration as the suspected interfered EEG signal before the occurrence of the suspected interfered EEG signal; or weakening the suspected interfered EEG signal
  • the sub-intermediate signal is a non-interfering signal
  • the corresponding sub-interfering signal the
  • the method for weakening the suspected interference signal may be that the parameter calculated by the normal EEG signal before the occurrence of the suspected interfered EEG signal replaces the parameter of the segment, or may be the first five times of calculation The average value of the corresponding parameters of the normal EEG signal is substituted for the segment parameter, which is not specifically limited in the embodiment of the present invention.
  • the high frequency radio frequency interference removal method obtained by the embodiment of the present invention obtains the detection threshold of the high frequency radio frequency interference signal by analyzing the EEG signal in the time domain, and classifies the high frequency radio frequency interference signal according to the detection threshold.
  • the categories of high-frequency radio frequency interference signals classify and mark EEG signals, so that EEG signals with different interference categories can be processed differently.
  • the embodiment of the present invention further provides a high frequency radio frequency interference removing device, which is used to perform the method according to any of the preceding claims.
  • the apparatus of this embodiment includes: an acquisition circuit and a processor.
  • the acquisition circuit is configured to collect an EEG signal. Specifically, it is used to collect an EEG signal with a sampling frequency not lower than 2 kHz.
  • the processor specifically, the processor is configured to:
  • Corresponding processing is performed on the sub-brain electrical signals according to the determined signal type.
  • a computer readable storage medium is stored, the computer readable storage medium storing a computer program comprising program instructions, the program instructions being implemented by a processor to:
  • the computer readable storage medium may be an internal storage unit of the apparatus described in any of the preceding embodiments, such as a hard disk or memory of the device.
  • the computer readable storage medium may also be an external storage device of the device, such as a plug-in hard disk equipped on the device, a smart memory card (SMC), and a Secure Digital (SD) card. , Flash Card, etc.
  • the computer readable storage medium may also include both an internal storage unit of the device and an external storage device.
  • the computer readable storage medium is for storing the computer program and other programs and data required by the device.
  • the computer readable storage medium can also be used to temporarily store data that has been output or is about to be output.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, or an electrical, mechanical or other form of connection.
  • the units described as separate components may or may not be physically separated, and the components displayed as the units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the embodiments of the present invention.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
  • the technical solution of the present invention contributes in essence or to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium.
  • a number of instructions are included to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

Abstract

本发明实施例公开了一种高频射频干扰去除的装置以及方法，其中装置包括：滤波单元，用于对原始脑电信号进行滤波得到中间脑电信号；高频信号提取单元，用于对中间脑电信号进行滤波，提取出中间脑电信号中的高频信号；标记单元，用于比较高频信号的幅值与比较阈值的大小，并根据比较结果对中间脑电信号进行分类标记；采集单元，用于对分类标记后的中间脑电信号进行采样得到脑电信号，并输入到所述处理器；处理器，用于设置比较阈值，并控制采集单元进行采样。本发明实施例通过对脑电信号在时域上进行分析，得到高频射频干扰信号的检测阈值，根据检测阈值检测出高频射频干扰信号，从而能够对高频射频干扰信号对应的脑电信号进行分类处理。

Description

一种高频射频干扰去除装置及方法 技术领域
本发明涉及医疗设备技术领域，尤其涉及一种高频射频干扰去除装置及方法。
背景技术
高频电刀(高频手术刀)是一种取代机械手术刀进行组织切割的电外科器械(electrosurgical unit，ESU)，它通过有效电极尖端产生的高频高压信号与肌体接触时进行加热，实现对肌体组织的分离和凝固，从而起到切割和止血的目的，在临床手术中，应用也越来越广泛。但是电刀产生的高频信号对术中生理信号的影响较大，这是目前术中监护的挑战，处理不当则会致使监护中断，或者给出错误的参数值，影响医生判断病人状态。
在病人监护系统中，目前对于ESU高频干扰的检测方法主要是基于干扰和生理信号的频域分布差异，设计对应滤波器去除高频干扰信号，或者基于频域特征变化给出干扰信号标记；频域分析需要对信号进行傅里叶变化，其计算复杂度高、资源占用大、耗时长。
发明内容
本发明实施例提供一种高频射频干扰去除装置及方法，可以去除脑电信号中的高频射频干扰信号。
第一方面，本发明实施例提供了一种高频射频干扰去除装置，该装置包括：滤波单元，高频信号提取单元，标记单元、采集单元以及处理器，其中
所述滤波单元，所述滤波单元的输入端接入所述原始脑电信号，用于对原始脑电信号进行滤波得到中间脑电信号；
所述高频信号提取单元，所述高频信号提取单元的输入端与所述滤波单元的输出端连接，用于对所述中间脑电信号进行滤波，提取出所述中间脑电信号中的高频信号；
所述标记单元，所述标记单元与所述高频信号提取单元的输出端连接，用于比较所述高频信号的幅值与比较阈值的大小，并根据比较结果对所述中间脑 电信号进行分类标记；
所述采集单元，所述采集单元的输入端与所述滤波单元的输出端连接，用于对进行分类标记后的中间脑电信号进行采样得到脑电信号，并将所述脑电信号输入到所述处理器；
所述处理器，用于设置标记单元所用的比较阈值，并控制所述采集单元对所述中间脑电信号进行采样；
其中，所述处理器的输入端与所述采集单元的输出端连接，所述处理器的输出端与所述标记单元的输入端连接，所述滤波单元的输入端接入所述原始脑电信号，所述滤波单元的输出端连接所述高频信号提取单元的输入端，所述高频信号提取单元的输出端连接所述标记单元，所述标记单元的输出端与所述采集单元的输入端连接，所述采集单元的输入端连接所述滤波单元的输出端，所述采集单元的输出端连接所述处理器，所述处理器的输出端连接所述标记单元。
第二方面，本发明实施例提供了一种高频射频干扰去除方法，该方法包括：
获取脑电信号；
对所述脑电信号进行高通滤波从而获得中间信号，其中，所述中间信号为高通滤波后的包含高频射频干扰的信号；
按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值；
按照第二预设时长获取子中间信号，根据所述检测阈值确定所述子中间信号的信号类型，其中，不同的信号类型反映所述脑电信号受干扰的程度不同；
根据确定的信号类型对所述子中间信号对应的脑电信号执行对应的处理。
第三方面，本发明实施例提供了另一种高频射频干扰去除装置，该装置用于执行上述第二方面的方法，包括：
采集单元，用于采集脑电信号；
处理器，所述处理器用于执行以下步骤：
对所述脑电信号进行高通滤波从而得到中间脑电信号，其中，所述中间信号为高通滤波后的包含高频射频干扰的信号；
按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值；
按照第二预设时长获取子中间脑电信号，根据所述检测阈值确定所述子中 间信号的信号类型，其中，不同的信号类型反映所述脑电信号受干扰的程度不同；
根据确定的子中间信号的信号类型对所述子中间信号对应的脑电信号执行对应的处理。
本发明实施例通过对脑电信号在时域上进行分析，得到高频射频干扰信号的检测阈值，根据检测阈值检测出高频射频干扰信号，从而能够对存在高频射频干扰信号对应时段的脑电信号进行分类处理。
附图说明
为了更清楚地说明本发明实施例技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明实施例提供的一种高频射频干扰去除装置的模块示意图；
图2是本发明实施例提供的一种高频射频干扰去除装置的结构示意图；
图3是本发明实施例提供的另一种高频射频干扰去除装置的结构示意图；
图4是本发明实施例提供的另一种高频射频干扰去除装置的结构示意图；
图5是本发明实施例提供的一种高频射频干扰去除方法的流程示意图；
图6是本发明另一实施例提供的一种高频射频干扰去除方法的流程示意图；
图7是本发明实施例提供的一种时间段关系示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
应当理解，当在本说明书和所附权利要求书中使用时，术语“包括”和“包含”指示所描述特征、整体、步骤、操作、元素和/或组件的存在，但并不排除一个或多个其它特征、整体、步骤、操作、元素、组件和/或其集合的存在或添加。
还应当理解，在此本发明说明书中所使用的术语仅仅是出于描述特定实施例的目的而并不意在限制本发明。如在本发明说明书和所附权利要求书中所使用的那样，除非上下文清楚地指明其它情况，否则单数形式的“一”、“一个”及“该”意在包括复数形式。
还应当进一步理解，在本发明说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
如在本说明书和所附权利要求书中所使用的那样，术语“如果”可以依据上下文被解释为“当…时”或“一旦”或“响应于确定”或“响应于检测到”。类似地，短语“如果确定”或“如果检测到[所描述条件或事件]”可以依据上下文被解释为意指“一旦确定”或“响应于确定”或“一旦检测到[所描述条件或事件]”或“响应于检测到[所描述条件或事件]”。
具体实现中，本发明实施例中描述的终端包括但不限于诸如具有触摸敏感表面(例如，触摸屏显示器和/或触摸板)的移动电话、膝上型计算机或平板计算机之类的其它便携式设备。还应当理解的是，在某些实施例中，所述设备并非便携式通信设备，而是具有触摸敏感表面(例如，触摸屏显示器和/或触摸板)的台式计算机。
在接下来的讨论中，描述了包括显示器和触摸敏感表面的装置。然而，应当理解的是，终端可以包括诸如物理键盘、鼠标和/或控制杆的一个或多个其它物理用户接口设备。
本发明实施例中，所述高频射频干扰去除装置以及方法用于对医疗监护系统中采集的脑电信号进行高频射频干扰信号的去除，所述脑电信号包括但不限于α波、β波、θ波以及δ波等。
请参阅图1，图1是本发明实施例提供一种高频射频干扰去除装置的模块示意图，如图所示该装置可包括：滤波单元101，高频信号提取单元102，标记单元103、采集单元104以及处理器105，其中，
所述滤波单元101，所述滤波单元101的输入端接入所述原始脑电信号，用于对原始脑电信号进行滤波得到中间脑电信号；
所述高频信号提取单元102，所述高频信号提取单元102的输入端与所述滤波单元的输出端连接，用于对所述中间脑电信号进行滤波，提取出所述中间脑 电信号中的高频信号；
所述标记单元103，所述标记单元103与所述高频信号提取单元102的输出端连接，用于比较所述高频信号的幅值与比较阈值的大小，并根据比较结果对所述中间脑电信号进行分类标记；
所述采集单元104，所述采集单元104的输入端与所述滤波单元101的输出端连接，用于对进行分类标记后的中间脑电信号进行采样得到脑电信号，并将所述脑电信号输入到所述处理器105；
所述处理器105，所述处理器105的输入端与所述采集单元104的输出端连接，所述处理器105的输出端与所述标记单元103的输入端连接，用于设置标记单元所用比较阈值，并控制所述采集单元104对所述中间脑电信号进行采样。
本发明实施例中，所述滤波单元101将其输入端输入的原始脑电信号进行低通滤波，以得到对脑电信号频带以外信号进行衰减后的中间脑电信号。所述中间脑电信号输入到所述高频信号提取单元102中提取出其中的高频信号，并将所述高频信号输入到标记单元，所述标记单元103对比所述高频信号与所述处理器105设置的比较阈值的大小，当比较结果表征所述高频信号幅值大于所述比较阈值时，表明所述高频信号对应的原始脑电信号受到了干扰，所述标记单元103对所述中间脑电信号进行标记，以使所述采集单元104采样到进行过干扰标记的脑电信号。
请参与图2，图2是本发明实施例提供的一种高频射频干扰装置的结构示意图，如图所示该装置可包括：滤波单元201，高频信号提取单元202，标记单元203、采集单元204以及处理器205，其中，
所述滤波单元201，所述滤波单元201的输入端接入所述原始脑电信号，用于对所述原始脑电信号进行滤波得到中间脑电信号；
所述高频信号提取单元202，所述高频信号提取单元202的输入端与所述滤波单元的输出端连接，用于对所述中间脑电信号进行滤波，提取出所述中间脑电信号中的高频信号；
所述标记单元203，所述标记单元203与所述高频信号提取单元202的输出端连接，用于比较所述高频信号的幅值与比较阈值的大小，并根据比较结果对所述中间脑电信号进行分类标记；
所述采集单元204，所述采集单元204的输入端与所述滤波单元201的输出 端连接，用于对进行分类标记后的中间脑电信号进行采样得到脑电信号，并将所述脑电信号输入到所述处理器；
所述处理器205，所述处理器205的输入端与所述采集单元204的输出端连接，所述处理器205的输出端与所述标记单元203的输入端连接，用于设置标记单元所用比较阈值，并控制所述采集单元204对所述中间脑电信号进行采样。当然，处理器205还可以根据采集单元204输出的中间脑电信号更新比较阈值，并将比较阈值输出。
其中，所述滤波单元201包括低通滤波器，所述低通滤波器的两个输入端接入所述脑电信号导联拾取的原始脑电信号，其中，所述原始脑电信号为差分信号。
所述高频信号提取单元202包括第一放大器、高通滤波器以及第二放大器，其中，所述第一放大器的两个输入端分别连接所述低通滤波器的两个输出端，所述第一放大器的输出端连接所述高通滤波器的输入端；所述高通滤波器的输出端连接所述第二放大器的输入端。
所述标记单元203包括数模转换器、高速比较器以及开关模块S，其中，所述数模转换器的输入端连接所述处理器205的输出端；所述高速比较器的第一输入端连接所述数模转换器的输出端，所述高速比较器的第二输入端连接所述高频信号提取单元202中第二放大器的输出端；所述开关模块S的两端分别连接所述低通滤波器输出端的两端，所述开关模块S的断开与闭合由所述高速比较器的比较结果控制。
所述采集单元204包括差分模数转换器，所述差分模数转换器的两个输入端分别连接所述滤波单元201中低通滤波器的两个输出端，同时，所述差分模数转换器的两个输入端分别连接了所述标记单元203中开关模块S的两端，所述差分模数转换器的输出端连接所述处理器205。
本发明实施例中，所述低通滤波器用于对脑电信号导联拾取的原始脑电信号进行低通滤波，以得到对脑电信号频带以外信号进行衰减后的中间脑电信号，其中，所述中间脑电信号为差分信号。所述中间脑电信号输入到所述第一放大器中，所述第一放大器对所述中间脑电信号进行放大，由于所述中间脑电信号为差分信号，所述第一放大器还用于将所述中间脑电信号转换为单端的第一中间脑电信号，所述高通滤波器对所述第一中间脑电信号进行高通滤波后提取出 其中的高频信号，所述第二放大器对所述高频信号进行放大，以增大所述高频信号的幅值，并将增大后得到的第二中间脑电信号输送到标记单元203中的高速比较器中。在所述标记单元203中，所述数模转换器接入所述处理器设置的比较阈值，并将所述比较阈值转换为参考电压，其中，所述比较阈值为临床经验数据统计分析得到的固定阈值。所述高速比较器比较所述第二放大器输入的所述第二中间脑电信号的幅值与所述参考电压的大小，并输出比较结果至所述开关模块S。当所述高频信号的幅值大于所述参考电压时，表明所述中间脑电信号受到高频射频信号干扰，所述高频比较器输出高电平，使所述开关模块S闭合，从而使所述差分模数转换器的两个输入端短接，以使所述差分模数转换器采样到零信号，从而对所述中间脑电信号进行分类标记，即当所述高频信号幅值大于所述参考电压时，所述差分模数转换器采样到零信号，使采样到的脑电信号波形呈现零脉冲，从而对受干扰的中间脑电信号进行了标记。当所述高频信号的幅值小于所述参考电压时，表明所述中间脑电信号没有受到所述高频射频信号的干扰，所述高频比较器输出低电平，所述开关模块S断开，所述差分数模转换器正常采样所述中间脑电信号以得到脑电信号，通过所述开关S的断开与闭合，使所述差分模数转换器采样到不同标记的脑电信号。
可选地，所述采集单元204还可以包括第三放大器，所述第三放大器用于对所述中间脑电信号进行放大，输出所述中间脑电信号经放大后得到的第三中间脑电信号，以便于所述差分模数转换器进行采样。如图3所示，所述第三放大器的输入端连接所述低通滤波器的输出端，所述第三放大器的输出端连接所述差分模数转换器的输入端。
可选地，所述第三放大器可以设置于所述开关模块S之前，也可以设置于所述开关模块S之后，本发明实施例不作具体限制。
可选地，所述第三放大器包括但不限于通用型放大器、高速型放大器、低功耗型放大器、可编程增益放大器(Programmable Gain Amplifier，PGA)等。
可选地，所述第三放大器与所述差分模数转换器可以是两个分立的器件，也可以是具备放大器和模数转换功能的专用EEG采集芯片，本发明实施例不作具体限定。
可选地，所述差分模数转换器的可以是8位模数转换器、10位模数转换器、12位模数转换器、16位模数转换器、24位模数转换器中的任意一种，本发明实 施例不作具体限定。
可选地，所述处理器205还用于对不同标记的脑电信号执行与所述分类标记对应的操作处理，例如，当所述第二脑电信号的幅值大于所述参考电压时，所述开关模块S闭合使所述差分模数转换器的两个输入端短接，从而使所述模数转换器采样到零信号，但是由于所述差分模数转换器以及所述高频射频干扰去除装置存在噪声，所述零信号的幅值并一定为零，所述处理器205可以设置置零阈值，将所述差分模数转换器采样到的幅值低于所述置零阈值的脑电信号置零。
可选地，所述低通滤波器包括但不限于二阶无源RC滤波器，三阶无源RC滤波器等，本发明实施例不作具体限定。
可以看出，本发明实施例中，通过高频射频干扰去除装置中的高频信号提取单元提取出脑电信号中的高频信号，将高频信号与预先设置的比较阈值进行比较，以确定高频信号是否为干扰信号，当确定所述高频信号为干扰信号时，将干扰信号对应的脑电信号通过标记单元置零，从而能够有效去取脑电信号中的干扰信号。
请参阅图4，图4是本发明实施例提供的另一种高频射频干扰装置的结构示意图，如图4所示，该装置可包括：滤波单元401，高频信号提取单元402，标记单元403、采集单元404以及处理器405，其中，
所述滤波单元401，所述滤波单元401的输入端接入所述原始脑电信号，用于对原始脑电信号进行滤波得到中间脑电信号；
所述高频信号提取单元402，所述高频信号提取单元402的输入端与所述滤波单元401的输出端连接，用于对所述中间脑电信号进行滤波，提取出所述中间脑电信号中的高频信号；
所述标记单元403，所述标记单元403与所述高频信号提取单元402的输出端连接，用于比较所述高频信号的幅值与比较阈值的大小，并根据比较结果对所述中间脑电信号进行分类标记；
所述采集单元404，所述采集单元404的输入端与所述滤波单元401的输出端连接，用于对进行分类标记后的中间脑电信号进行采样得到脑电信号，并将所述脑电信号输入到所述处理器；
所述处理器405，所述处理器的输入端与所述采集单元404的输出端连接， 所述处理器405的输出端与所述标记单元403的输入端连接，用于设置标记单元所用比较阈值，并控制所述采集单元404对所述中间脑电信号进行采样。
其中，所述滤波单元401包括低通滤波器，所述低通滤波器的两个输入端接入所述脑电信号导联拾取的原始脑电信号，其中，所述原始脑电信号为差分信号。
所述高频信号提取单元402包括第一放大器、高通滤波器以及第二放大器，其中，所述第一放大器的两个输入端分别连接所述低通滤波器的两个输出端，所述第一放大器的输出端连接所述高通滤波器的输入端；所述高通滤波器的输出端连接所述第二放大器的输入端。
所述标记单元403包括数模转换器、高速比较器以及开关模块S，其中，所述数模转换器的输入端连接所述处理器405的输出端；所述高速比较器的第一输入端连接所述数模转换器的输出端，所述高速比较器的第二输入端连接所述高频信号提取单元402中第二放大器的输出端；所述开关模块S的第一端接所述采集单元404，所述开关模块S的断开与闭合由所述高速比较器的比较结果控制。
所述采集单元404包括第四放大器和单端模数转换器，其中，所述第四放大器为仪表放大器，所述仪表放大器的两个输入端分别连接所述低通滤波器的输出端，所述仪表放大器的输出端连接所述单端模数转换器的输入端；所述单端模数转换器的输出端连接所述处理器405。
可选地，所述开关模块S可以连接于所述第四放大器之前，也可以连接于所述第四放大器之后，所述单端模数转换器之前，若所述开关模块S连接于所述第四放大器之前，则所述开关模块S的两端分别连接所述第四放大器的两个输入端，若所述开关模块S连接于所述单端模数转换器之前，则所述开关模块S的一端连接于所述单端模数转换器的输入端，另一端接地。
本发明实施例中，所述低通滤波器用于对脑电信号导联拾取的原始脑电信号进行低通滤波，以得到对EEG频带以外信号进行衰减后的中间脑电信号，其中，所述中间脑电信号为差分信号。所述中间脑电信号输入到所述第一放大器中，所述第一放大器对所述中间脑电信号进行放大，由于所述中间脑电信号为差分信号，所述第一放大器还用于将所述中间脑电信号转换为单端的第一中间脑电信号，所述高通滤波器对所述第一中间脑电信号进行高通滤波后提取出其 中的高频信号，所述第二放大器对所述高频信号进行放大，以增大所述高频信号的幅值，并将增大后得到的所述第二中间脑电信号输送到标记单元403的高速比较器中。在所述标记单元403中，所述数模转换器接入所述处理器设置的比较阈值，并将所述比较阈值转换为参考电压，其中，所述比较阈值为临床经验数据统计分析得到的固定阈值。所述高速比较器比较所述第二放大器输入的高频信号的幅值与所述参考电压的大小，并输出比较结果至所述开关模块S。当所述高频信号的幅值大于所述参考电压时，表明所述中间脑电信号受到高频射频信号干扰，所述高频比较器输出高电平，使所述开关模块S闭合，从而使所述单端模数转换器的输入端接地，以使所述单端模数转换器采样到零信号，从而对所述中间脑电信号进行分类标记，即当所述高频信号幅值大于所述参考电压时，所述单端模数转换器采样到零信号，使采样到的脑电信号波形呈现零脉冲，从而对受干扰的中间脑电信号进行了标记。当所述高频信号的幅值小于所述参考电压时，表明所述原始脑电信号没有受到所述高频射频信号的干扰，所述高频比较器输出低电平，所述开关模块S断开，所述采集单元404正常采样所述中间脑电信号，所述采集单元404中的第四放大器将所述中间脑电信号进行放大，并将所述中间脑电信号转换为单端的第四中间脑电信号，以便于所述单端模数转换器采样，所述单端数模转换器正常采样所述中间脑电信号以得到脑电信号，通过所述开关S的断开与闭合，使所述单端模数转换器的采样到不同标记的脑电信号。
可以理解的是，医疗监护系统的EEG测量通道有多个，本发明实施例仅给出其中一个通道的采集与处理过程，其他通道的采集与处理可以参考上述实施例中的过程，或者，其他通道参照被标记通道的脑电信号，对本通道采集的脑电信号进行相同的处理。举例来讲，所述医疗监护系统包括α波通道、β波通道、θ波通道以及δ波通道四个EEG测量通道，所述高频射频干扰去除装置对上述四个EEG通道中的脑电信号均采用上述实施例中的标记与采集处理，或者，所述高频射频干扰去除装置仅对δ波通道的脑电信号实施上述实施例中的标记与采集处理，其他三个通道对与δ波通道相同时间采集到的脑电信号进行与δ波通道相同的标记处理。
可以看出，本发明实施例中，通过高频射频干扰去除装置中的高频信号提取单元提取出脑电信号中的高频信号，将高频信号与预先设置的比较阈值进行 比较，以确定高频信号是否为干扰信号，当确定所述高频信号为干扰信号时，将干扰信号对应的脑电信号通过标记单元置零，从而能够有效去取脑电信号中的干扰信号。
请参阅图5，图5是本发明实施例提供的一种高频射频干扰去除方法的流程示意图，如图5所示，所述方法包括：
501、获取脑电信号。
本发明实施例中，获取的所述脑电信号的采样频率不低于2kHz。
502、对所述脑电信号进行高通滤波从而获得中间信号，其中，所述中间信号为高通滤波后的包含高频射频干扰的信号。
本发明实施例中，正常脑电信号的频率低于100Hz，而高频射频干扰信号的频率高于10kHz以上，通过高通滤波的方法对所述脑电信号中的低频信号进行衰减，以得到主要为高频射频干扰信号的所述中间信号。
503、按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值。
本发明实施例中，所述时域特征包括但不限于所述中间信号的幅值，所述中间信号幅值的平均值、所述中间信号幅值的方差等，根据所述时域特征得到检测阈值，例如，若所述第一预设时长为τ，所述第一预设时长的时间内有M个采样点，可以将所述M个采样点的幅值的平均值作为所述检测阈值。应理解，上述例子仅用作举例，不能理解为具体限定。
504、按照第二预设时长获取子中间信号，根据所述检测阈值确定所述子中间信号的信号类型，其中，不同的信号类型反映所述脑电信号受干扰的程度不同。
本发明实施例中，从所述中间信号中获取一段第二时长T的子中间信号，将所述子中间信号的时域特征与所述检测阈值进行比较，以确定所述子中间信号的信号类型。例如，若所述子中间信号幅值大于等于所述检测阈值，则确定所述子中间信号为干扰信号，若所述子中间信号幅值小于所述检测阈值，则确定所述子中间信号为非干扰信号。应理解，上述例子仅用作举例，不能理解为具体限定。
505、根据确定的信号类型对所述子中间信号对应的脑电信号执行对应的处理。
本发明实施例中，若所述子中间信号为干扰信号，则所述子中间信号对应的脑电信号为受高频射频干扰的信号，若所述子中间信号为非干扰信号，则所述子中间信号对应的脑电信号为正常信号。对受高频射频干扰的脑电信号以及正常脑电信号，进行不同的信号处理方式，例如，若某一时间段内的脑电信号是受高频射频干扰的信号，则用受干扰的信号出现之前的与受干扰信号时长相同的正常脑电信号替换所述受高频射频干扰的信号。
举例来讲，对于采样得到的脑电信号，对该脑电信号进行高通滤波得到包含高频射频干扰的中间信号，以第一预设时长获取一段中间信号，计算得到第一预设时长内该段中间信号幅值的平均值，将该平均值作为检测阈值。再从所述中间信号中获取一段第二时长的子中间信号，计算得到第二预设时长内子中间信号幅值的平均值，若第二预设时长内所述子中间信号幅值的平均值大于等于所述检测阈值，则确定所述子中间信号为干扰信号，所述子中间信号对应的脑电信号为受高频射频干扰的脑电信号，若第二预设时长内子中间信号幅值的平均值小于所述检测阈值，则确定所述子中间信号为非干扰信号，所述子中间信号对应的脑电信号为正常脑电信号。对于所述受高频射频干扰的脑电信号，用所述受高频射频干扰的脑电信号出现之前的与所述受高频射频干扰的脑电信号时长相同的正常脑电信号替换所述干扰信号对应的脑电信号。
可选地，所述第二预设时长T可以小于所述第一预设时长τ，可以等于所述第一预设时长τ，也可以大于所述第一预设时长τ，本发明实施例不作具体限定。
可选地，根据所述子中间信号中第一预设时长计算得到的所述检测阈值，可以作为所述子中间信号中第二预设时长内信号的检测阈值，也可以作为所述子中间信号中下一个第二预设时长内信号的检测阈值，还可以第三预设时长内的信号的检测阈值，所述第三预设时长为下一段子中间信号中的一段时长，本发明实施例不作具体限定。
请参照图6，所述图6为本发明实施例提供的另一种高频射频干扰去除方法的流程示意图，如图6所示，所述方法包括：
601、获取脑电信号。
本发明实施例中，获取的所述脑电信号的采样频率不低于2kHz。
602、对所述脑电信号进行高通滤波从而获得中间信号，其中，所述中间信号为高通滤波后的包含高频射频干扰的信号。
本发明实施例中，正常脑电信号的频率低于100Hz，而高频射频干扰信号的频率高于10kHz以上，通过高通滤波的方法对所述脑电信号中的低频信号进行衰减，以得到主要为高频射频干扰信号的所述中间信号。
603、按照第一预设时长获取n个所述第一预设时长的所述中间信号的时域特征，根据所述时域特征得到检测阈值。
本发明实施例中，所述时域特征为所述中间信号的包络特征，根据所述中间信号的包络特征计算检测阈值。例如，根据所述包络特征计算检测阈值的步骤可以为：
在第一预设时长τ内，实时统计所述中间信号上包络和下包络的时域特征变化，根据所述上包络和所述下包络的时域变化计算检测阈值，例如，可以从所述中间信号中获取n个第一预设时长的中间信号，统计n个第一预设时长的中间信号的上包络特征和下包络特征，根据所述上包络特征和所述下包络特征计算所述检测阈值。可以根据如下公式确定所述检测阈值，
Figure PCTCN2017120370-appb-000001
其中，C为大于0的实数，i，n为正整数，τ为所述第一预设时长，Thd为所述检测阈值，f up(t)为上包络特征，f low(t)为下包络特征。
本发明实施例中，所述上包络f up(t)和所述下包络特征f low(t)可以根据如下公式获取，
f up(t)＝A×max(x(t-τ)，...，x(t))
f low(t)＝B×min(x(t-τ)，...，x(t))
其中，A、B为大于0的实数，x(t)为t时刻所述中间脑电信号的幅值。
在本发明实施例中，当i等于1时，所述第一预设时长对应的时间段为t 1-τ时刻至t 1时刻，当i等于2时，所述第一预设时长对应的时间段为t 2-τ时刻至t 2时刻，可选地，如图7所示，图7是本发明实施例提供的一种时间段关系示意图，所述t 1-τ时刻至t 1时刻与t 2-τ时刻至t 2时刻两个时间段可以含有相互重叠的部分，也可以是连续但不重叠的两个时间段，还可以是具有时间间隔的两个时间段，本发明实施例不作具体限制。
可选地，所述时域特征不局限于所述包络特征，所述时域特征还可以是所述中间信号幅值的平均值、方差、标准差，平均值与最大值的关系组合值，或 者特定值等，所述特征值可以是第二幅值最大值或者第三幅值最大值等，本发明实施例不作具体限定。
604、按照第二预设时长获取子中间信号，根据所述检测阈值确定所述子中间信号的信号类型，其中，不同的信号类型反映所述脑电信号受干扰的程度不同。
本发明实施例中，获取所述检测阈值之后，可以通过以下两种实施方式确定所述子中间信号的信号类型：
实施方式一：根据所述检测阈值得到第一阈值和第二阈值，其中，所述第一阈值是所述检测阈值乘以第一系数得到，所述第二阈值是所述检测阈值乘以第二系数得到，所述第一系数大于所述第二系数。或者，所述第一阈值是所述检测阈值加上第一常数得到，所述第二阈值是所述检测阈值加上第二常数得到，所述第一常数大于所述第二常数。应理解，上述两种获取第一阈值和第二阈值的方法仅作为举例，不能理解为具体限定。
若通过所述检测阈值乘以第一系数得到所述第一阈值，通过所述检测阈值乘以第二系数得到所述第二阈值之后，从所述中间信号中获取一段第二预设时长T的子中间信号，若所述子中间信号的幅值大于等于第一阈值，则确定所述子中间信号为干扰信号；若所述子中间信号的幅值小于第一阈值且大于等于第二阈值，则确定所述子中间信号为疑似干扰信号；若所述子中间信号的幅值小于第二阈值，则确定所述子中间信号为非干扰信号。
实施方式二：从所述中间信号中获取一段第二预设时长T的子中间信号，判断所述第二预设时长内所述子中间信号的幅值大于所述检测阈值的占比，若占比大于等于第一占比阈值，则确定所述子中间信号为干扰信号；若占比小于所述第一占比阈值，且大于等于第二占比阈值，则确定所述子中间信号为疑似干扰信号；若占比小于第二占比阈值，则确定所述子中间信号为非干扰信号。
可选地，所述第二预设时长T对应的时间段与n个第一预设时长τ对应的时间段可以完全相同，也可以只有部分重叠，所述第二预设时长T对应的时间段与所述n个第一预设时长τ对应的时间段还可以没有重叠部分，即所述第二预设时长T对应的时间段是n个第一预设时长τ对应的时间段之后的一个时间段。
605、根据确定的信号类型对所述子中间信号对应的脑电信号执行对应的处理。
本发明实施例中，若所述子中间信号为干扰信号，则所述子中间信号对应的子脑电信号为受高频射频干扰的脑电信号，将所述受高频射频干扰的脑电信号删除，或者，用所述受高频射频干扰的脑电信号出现之前的与所述受高频射频干扰的脑电信号时长相同的正常脑电信号替换所述干扰信号；若所述子中间信号为疑似干扰信号，则对应的子脑电信号为疑似受干扰的脑电信号，输出所述疑似受干扰的脑电信号，并输出所述疑似受干扰的脑电信号不可信的提示信息；或者，用所述疑似受干扰的脑电信号出现之前的与疑似受干扰的脑电信号时长相同的非干扰信号替换所述干扰信号；或者，对所述疑似受干扰的脑电信号进行弱化处理；若所述子中间信号为非干扰信号，则对应的子脑电信号为正常脑电信号，输出所述正常脑电信号。
可选地，对所述疑似干扰信号进行弱化处理的方式可以是所述疑似受干扰的脑电信号出现之前的正常脑电信号计算得到的参数替换该段的参数，也可以是计算前五次正常脑电信号对应参数的平均值替换该段参数，本发明实施例不作具体限定。
通过本发明实施例提供的高频射频干扰去除方法，通过对脑电信号在时域上进行分析，得到高频射频干扰信号的检测阈值，根据检测阈值对高频射频干扰信号进行分类，根据所述高频射频干扰信号的类别对脑电信号进行分类标记，从而能够对存在不同干扰类别的脑电信号进行不同的处理。
本发明实施例还提供一种高频射频干扰去除装置，该装置用于执行前述任一项所述的方法的。具体地，本实施例的装置包括：采集电路和处理器。
所述采集电路，用于采集脑电信号。具体的，用于采集采样频率不低于2kHz脑电信号。
所述处理器，具体地，所述处理器用于：
对所述脑电信号进行高通滤波从而得到中间脑电信号，其中，所述中间信号为高通滤波后的包含高频射频干扰的信号；
按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值；
按照第二预设时长获取第二脑电信号，根据所述检测阈值确定所述子脑电信号的信号类型，其中，不同的信号类型反映所述子脑电信号受干扰的程度不同；
根据确定的信号类型对所述子脑电信号执行对应的处理。
在本发明的另一实施例中提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序包括程序指令，所述程序指令被处理器执行时实现：
所述计算机可读存储介质可以是前述任一实施例所述的装置的内部存储单元，例如装置的硬盘或内存。所述计算机可读存储介质也可以是所述装置的外部存储设备，例如所述装置上配备的插接式硬盘，智能存储卡(Smart Media Card，SMC)，安全数字(Secure Digital，SD)卡，闪存卡(Flash Card)等。进一步地，所述计算机可读存储介质还可以既包括所述装置的内部存储单元也包括外部存储设备。所述计算机可读存储介质用于存储所述计算机程序以及所述装置所需的其他程序和数据。所述计算机可读存储介质还可以用于暂时地存储已经输出或者将要输出的数据。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本发明的范围。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，上述描述的装置的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口、装置或单元的间接耦合或通信连接，也可以是电的，机械的或其它的形式连接。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为 单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本发明实施例方案的目的。
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以是两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分，或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以权利要求的保护范围为准。

Claims (30)

  1. 一种高频射频干扰去除装置，其特征在于，包括滤波单元，高频信号提取单元，标记单元、采集单元以及处理器，其中，
    所述滤波单元，所述滤波单元的输入端接入所述原始脑电信号，用于对所述原始脑电信号进行滤波得到中间脑电信号；
    所述高频信号提取单元，所述高频信号提取单元的输入端与所述滤波单元的输出端连接，用于对所述中间脑电信号进行滤波，提取出所述中间脑电信号中的高频信号；
    所述标记单元，所述标记单元与所述高频信号提取单元的输出端连接，用于比较所述高频信号的幅值与比较阈值的大小，并根据比较结果对所述中间脑电信号进行分类标记；
    所述采集单元，所述采集单元的输入端与所述滤波单元的输出端连接，用于对进行分类标记后的中间脑电信号进行采样得到脑电信号，并将所述脑电信号输入到所述处理器；
    所述处理器，所述处理器的输入端与所述采集单元的输出端连接，所述处理器的输出端与所述标记单元的输入端连接，用于设置标记单元所用的比较阈值，并控制所述采集单元对所述中间脑电信号进行采样。
  2. 根据权利要求1所述的装置，其特征在于，所述滤波单元包括低通滤波器，所述低通滤波器用于对获取的原始脑电信号进行滤波以得到所述中间脑电信号，其中，所述原始脑电信号和所述中间脑电信号均为差分信号。
  3. 根据权利要求2所述的装置，其特征在于，所述高频信号提取单元包括第一放大器、高通滤波器以及第二运算放大器，其中，
    所述第一放大器，所述第一放大器的输入端连接所述滤波单元的输出端，对所述滤波单元输出的中间脑电信号进行放大，并将放大后的中间脑电信号转换为单端的第一中间脑电信号；
    所述高通滤波器，所述高通滤波器的输入端连接所述第一放大器的输出端，对所述第一中间脑电信号进行滤波，提取出所述第一中间脑电信号中的高频信号；
    所述第二放大器，所述第二放大器的输入端连接所述高通滤波器的输出端，对所述高频信号进行放大，输出所述高频信号经放大后得到的第二中间脑电信号。
  4. 根据权利要求3所述的装置，其特征在于，所述标记单元包括数模转换器、高速比较器以及开关模块，其中，
    所述数模转换器，所述数模转换器的输入端连接所述处理器的输出端，用于将所述处理器输出的所述比较阈值转换为参考电压；
    所述高速比较器，所述高速比较器的第一输入端连接所述数模转换器的输出端，第二输入端连接所述第二放大器的输出端，用于比较所述参考电压与所述第二中间脑电信号的幅值，并输出比较结果；
    所述开关模块，所述开关模块连接于所述采集单元，用于在所述比较结果表征所述高频信号的幅值大于所述参考电压时闭合，以使所述采集单元采样到零信号，从而对所述中间脑电信号进行分类标记。
  5. 根据权利要求4所述的装置，其特征在于，所述采集单元包括差分模数转换器，其中，
    所述差分模数转换器，所述差分模数转换器的输入端连接所述低通滤波器的输出端，用于对进行分类标记后的中间脑电信号进行采样得到脑电信号，并将所述脑电信号输入到所述处理器。
  6. 根据权利要求5所述的装置，其特征在于，所述采集单元还包括第三放大器，所述第三放大器的输入端连接所述滤波单元的输出端，输出端连接所述差分模数转换器的输入端，用于对所述中间脑电信号进行放大，增大所述中间脑电信号的幅值，输出所述中间脑电信号经放大后得到的第三中间脑电信号，其中，所述第三中间脑电信号为差分信号。
  7. 根据权利要求1所述的装置，其特征在于，所述采集单元包括第四放大器以及单端模数转换器，其中，
    所述第四放大器，所述第四放大器的输入端连接所述滤波单元的输出端，用于对所述中间脑电信号进行放大，并将所述中间脑电信号转换为单端的第四中间脑电信号；
    所述单端模数转换器，所述单端模数转换器的输入端连接所述第四放大器的输出端，所述单端模数转换器的输出端连接所述处理器，用于对进行分类标 记后的第四中间脑电信号进行采样得到脑电信号。
  8. 根据权利要求1所述的装置，其特征在于，所述处理器还用于对进行分类标记后的脑电信号执行与所述分类标记对应的操作处理。
  9. 一种高频射频干扰去除的方法，其特征在于，包括：
    获取脑电信号；
    对所述脑电信号进行高通滤波从而获得中间信号，其中，所述中间信号为高通滤波后的包含高频射频干扰的信号；
    按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值；
    按照第二预设时长获取子中间信号，根据所述检测阈值确定所述子中间信号的信号类型，其中，不同的信号类型反映所述脑电信号受干扰的程度不同；
    根据确定的信号类型对所述子中间信号对应的脑电信号执行对应的处理。
  10. 根据权利要求9所述的方法，其特征在于，所述时域特征为中间信号的包络特征。
  11. 根据权利要求10所述的方法，所述根据所述时域特征得到检测阈值的步骤具体为：
    根据所述包络特征自适应调节所述检测阈值。
  12. 根据权利要求10或11所述的方法，其特征在于，所述根据所述时域特征得到检测阈值的步骤具体为：
    在第一预设时长τ内，实时统计对比其信号上包络f up(t)和下包络f low(t)的时域特征变化；
    所述检测阈值根据如下公式获取，
    Figure PCTCN2017120370-appb-100001
    其中，i、n为正整数，τ为所述第一预设时长，f up(t)为上包络特征，f low(t)为下包络特征，Thd为所述检测阈值。
  13. 根据权利要求9所述的方法，其特征在于，
    按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值之后，所述方法还包括：
    将得到的检测阈值作为后续第三预设时长内的检测阈值，所述第三预设时 长大于所述第一预设时长。
  14. 根据权利要求9所述的方法，其特征在于，所述根据所述检测阈值确定所述子中间信号的信号类型，包括：
    根据对应的检测阈值得到第一阈值和第二阈值；
    若所述子中间信号的幅值大于等于第一阈值，则确定所述子中间信号为干扰信号；
    若所述子中间信号的幅值小于第一阈值且大于等于第二阈值，则确定所述子中间信号为疑似干扰信号；
    若所述子中间信号的幅值小于第二阈值，则确定所述子中间信号为非干扰信号。
  15. 根据权利要求14所述的方法，其特征在于，第一阈值为所述检测阈值乘以第一系数，所述第二阈值为所述检测阈值乘以第二系数，所述第一系数大于第二系数。
  16. 根据权利要求14所述的方法，其特征在于，所述子中间信号的幅值为对应第二预设时长内中间信号幅值的平均值、最大值、平均值与最大值的关系组合值，或者特定值。
  17. 根据权利要求9所述的方法，其特征在于，所述根据所述检测阈值确定所述子中间信号的信号类型，包括：
    判断所述第二预设时长内幅值大于所述检测阈值的子中间信号的占比；
    若占比大于等于第一占比阈值，则确定所述子中间信号为干扰信号；
    若占比小于所述第一占比阈值，且大于等于第二占比阈值，则确定所述子中间信号为疑似干扰信号；
    若占比小于第二占比阈值，则确定所述子中间信号为非干扰信号。
  18. 根据权利要求9所述的方法，其特征在于，所述根据所述检测阈值确定所述子中间信号的信号类型，包括：
    若所述子中间信号的幅值大于等于所述检测阈值，则确定所述子中间信号为干扰信号；
    若所述子中间信号的幅值小于所述检测阈值，则确定所述子中间信号为非干扰信号。
  19. 根据权利要求9所述的方法，其特征在于，所述根据确定的信号类型对 所述子中间信号对应的脑电信号执行对应的处理，包括：
    若所述子中间信号为干扰信号，则将所述子中间信号对应的脑电信号删除，或者，用所述干扰信号出现之前的与所述干扰信号时长相同的正常脑电信号替换所述干扰信号对应的脑电信号；
    若所述子中间信号为疑似干扰信号，则输出所述疑似干扰信号对应的脑电信号，并输出脑电信号不可信的提示信息；或者，用所述疑似干扰信号出现之前的与所述疑似干扰信号时长相同的正常脑电信号替换所述疑似干扰信号对应的脑电信号；或者，对所述疑似干扰信号对应的脑电信号进行弱化处理；
    若所述子中间信号为非干扰信号，则输出所述非干扰信号对应的脑电信号。
  20. 一种高频射频干扰去除装置，其特征在于，包括：
    采集电路，用于采集脑电信号；
    处理器，所述处理器用于执行以下步骤：
    对所述脑电信号进行高通滤波从而得到中间脑电信号，其中，所述中间信号为高通滤波后的包含高频射频干扰的信号；
    按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值；
    按照第二预设时长获取子中间脑电信号，根据所述检测阈值确定所述子中间信号的信号类型，其中，不同的信号类型反映所述脑电信号受干扰的程度不同；
    根据确定的信号类型对所述子中间信号对应的脑电信号执行对应的处理。
  21. 根据权利要求20所述的装置，其特征在于，所述时域特征为中间信号的包络特征。
  22. 根据权利要求21所述的装置，所述根据所述时域特征得到检测阈值的步骤具体为：
    根据所述包络特征自适应调节所述检测阈值。
  23. 根据权利要求21或22所述的装置，其特征在于，所述根据所述时域特征得到检测阈值的步骤具体为：
    在第一预设时长τ内，实时统计对比其信号上包络f up(t)和下包络f low(t)的时域特征变化；
    所述检测阈值根据如下公式获取，
    Figure PCTCN2017120370-appb-100002
    其中，i、n为正整数，τ为所述第一预设时长，f up(t)为上包络特征，f low(t)为下包络特征，Thd为所述检测阈值。
  24. 根据权利要求20所述的装置，其特征在于，
    按照第一预设时长获取所述中间信号的时域特征，根据所述时域特征得到检测阈值之后，所述方法还包括：
    将得到的检测阈值作为后续第三预设时长的检测阈值，所述第三预设时长大于所述第一预设时长。
  25. 根据权利要求20所述的装置，其特征在于，所述根据所述检测阈值确定所述子中间信号的信号类型，包括：
    根据对应的检测阈值得到第一阈值和第二阈值；
    在所述子中间信号的幅值大于等于第一阈值的情况下，确定所述子中间信号为干扰信号；
    在所述子中间信号的幅值小于第一阈值且大于等于第二阈值的情况下，确定所述子中间信号为疑似干扰信号；
    在所述子中间信号的幅值小于第二阈值的情况下，确定所述子中间信号为非干扰信号。
  26. 根据权利要求25所述的装置，其特征在于，第一阈值为所述检测阈值乘以第一系数，所述第二阈值为所述检测阈值乘以第二系数，所述第一系数大于第二系数。
  27. 根据权利要求25所述的装置，其特征在于，所述中间信号的幅值为对应第二预设时长内中间信号幅值的平均值、最大值、平均值与最大值的关系组合值，或者特定值。
  28. 根据权利要求20所述的装置，其特征在于，所述根据所述检测阈值确定所述子中间信号的信号类型，包括：
    判断所述第二预设时长内幅值大于所述检测阈值的子中间信号的占比；
    在占比大于等于第一占比阈值的情况下，确定所述子中间信号为干扰信号；
    在占比小于所述第一占比阈值，且大于等于第二占比阈值的情况下，确定所述子中间信号为疑似干扰信号；
    在占比小于所述第二占比阈值的情况下，确定所述子中间信号为非干扰信号。
  29. 根据权利要求20所述的装置，其特征在于，所述根据所述检测阈值确定所述子中间信号的信号类型，包括：
    在所述子中间信号的幅值大于等于所述检测阈值，确定所述子中间信号为干扰信号；
    在所述子中间信号的幅值小于所述检测阈值的情况下，确定所述子中间信号为非干扰信号。
  30. 根据权利要求20所述的装置，其特征在于，所述根据确定的信号类型对所述子中间信号对应的脑电信号执行对应的处理，包括：
    在所述子中间信号为干扰信号的情况下，将所述子中间信号对应的脑电信号删除，或者，用所述干扰信号出现之前的与所述干扰信号时长相同的正常脑电信号替换所述干扰信号对应的脑电信号；
    在所述子中间信号为疑似干扰信号的情况下，输出所述疑似干扰信号对应的脑电信号，并输出脑电信号不可信的提示信息；或者，用所述疑似干扰信号出现之前的与所述疑似干扰信号时长相同的正常脑电信号替换所述疑似干扰信号对应的脑电信号；或者，对所述疑似干扰信号对应的脑电信号进行弱化处理；
    在所述子中间信号为非干扰信号的情况下，输出所述非干扰信号对应的脑电信号。
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