CN203776899U - Brain signal acquisition and process equipment based on structured sparse compressed sensing - Google Patents
Brain signal acquisition and process equipment based on structured sparse compressed sensing Download PDFInfo
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- CN203776899U CN203776899U CN201320812942.0U CN201320812942U CN203776899U CN 203776899 U CN203776899 U CN 203776899U CN 201320812942 U CN201320812942 U CN 201320812942U CN 203776899 U CN203776899 U CN 203776899U
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Abstract
The utility model discloses brain signal acquisition and process equipment based on structured sparse compressed sensing. The defects that existing brain signal acquisition and process equipment is large in size, complex to operate and the like are overcome. According to the equipment, a brain signal sensor collects electroencephalogram signals of a human body, a signal processing circuit carries out amplifying, shaping and analog-digital converting on the electroencephalogram signals, a compressive sampling circuit carries out compressive sampling on the electroencephalogram signals processed through the signal processing circuit to obtain the sampled signals, a signal sending circuit sends the sampled signals, a signal receiving and reconstructing circuit receives, reconstructs and amplifies the sampled signals to obtain electroencephalogram data, and a data storing and analyzing circuit analyzes and obtains amplitude and frequency of the electroencephalogram data, compares the amplitude and the frequency of the electroencephalogram data with reference signals, and carries out data analysis according to the compared result to obtain the analyzed result. The brain signal acquisition and process equipment is small in size, easy to carry, easy to operate and capable of being accepted by wide households and hospitals.
Description
Technical field
This utility model relates to a kind of brain signal and obtains and treatment facility, relates in particular to a kind of brain signal based on structural sparse compressed sensing and obtains and treatment facility.
Background technology
Brain wave analysis is one of important means of psychosis clinical diagnosis.Electroencephalogram is by electroencephalography instrument, bio electricity faint brain self to be amplified to record to become a kind of curve chart, with the modern auxiliary examination method of one of assisted diagnosis disease.It to those who are investigated without any wound.
Occur that at present both at home and abroad multiple brain signal obtains and the equipment of processing, mainly comprised three kinds of Video-EEG, Active electroencephalogram (EEG) and Routine Eegs etc., and be widely used in practice medical science and research field.But these equipment prices are high, volume is larger, heavy dumb, operates more complicated.
Utility model content
Technical problem to be solved in the utility model is to overcome current brain signal to obtain and the deficiency such as the larger operation of the equipment volume of processing is more complicated.
In order to solve the problems of the technologies described above, this utility model provides a kind of brain signal based on structural sparse compressed sensing to obtain and treatment facility, comprise: brain signal sensor (1), signal processing circuit (2), Signal Compression sample circuit (3), signal sending circuit (4), signal receive reconfigurable circuit (5), data storage and analysis circuit (6), wherein:
Described brain signal sensor (1) gathers the EEG signals of human body;
Described signal processing circuit (2) to described EEG signals amplify, shaping and analog-to-digital conversion process;
Described compression sampling circuit (3), to carrying out compression sampling through described signal processing circuit (2) EEG signals after treatment, obtains sampled signal;
Described signal sending circuit (4) sends described sampled signal;
Described signal receives reconfigurable circuit (5) and receives described sampled signal, and described sampled signal is reconstructed and is amplified, and obtains eeg data;
The analysis of described data storage and analysis circuit (6) obtains amplitude and the frequency of described eeg data, and the amplitude of described eeg data and frequency and reference signal are compared, and carries out data analysis according to comparative result, obtains analysis result.
Preferably, described brain signal sensor (1) includes circular electrode brain electric conductance on line and nylon locking cap.
Preferably, described signal processing circuit (2) comprises signal amplification circuit (21) and analog to digital conversion circuit (22), wherein:
Described signal amplification circuit (21) amplifies and Shape correction described EEG signals;
The EEG signals of analog-digital conversion circuit as described (22) after to described amplification and Shape correction carried out analog digital conversion.
Preferably, described signal sending circuit (4) sends to described signal to receive reconfigurable circuit (5) described sampled signal by wireless transmission.
Preferably, described signal receives reconfigurable circuit (5) and comprises wireless receiving circuit (51), signal reconstruction circuit (52) and signal amplification circuit (53), wherein:
Described wireless receiving circuit (51) receives described sampled signal by wireless transmission method;
Described signal reconstruction circuit (52) is reconstructed described sampled signal;
The signal of described signal amplification circuit (53) after to described reconstruct amplifies, and obtains described eeg data.
Preferably, described data storage and analysis circuit (6) comprise input circuit (61) and data storage analysis circuit (62), wherein:
Described input circuit (61) receives described eeg data;
Described data storage analysis circuit (62) analysis obtains amplitude and the frequency of described eeg data, and the amplitude of described eeg data and frequency and reference signal are compared, and carries out data analysis according to comparative result, obtains analysis result.
Preferably, described data storage and analysis circuit (6) comprise display circuit (63), show described analysis result.
Compared with prior art, the application's embodiment provides a kind of lower-cost brain signal based on structural sparse compressed sensing to obtain and treatment facility.The application's embodiment volume is little, easily carries, simple to operate, can be accepted by vast family and hospital.The application's embodiment adopts that precision is high, noise is little, safety is good, the circular electrode brain electric conductance on line of the soft resistance to bending of cable material, by nylon locking cap, electrode is fixed on to a up-sampling EEG signals.Signal is by by amplifying circuit, shaping circuit, compression sampling and wireless transceiver circuit, signal reconstruction, amplifying circuit, and finally display waveform and data on computers, provide diagnostic result and health guidance.The diseases such as this equipment can diagnosing psychiatric disorders, epilepsy, the cerebral tumor, and can realize remote monitoring, not being subject to distance restraint, accuracy is high, and real-time is good.
Brief description of the drawings
Fig. 1 is that the brain signal based on structural sparse compressed sensing of the embodiment of the present application is obtained and the organigram for the treatment of facility.
Detailed description of the invention
Describe embodiment of the present utility model in detail below with reference to drawings and Examples, to this utility model, how application technology means solve technical problem whereby, and the implementation procedure of reaching technique effect can fully understand and implement according to this.Each feature in the embodiment of the present application and embodiment, the mutually combining under prerequisite of not conflicting mutually, all within protection domain of the present utility model.
Compressed sensing technology is a kind of new Sampling techniques, it is by the sparse characteristic of exploitation signal, under the condition much smaller than Nyquist (Nyquist) sample rate, obtain the discrete sample of signal by stochastical sampling, then by the perfect reconstruction signal of non-linear algorithm for reconstructing.
Compressed sensing technology is almost blank in the application of medical science neighborhood, but application prospect is expected very much.Via the remote monitoring of the physiological signal of wireless body area network, it is a main direction of studying in current medical communication field.Compressed sensing technology is applied to this field obvious advantage: when the sparse matrix that (1) is only 0 and 1 when employing element is sensing matrix, compressed sensing can reduce more than traditional wavelet compression techniques the loss of the energy of wireless body area network.The key problem that wireless body area network is studied and reduce energy loss.(2), from compression quality, compressed sensing and wavelet compression have similar compression ratio and Quality of recovery.Its general principles is first to gather original brain signal X, then generates arbitrarily a random perception matrix Φ, just can be obtained the signal Y=Φ X of compression by X and Φ.Signal Y passes to intelligent terminal and carries out remote transmission through the Internet via wireless body area network.Long-range, piece sparse Bayesian study (BSBL) algorithm recovers original brain signal X by signal Y and shared random perception matrix Φ.
As shown in Figure 1, the brain signal based on structural sparse compressed sensing of the embodiment of the present application is obtained and treatment facility, mainly comprises that brain signal sensor 1, signal processing circuit 2, Signal Compression sample circuit 3, signal sending circuit 4, signal receive reconfigurable circuit 5, data storage and analysis circuit 6.
Brain signal sensor 1 gathers the EEG signals of human body.Brain signal sensor 1 in the embodiment of the present application, brain signal sensor 1 includes circular electrode brain electric conductance on line and nylon locking cap, it adopts circular electrode brain electric conductance on line, its certainty of measurement is high, noise is little, safety is good, and the soft resistance to bending of cable material, is fixed on electrode on people's head by nylon locking cap.
Signal processing circuit 2 is connected with brain signal sensor 1, and the EEG signals that brain signal sensor 1 is gathered is amplified, shaping and modulus (A/D) conversion process, and EEG signals after treatment is sent to compression sampling circuit 3.
Compression sampling circuit 3 is connected with signal processing circuit 2, to carrying out compression sampling through signal processing circuit 2 EEG signals after treatment, obtains sampled signal and sends to signal sending circuit 4.
Signal sending circuit 4 is connected with compression sampling circuit 3, sends to signal to receive reconfigurable circuit 5 sampled signal by modes such as wireless transmission.
Signal receives reconfigurable circuit 5 and signal sending circuit 4 and is connected by the mode such as wireless, the sampled signal that reception signal sending circuit 4 sends by wireless mode; Receiving after sampled signal, sampled signal is reconstructed and is amplified, obtaining eeg data; Eeg data is transferred to data storage and analysis circuit 6.
Data storage receives reconfigurable circuit 5 with analysis circuit 6 and signal and is connected, receive signal and receive the eeg data that reconfigurable circuit 5 transmits, analyze the amplitude and the frequency that obtain eeg data, and the amplitude of eeg data and frequency and reference signal are compared, carry out data analysis according to comparative result, and display analysis result.
As shown in Figure 1, the signal processing circuit 2 in the embodiment of the present application comprises signal amplification circuit 21 and analog to digital conversion circuit 22.Signal amplification circuit 21 is connected with brain signal sensor 1, and the EEG signals that brain signal sensor 1 is gathered is amplified and shaping.Brain signal is a kind of bio signal, comparatively faint, affected by noise and testee brain light exercise, after amplifying, can improve signal intensity.Analog to digital conversion circuit 22 is connected with signal amplification circuit 21 and compression sampling circuit 3, to signal amplification circuit 21 amplify and Shape correction after EEG signals carry out analog digital conversion, and the EEG signals after analog digital conversion is sent to compression sampling circuit 3.
In the application's embodiment, Signal Compression sample circuit 3 not only reduces the requirement of sample frequency to hardware with respect to traditional nyquist sampling, also reduced sampling time and sampled data, due to the minimizing of sampled data, the memory space needing and transmission time also reduce accordingly.
In the application's embodiment, signal sending circuit 4 adopts remote wireless transmission or short distance Bluetooth transmission, has realized the remote monitoring of the physiological signal of wireless body area network.
Signal sending circuit 4 and signal receive reconfigurable circuit 5 and adopt remote wireless transmission or short distance Bluetooth transmission, can realize the remote monitoring of the physiological signal of wireless body area network, and this feature makes native system more flexible, is subject to distance limit less.Such as, tested object can be located in bedroom, parlor etc., by the wireless remote location such as hospital, clinic that sends the data to.
As shown in Figure 1, the reception of the signal in the embodiment of the present application reconfigurable circuit 5 comprises wireless receiving circuit 51, signal reconstruction circuit 52 and signal amplification circuit 53.Wireless receiving circuit 51 is connected with signal sending circuit 4 by wireless transmission method, receives the sampled signal that signal sending circuit 4 sends by wireless mode.Signal reconstruction circuit 52 is connected with wireless receiving circuit 51, and sampled signal is reconstructed.Signal amplification circuit 53 is connected with signal reconstruction circuit 52, and the signal that 52 reconstruct obtain to signal reconstruction circuit amplifies, and to make up the loss of signal in transmitting procedure, obtains eeg data.
As shown in Figure 1, the data storage in the embodiment of the present application and analysis circuit 6 comprise input circuit 61, data storage analysis circuit 62 and display circuit 63 etc.Input circuit 61 receives reconfigurable circuit 5 with signal and is connected, and the eeg data that reception signal reception reconfigurable circuit 5 transmits also inputs to data storage analysis circuit 62.Data storage analysis circuit 62 is connected with input circuit 61, collect historical data storage, for data brain electricity analytical, statistics provide reference and support, analyze the amplitude and the frequency that obtain eeg data, and the amplitude of eeg data and frequency and reference signal are compared, carry out data analysis according to comparative result, and obtain analysis result.Data storage analysis circuit 62 adopts the technology such as Apache, MySQL, PHP to realize, and the functions such as chart displaying can be provided, and has complied with the development trend of the bioinformatics based on Web.Display circuit 63 is connected with data storage analysis circuit 62, and video data storage analysis circuit 62 carries out according to comparative result the analysis result that data analysis obtains.
The application's embodiment is in the time of application, and the head that can circular electrode be fixed on to people by nylon locking cap is upper, gathers the EEG signals of human body.Signal processing circuit to EEG signals amplify, shaping and analog-to-digital conversion process, and signal after treatment is sent to compression sampling circuit.Compression sampling circuit, to carrying out compression sampling through signal processing circuit EEG signals after treatment, obtains sampled signal and sends to signal sending circuit.Signal sending circuit sends to signal to receive reconfigurable circuit sampled signal by modes such as wireless transmission.Signal receives reconfigurable circuit and receives after sampled signal, and sampled signal is reconstructed and is amplified, and obtains eeg data.Data storage and analysis circuit compare the amplitude of eeg data and frequency and reference signal, carry out brain electricity analytical according to comparative result, and display analysis result.
Compared with prior art, the application's embodiment relies on the structural sparse compressive sensing theory developing rapidly in recent years to carry out compression sampling to signal, so not only reduces the requirement of sample frequency to hardware, has also reduced sampling time and sampled data.Owing to having reduced sampled data, therefore needed memory space and transmission time also reduce accordingly.Compressed sensing can reduce more than traditional wavelet compression techniques the loss of the energy of wireless body area network, utilizes the original EEG signals of piece sparse Bayesian study BSBL algorithm reconstruct at receiving terminal.Based on receiving more accurately EEG signals than existing method at signal receiving end after this theory long-distance transmissions.When this utility model energy Long term Monitoring and length, guard, and also have the function of playback, can be to EEG signals accurate analysis.
The application's embodiment has the features such as cost is low, volume is little, energy remote monitoring, can even be widely used at average family at small-middle hospital.Current social operating pressure is large, environmental pollution is serious, brain diseases comprises that the numbers of falling ill such as mental sickness, epilepsy, the cerebral tumor rise year by year, serious harm people physical and mental health, this product can prevent, diagnose relevant disease effectively, there is certain facilitation for social medical treatment, promote social development.
Although the disclosed embodiment of this utility model as above, the embodiment that described content only adopts for ease of understanding this utility model, not in order to limit this utility model.Those of skill in the art under any this utility model; do not departing under the prerequisite of the disclosed spirit and scope of this utility model; can in the form of implementing and details, carry out any amendment and variation; but scope of patent protection of the present utility model, still must be as the criterion with the scope that appending claims was defined.
Claims (7)
1. the brain signal based on structural sparse compressed sensing is obtained and treatment facility, it is characterized in that, this equipment comprises: brain signal sensor (1), signal processing circuit (2), Signal Compression sample circuit (3), signal sending circuit (4), signal receive reconfigurable circuit (5), data storage and analysis circuit (6), wherein:
Described brain signal sensor (1) gathers the EEG signals of human body;
Described signal processing circuit (2) to described EEG signals amplify, shaping and analog-to-digital conversion process;
Described compression sampling circuit (3), to carrying out compression sampling through described signal processing circuit (2) EEG signals after treatment, obtains sampled signal;
Described signal sending circuit (4) sends described sampled signal;
Described signal receives reconfigurable circuit (5) and receives described sampled signal, and described sampled signal is reconstructed and is amplified, and obtains eeg data;
The analysis of described data storage and analysis circuit (6) obtains amplitude and the frequency of described eeg data, and the amplitude of described eeg data and frequency and reference signal are compared, and carries out data analysis according to comparative result, obtains analysis result.
2. equipment according to claim 1, is characterized in that, described brain signal sensor (1) includes circular electrode brain electric conductance on line and nylon locking cap.
3. equipment according to claim 1, is characterized in that, described signal processing circuit (2) comprises signal amplification circuit (21) and analog to digital conversion circuit (22), wherein:
Described signal amplification circuit (21) amplifies and Shape correction described EEG signals;
The EEG signals of analog-digital conversion circuit as described (22) after to described amplification and Shape correction carried out analog digital conversion.
4. equipment according to claim 1, is characterized in that, described signal sending circuit (4) sends to described signal to receive reconfigurable circuit (5) described sampled signal by wireless transmission.
5. equipment according to claim 1, it is characterized in that, described signal receives reconfigurable circuit (5) and comprises wireless receiving circuit (51), signal reconstruction circuit (52) and signal amplification circuit (53), wherein:
Described wireless receiving circuit (51) receives described sampled signal by wireless transmission method;
Described signal reconstruction circuit (52) is reconstructed described sampled signal;
The signal of described signal amplification circuit (53) after to described reconstruct amplifies, and obtains described eeg data.
6. equipment according to claim 1, is characterized in that, described data storage and analysis circuit (6) comprise input circuit (61) and data storage analysis circuit (62), wherein:
Described input circuit (61) receives described eeg data;
Described data storage analysis circuit (62) analysis obtains amplitude and the frequency of described eeg data, and the amplitude of described eeg data and frequency and reference signal are compared, and carries out data analysis according to comparative result, obtains analysis result.
7. equipment according to claim 6, is characterized in that, described data storage and analysis circuit (6) comprise display circuit (63), show described analysis result.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201320812942.0U CN203776899U (en) | 2013-11-29 | 2013-11-29 | Brain signal acquisition and process equipment based on structured sparse compressed sensing |
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| CN201320812942.0U CN203776899U (en) | 2013-11-29 | 2013-11-29 | Brain signal acquisition and process equipment based on structured sparse compressed sensing |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108446021A (en) * | 2018-02-28 | 2018-08-24 | 天津大学 | Application process of the P300 brain-computer interfaces in smart home based on compressed sensing |
| CN109475737A (en) * | 2016-07-13 | 2019-03-15 | 特拉维夫大学拉莫特有限公司 | New bio signal acquisition method and algorithm for wearable device |
| CN109523486A (en) * | 2018-11-22 | 2019-03-26 | 合肥工业大学 | Based on the multichannel brain electric signal reconfiguring method of robust compressed sensing under noise circumstance |
| CN110251083A (en) * | 2019-06-20 | 2019-09-20 | 深圳大学 | A kind of processing method, system and the storage medium of the location data of epileptic focus |
-
2013
- 2013-11-29 CN CN201320812942.0U patent/CN203776899U/en not_active Expired - Fee Related
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109475737A (en) * | 2016-07-13 | 2019-03-15 | 特拉维夫大学拉莫特有限公司 | New bio signal acquisition method and algorithm for wearable device |
| CN108446021A (en) * | 2018-02-28 | 2018-08-24 | 天津大学 | Application process of the P300 brain-computer interfaces in smart home based on compressed sensing |
| CN108446021B (en) * | 2018-02-28 | 2020-03-17 | 天津大学 | Application method of P300 brain-computer interface in intelligent home based on compressed sensing |
| CN109523486A (en) * | 2018-11-22 | 2019-03-26 | 合肥工业大学 | Based on the multichannel brain electric signal reconfiguring method of robust compressed sensing under noise circumstance |
| CN109523486B (en) * | 2018-11-22 | 2021-04-02 | 合肥工业大学 | Multi-channel electroencephalogram signal reconstruction method based on robust compressed sensing in noise environment |
| CN110251083A (en) * | 2019-06-20 | 2019-09-20 | 深圳大学 | A kind of processing method, system and the storage medium of the location data of epileptic focus |
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Granted publication date: 20140820 Termination date: 20151129 |