CN105534520A - Multi-parameter family-type brain cognition detection method, device and system - Google Patents
Multi-parameter family-type brain cognition detection method, device and system Download PDFInfo
- Publication number
- CN105534520A CN105534520A CN201510876010.6A CN201510876010A CN105534520A CN 105534520 A CN105534520 A CN 105534520A CN 201510876010 A CN201510876010 A CN 201510876010A CN 105534520 A CN105534520 A CN 105534520A
- Authority
- CN
- China
- Prior art keywords
- data
- data flow
- skin
- reactance
- eye movement
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
-
- 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
- A61B5/389—Electromyography [EMG]
Abstract
The invention provides a multi-parameter family-type brain cognition detection method, device and system. The method comprises the following steps: receiving an electroencephalogram signal data flow, an electronystagmogram data flow and a skin reactance data flow; conducting primary processing on the electroencephalogram signal data flow, the electronystagmogram data flow and the skin reactance data flow, and transmitting the data flows obtained from the primary processing to a pre-trained support vector machine; and analyzing the data flows obtained from the primary processing by virtue of the support vector machine, so as to obtain brain cognition states, wherein the brain cognition states include a normal state, a to-be-determined state and an abnormal state. The technical scheme provided by the invention has the advantages of being portable and high in detection accuracy.
Description
Technical field
The present invention relates to home medical equipment field, particularly relate to a kind of multiparameter family brain cognition detection method, device.
Background technology
Brain cognition comprises the cerebral deficits such as attention deficit, hyperkinetic syndrome class brain cognitive state; existing brain cognitive state is thought by Gene Handling at present; brought out by environmental factors again and to cause; the symptom of most brain cognition shows gradually after baby due; general guardian can recognize dystropy at about two years old, and this exception can develop gradually.
The development of mobile Internet, the Urban-rural Difference between every field is reduced, and brain cognition obtains concern too.Its Main Patterns is by developing various mobile platform software APP, the cognitive relevant APP of money more than 130 of brain of each platform current that investigation AutismSpeaks website is included, its major function concentrates on: cause people to the understanding of brain cognitive state, prevention brain is cognitive, carries out training, early discovery etc. from languageand behavior.In this money more than 130 APP, what lay claim to clear and definite scientific basis only has 1/4, great majority be play, picture and text are main training form, in the APP of early discovery type be test exercise question, instrument helps to find that there is the cognitive sign of brain.
In the scheme realizing prior art, find that the scheme of prior art has following technical problem:
The APP of mobile platform test exercise question, tool helps users detect brain cognition, and mobile platform APP can realize portablely detecting anywhere or anytime.But this mode subjectivity is too strong, majority needs user to carry out the judgement of subjectivity according to self knowledge, detects poor repeatability, there is practice effect and psychological effect, also do not have scientific research to support this test, be difficult to play practical function.
Summary of the invention
There is provided a kind of multiparameter family brain cognition detection method, described multiparameter family brain cognition detection method adopts the method for multiparameter and support vector machine to detect the state of brain cognition, and whole detection is without the need to artificial judgement, so it has the strong advantage of objectivity.
First aspect, provide a kind of multiparameter family brain cognition detection method, described method comprises the steps:
Receive EEG signals data flow, eye movement data stream and skin reactance data flow;
After described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, by the data flow after preliminary treatment to the good support vector machine of training in advance;
By support vector machine, the data-flow analysis after preliminary treatment is obtained to the state of brain cognition;
Described brain cognitive state comprises: normal condition, state to be confirmed and abnormality.
Optionally, described concrete to described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, comprising:
Carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow makes described EEG signals data flow, eye movement data stream and skin reactance data flow become synchronous data flow.
Optionally, described method also comprised before preliminary treatment:
The data deletion of first threshold scope will be exceeded in described EEG signals data flow, the data deletion of Second Threshold scope will be exceeded in described eye movement data stream, by the data deletion more than the 3rd threshold range in described skin reactance data flow, the data of deleting in EEG signals data flow the first fitting data is filled, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled.
Wherein, described first fitting data is within the scope of described first threshold, and described second fitting data is within the scope of described Second Threshold, and described 3rd fitting data is in described 3rd threshold range.
Second aspect, provide a kind of multiparameter family brain cognition detection device, described device comprises:
Receiving element, for receiving EEG signals data flow, eye movement data stream and skin reactance data flow;
Data processing unit, for after described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow;
Transmitting element, for by the data flow after preliminary treatment to the good support vector machine of training in advance;
Analytic unit, for obtaining the state of brain cognition to the data-flow analysis after preliminary treatment by support vector machine;
Described brain cognitive state comprises: normal condition, state to be confirmed and abnormality.
Optionally, described data processing unit is concrete, for:
Carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow makes described EEG signals data flow, eye movement data stream and skin reactance data flow become synchronous data flow.
Optionally, described device also comprises:
Delete cells, for the data deletion by exceeding first threshold scope in described EEG signals data flow, will exceed the data deletion of Second Threshold scope, by the data deletion more than the 3rd threshold range in described skin reactance data flow in described eye movement data stream;
Fitting unit, for filling the data of deleting in EEG signals data flow the first fitting data, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled.
Wherein, described first fitting data is within the scope of described first threshold, and described second fitting data is within the scope of described Second Threshold, and described 3rd fitting data is in described 3rd threshold range.
The third aspect, provide a kind of multiparameter family brain cognition detection system, described system comprises: eeg signal acquisition device, eye harvester, skin pricktest impedance recording equipment, DSP date processing box and intelligent terminal; Wherein,
Eeg signal acquisition device, for gathering EEG signals data flow, and by this EEG signals data flow;
Eye harvester, for gathering eye movement data stream, and sends this eye movement data stream;
Skin pricktest impedance recording equipment, for gathering skin reactance data flow, and by this skin reactance data flow;
DSP date processing box, for receiving EEG signals data flow, eye movement data stream and skin reactance data flow, after described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, by the data flow intelligent terminal after preliminary treatment;
Intelligent terminal, for obtaining the state of brain cognition to the data-flow analysis after preliminary treatment by support vector machine.
Optionally, described DSP date processing box, specifically, described EEG signals data flow, eye movement data stream and skin reactance data flow is made to become synchronous data flow for carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow.
Optionally, described DSP date processing box, also for, the data deletion of first threshold scope will be exceeded in described EEG signals data flow, the data deletion of Second Threshold scope will be exceeded, by the data deletion more than the 3rd threshold range in described skin reactance data flow in described eye movement data stream; For filling the data of deleting in EEG signals data flow the first fitting data, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled.
Wherein, described first fitting data is within the scope of described first threshold, and described second fitting data is within the scope of described Second Threshold, and described 3rd fitting data is in described 3rd threshold range.
Fourth aspect, provides a kind of intelligent terminal, and described intelligent terminal comprises above-mentioned multiparameter family brain cognition detection device.
The multiparameter family brain cognition detection method of stating provided according to each embodiment and device carry out automatic decision brain cognitive state by multiple parameters such as brain electricity initial data, eye movement data and skin pricktest impedance datas, so its to have objectivity strong, reproducible, detect advantage accurately.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
The flow chart of the multiparameter family brain cognition detection method that Fig. 1 provides for the present invention first better embodiment;
The structural representation of the eeg signal acquisition device that Fig. 2 provides for the present invention first better embodiment;
Fig. 3 be multiparameter family brain cognition detection method in the present invention second better embodiment flow chart;
The structural representation of multiparameter family brain cognition detection device of Fig. 4 for providing in the present invention the 3rd better embodiment;
The structural representation of the parameter family brain cognition detection system that Fig. 5 provides for the present invention the 4th better embodiment;
The app interface schematic diagram that Fig. 6 provides for the present invention the 4th better embodiment;
The structured flowchart of the parameter family brain cognition detection system that Fig. 7 provides for the present invention the 4th better embodiment.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Consult Fig. 1, a kind of multiparameter family brain cognition detection method that Fig. 1 the present invention first better embodiment provides, the method can be completed by intelligent terminal, this intelligent terminal includes but not limited to: the home-use portable intelligent device such as mobile phone, panel computer, personal computer, the method as shown in Figure 1, comprises the steps:
Step S101, reception EEG signals data flow, eye movement data stream and skin reactance data flow;
Above-mentioned steps midbrain electrical signal data stream can be gathered by eeg signal acquisition device, then by EEG signals data flow that short-range communication module transmission collects; Above-mentioned short-range communication module includes but not limited to: the short-range communication module such as WIFI, bluetooth, above-mentioned eeg signal acquisition device as shown in Figure 2, comprise: multiple brain wave acquisition electrode 301, reference electrode 302, rechargeable battery 303, fixing head hoop 304 and bluetooth module; Wherein, the material of brain wave acquisition electrode 301 can be the one of the materials such as Ag or AgAl, rustless steel or gold, can be directly connected in contact point, not need conducting resinl in use.The quantity prioritizing selection of brain wave acquisition electrode 301 3, be used for gathering EEG signals signal, the signal collected is the EEG signals data flow of 10 μ V magnitudes, and brain wave acquisition point is positioned at above forehead left eye or right eye.Reference electrode 302, what this material with reference to electric level 302 and brain wave acquisition electrode 301 adopted is identical electrode material, after can being arranged on ear with reference to the position of electric level or be clipped on ear-lobe.Rechargeable battery 303 can be lithium ion battery, lithium polymer battery, biological fuel cell or radio frequency powered device, biological fuel cell provides electric energy by the glucose of enzyme catalysis self, radio frequency powered device is undertaken by coil in vivo responding to the one produced in electric energy, the position of bluetooth module can be arranged on the position of rechargeable battery 303, certainly also this position can be adjusted in actual applications, this bluetooth module needs the DC voltage of 3.3V; The model of bluetooth module can select bluetooth 4.0 integrated chip of SM01A.Fixing head hoop 304 be by a kind of arbitrarily flexible, there is good plasticity, softness, comfortable, harmless to human non-toxic macromolecular material make, the head hoop of this material can make whole brain wave acquisition device be fixed on same position, the signal of what brain wave acquisition electrode was recorded to is same position, head hoop can have the flexible of certain limit simultaneously, make the head hoop only needing large, medium and small three kinds of sizes, just can dress at the head of all normal persons and use.
The eye that eye movement data stream in above-mentioned steps can adopt Tobii company to provide moves the solution of harvester, the TobiiGlasses2 eye tracker adopted can comprise two parts composition, wear part---glasses and recording equipment can be the one among the senior version of TobiiGlassesLiveView version, TobiiGlassesLiveView wireless version and TobiiGlasses three kinds of versions.Glasses have a Radix Rumicis high definition scene camera, resolution is 1920 × 1080, has 4 eyes and moves video camera, the gyroscope of outfit and acceleration transducer etc.
In above-mentioned steps, skin reactance data flow can be measured by skin pricktest impedance recording equipment, and this skin pricktest impedance recording equipment comprises two finger cot type electrodes and connection cord, and cable can be the one in the materials such as copper, aluminum, outside insulating barrier plastic wraps.
Step S102, to after described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, by the data flow after preliminary treatment to the good support vector machine of training in advance;
Can have multiple to the mode that EEG signals data flow, eye movement data stream and skin reactance data flow carry out preliminary treatment in above-mentioned steps 102, the processing mode of the present invention first better embodiment to above-mentioned data flow does not limit, its concrete processing mode see the description in the present invention second better embodiment, can repeat no more here.
Step S103, by support vector machine, the data-flow analysis after preliminary treatment is obtained to the state of brain cognition.
Brain cognitive state in above-mentioned steps includes but not limited to: normal condition, state to be confirmed and abnormality, and wherein, normal condition represents normal by brain cognition detection discovery brain activity; State to be confirmed can represent, the state of the brain cognition now detected is between abnormality and normal condition, and abnormality represents abnormal by brain cognition detection discovery brain activity.
In above-mentioned steps, the training process of support vector machine can adopt following scheme to train, (can certainly be such as other quantity by support vector machine to 50, such as 100 or 20) the cognitive abnormal personnel of brain carry out parameter acquisition, this 50 brains cognitive abnormal personnel are through and diagnose clinically, therefore, the parameter collected all carrys out the cognitive abnormal personnel of brain, and parameters has the cognitive abnormal distinctive feature of brain; Be input in support vector machine by these training datas, training obtains characteristic vector.Certainly, in the present invention first better embodiment, other mode can also be adopted to carry out Training Support Vector Machines, and the present invention first better embodiment does not limit the concrete training method of above-mentioned support vector machine.
The technical scheme that the present invention first better embodiment provides, EEG signals data flow is received by portable family checkout equipment, eye movement data stream and these three data flow of skin reactance data flow, then to three Data Stream Processing, then the data after process are sent to support vector machine and carry out analyzing the result that namely can obtain corresponding brain cognitive state timely, because this technical scheme is analyzed by support vector machine, whole analysis all can complete within the family, so it has portable, advantage easily, and whole detection completes automatically by equipment, user is not needed to carry out subjective judgement, so it has the strong advantage of objectivity.And above-mentioned data are data flow, it belongs to the detection of setting-up time section, can improve the accuracy of detection.
Consult Fig. 3, a kind of multiparameter family brain cognition detection method that Fig. 3 the present invention second better embodiment provides, the method can be completed by intelligent terminal, this intelligent terminal includes but not limited to: the home-use portable intelligent device such as mobile phone, panel computer, personal computer, the method as shown in Figure 3, comprises the steps:
Step S201, reception EEG signals data flow, eye movement data stream and skin reactance data flow;
Above-mentioned steps midbrain electrical signal data stream can be gathered by eeg signal acquisition device, then by EEG signals data flow that short-range communication module transmission collects; Above-mentioned short-range communication module includes but not limited to: the short-range communication module such as WIFI, bluetooth, above-mentioned eeg signal acquisition device as shown in Figure 2, comprise: multiple brain wave acquisition electrode 301, reference electrode 302, rechargeable battery 303, fixing head hoop 304 and bluetooth module; Wherein, the material of brain wave acquisition electrode 301 can be the one of the materials such as Ag or AgAl, rustless steel or gold, can be directly connected in contact point, not need conducting resinl in use.The quantity prioritizing selection of brain wave acquisition electrode 301 3, be used for gathering EEG signals signal, the signal collected is the EEG signals data flow of 10 μ V magnitudes, and brain wave acquisition point is positioned at above forehead left eye or right eye.Reference electrode 302, what this material with reference to electric level 302 and brain wave acquisition electrode 301 adopted is identical electrode material, after can being arranged on ear with reference to the position of electric level or be clipped on ear-lobe.Rechargeable battery 303 can be lithium ion battery, lithium polymer battery, biological fuel cell or radio frequency powered device, biological fuel cell provides electric energy by the glucose of enzyme catalysis self, radio frequency powered device is undertaken by coil in vivo responding to the one produced in electric energy, the position of bluetooth module can be arranged on the position of rechargeable battery 303, certainly also this position can be adjusted in actual applications, this bluetooth module needs the DC voltage of 3.3V; The model of bluetooth module can select bluetooth 4.0 integrated chip of SM01A.Fixing head hoop 304 be by a kind of arbitrarily flexible, there is good plasticity, softness, comfortable, harmless to human non-toxic macromolecular material make, the head hoop of this material can make whole brain wave acquisition device be fixed on same position, the signal of what brain wave acquisition electrode was recorded to is same position, head hoop can have the flexible of certain limit simultaneously, make the head hoop only needing large, medium and small three kinds of sizes, just can dress at the head of all normal persons and use.
The eye that eye movement data stream in above-mentioned steps can adopt Tobii company to provide moves the solution of harvester, the TobiiGlasses2 eye tracker adopted can comprise two parts composition, wear part---glasses and recording equipment can be the one among the senior version of TobiiGlassesLiveView version, TobiiGlassesLiveView wireless version and TobiiGlasses three kinds of versions.Glasses have a Radix Rumicis high definition scene camera, resolution is 1920 × 1080, has 4 eyes and moves video camera, the gyroscope of outfit and acceleration transducer etc.
In above-mentioned steps, skin reactance data flow can be measured by skin pricktest impedance recording equipment, and this skin pricktest impedance recording equipment comprises two finger cot type electrodes and connection cord, and cable can be the one in the materials such as copper, aluminum, outside insulating barrier plastic wraps.
Step S202, different disposal is carried out to described EEG signals data flow, eye movement data stream and skin reactance data flow make described EEG signals data flow, eye movement data stream and skin reactance data flow become synchronous data flow, by synchronous data flow to the good support vector machine of training in advance;
In above-mentioned steps S202, synchronous process is carried out to data and make described EEG signals data flow, the specifically synchronous mode that eye movement data stream and skin reactance data flow become synchronous data flow can have multiple, such as, in an embodiment of the present invention second better embodiment, obtain time started 1 and the end time 1 of EEG signals data flow, the time started 2 of eye movement data stream and end time 2, the time started 3 of skin reactance data flow and end time 3, extract the time started the latest in 3 time starteds, extract the end time the earliest time in 3 end times, here the hypothesis time started 3 is the time started the latest, end time 2 is earliest finish time, in eeg data stream, then intercept the data flow between time started 3 and end time 2, the data flow between time started 3 and end time 2 is intercepted in eye movement data stream, the data flow between time started 3 and end time 2 is intercepted in skin reactance data flow.
Certain above-mentioned synchronous mode can also adopt other mode, such as in an embodiment of the present invention second better embodiment, directly can obtain a setting-up time section, the data flow of setting-up time section is intercepted in eeg data stream, in eye movement data stream, intercept the data flow of setting-up time section, in skin reactance data flow, intercept the data flow of setting-up time section.
Step S203, by support vector machine, the data-flow analysis after preliminary treatment is obtained to the state of brain cognition.
Brain cognitive state in above-mentioned steps includes but not limited to: normal condition, state to be confirmed and abnormality, and wherein, normal condition represents normal by brain cognition detection discovery brain activity; State to be confirmed can represent, the state of the brain cognition now detected is between abnormality and normal condition, and abnormality represents abnormal by brain cognition detection discovery brain activity.
In above-mentioned steps, the training process of support vector machine can adopt following scheme to train, (can certainly be such as other quantity by support vector machine to 50, such as 100 or 20) the cognitive abnormal personnel of brain carry out parameter acquisition, this 50 brains cognitive abnormal personnel are through and diagnose clinically, therefore, the parameter collected all carrys out the cognitive abnormal personnel of brain, and parameters has the cognitive abnormal distinctive feature of brain; Be input in support vector machine by these training datas, training obtains characteristic vector.Certainly, in the present invention second better embodiment, other mode can also be adopted to carry out Training Support Vector Machines, and the present invention second better embodiment does not limit the concrete training method of above-mentioned support vector machine.
The technical scheme that the present invention second better embodiment provides, EEG signals data flow is received by portable family checkout equipment, eye movement data stream and these three data flow of skin reactance data flow, then to three Data Stream Processing, then the data after process are sent to support vector machine and carry out analyzing the result that namely can obtain corresponding brain cognitive state timely, because this technical scheme is analyzed by support vector machine, whole analysis all can complete within the family, so it has portable, advantage easily, and whole detection completes automatically by equipment, user is not needed to carry out subjective judgement, so it has the strong advantage of objectivity.And above-mentioned data are data flow, it belongs to the detection of setting-up time section, can improve the accuracy of detection.
Optionally, in the method that the present invention second better embodiment provides, before step S202, can also comprise after step S201:
The data deletion of first threshold scope will be exceeded in EEG signals data flow, the data deletion of Second Threshold scope will be exceeded in eye movement data stream, by in skin reactance data flow more than the data deletion of the 3rd threshold range, the data of deleting in EEG signals data flow the first fitting data is filled, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled.
Wherein, above-mentioned first fitting data is within the scope of first threshold, and the second fitting data is within the scope of Second Threshold, and the 3rd fitting data is in the 3rd threshold range.
Occurrence the present invention second better embodiment of above-mentioned fitting data does not limit, such as, in an embodiment of the present invention second preferred mode, the meansigma methods of all values in EEG signals data flow can be adopted as the first fitting data, second fitting data or the 3rd fitting data also can adopt the mode of meansigma methods to fill, certainly in actual applications, also other data can be adopted to fill, such as in another embodiment of the present invention second better embodiment, can adopt and be used as fitting data with the immediate value of these deletion data (being in threshold range).
Said method adopts the mode of data filtering and data fitting to flow to row relax to data, makes some non-essential data deletions, and adopts effective data to fill erasing time point, can increase the accuracy of detection like this.
Consult Fig. 4, a kind of multiparameter family brain cognition detection device 400 that Fig. 4 provides for the present invention the 3rd better embodiment, said apparatus can comprise:
Receiving element 401, for receiving EEG signals data flow, eye movement data stream and skin reactance data flow;
Above-mentioned receiving element 401 midbrain electrical signal data stream can be gathered by eeg signal acquisition device, then by EEG signals data flow that short-range communication module transmission collects; Above-mentioned short-range communication module includes but not limited to: the short-range communication module such as WIFI, bluetooth, above-mentioned eeg signal acquisition device as shown in Figure 2, comprise: multiple brain wave acquisition electrode 301, reference electrode 302, rechargeable battery 303, fixing head hoop 304 and bluetooth module; Wherein, the material of brain wave acquisition electrode 301 can be the one of the materials such as Ag or AgAl, rustless steel or gold, can be directly connected in contact point, not need conducting resinl in use.The quantity prioritizing selection of brain wave acquisition electrode 301 3, be used for gathering EEG signals signal, the signal collected is the EEG signals data flow of 10 μ V magnitudes, and brain wave acquisition point is positioned at above forehead left eye or right eye.Reference electrode 302, what this material with reference to electric level 302 and brain wave acquisition electrode 301 adopted is identical electrode material, after can being arranged on ear with reference to the position of electric level or be clipped on ear-lobe.Rechargeable battery 303 can be lithium ion battery, lithium polymer battery, biological fuel cell or radio frequency powered device, biological fuel cell provides electric energy by the glucose of enzyme catalysis self, radio frequency powered device is undertaken by coil in vivo responding to the one produced in electric energy, the position of bluetooth module can be arranged on the position of rechargeable battery 303, certainly also this position can be adjusted in actual applications, this bluetooth module needs the DC voltage of 3.3V; The model of bluetooth module can select bluetooth 4.0 integrated chip of SM01A.Fixing head hoop 304 be by a kind of arbitrarily flexible, there is good plasticity, softness, comfortable, harmless to human non-toxic macromolecular material make, the head hoop of this material can make whole brain wave acquisition device be fixed on same position, the signal of what brain wave acquisition electrode was recorded to is same position, head hoop can have the flexible of certain limit simultaneously, make the head hoop only needing large, medium and small three kinds of sizes, just can dress at the head of all normal persons and use.
The eye that eye movement data stream in above-mentioned receiving element 401 can adopt Tobii company to provide moves the solution of harvester, the TobiiGlasses2 eye tracker adopted can comprise two parts composition, wear part---glasses and recording equipment can be the one among the senior version of TobiiGlassesLiveView version, TobiiGlassesLiveView wireless version and TobiiGlasses three kinds of versions.Glasses have a Radix Rumicis high definition scene camera, resolution is 1920 × 1080, has 4 eyes and moves video camera, the gyroscope of outfit and acceleration transducer etc.
In above-mentioned receiving element 401, skin reactance data flow can be measured by skin pricktest impedance recording equipment, this skin pricktest impedance recording equipment comprises two finger cot type electrodes and connection cord, cable can be the one in the materials such as copper, aluminum, outside insulating barrier plastic wraps.
Data processing unit 402, for after described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow;
Can have multiple to the mode that EEG signals data flow, eye movement data stream and skin reactance data flow carry out preliminary treatment in above-mentioned data processing unit 402, the processing mode of the present invention first better embodiment to above-mentioned data flow does not limit, its concrete processing mode see the description in the present invention second better embodiment, can repeat no more here.
Transmitting element 403, for by the data flow after preliminary treatment to the good support vector machine of training in advance;
Analytic unit 404, for obtaining the state of brain cognition to the data-flow analysis after preliminary treatment by support vector machine;
Brain cognitive state in above-mentioned steps includes but not limited to: normal condition, state to be confirmed and abnormality, and wherein, normal condition represents normal by brain cognition detection discovery brain activity; State to be confirmed can represent, the state of the brain cognition now detected is between abnormality and normal condition, and abnormality represents abnormal by brain cognition detection discovery brain activity.
Optionally, data processing unit 402 is concrete, for:
Carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow makes described EEG signals data flow, eye movement data stream and skin reactance data flow become synchronous data flow.
In above-mentioned data processing unit 402, synchronous process is carried out to data and make described EEG signals data flow, the specifically synchronous mode that eye movement data stream and skin reactance data flow become synchronous data flow can have multiple, such as, in an embodiment of the present invention the 3rd better embodiment, obtain time started 1 and the end time 1 of EEG signals data flow, the time started 2 of eye movement data stream and end time 2, the time started 3 of skin reactance data flow and end time 3, extract the time started the latest in 3 time starteds, extract the end time the earliest time in 3 end times, here the hypothesis time started 3 is the time started the latest, end time 2 is earliest finish time, in eeg data stream, then intercept the data flow between time started 3 and end time 2, the data flow between time started 3 and end time 2 is intercepted in eye movement data stream, the data flow between time started 3 and end time 2 is intercepted in skin reactance data flow.
Certain above-mentioned synchronous mode can also adopt other mode, such as in an embodiment of the present invention the 3rd better embodiment, directly can obtain a setting-up time section, the data flow of setting-up time section is intercepted in eeg data stream, in eye movement data stream, intercept the data flow of setting-up time section, in skin reactance data flow, intercept the data flow of setting-up time section.
Optionally, said apparatus can also comprise:
Delete cells 407, for the data deletion by exceeding first threshold scope in described EEG signals data flow, the data deletion of Second Threshold scope will be exceeded, by the data deletion more than the 3rd threshold range in described skin reactance data flow in described eye movement data stream;
Fitting unit 408, for filling the data of deleting in EEG signals data flow the first fitting data, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled.
Wherein, described first fitting data is within the scope of described first threshold, and described second fitting data is within the scope of described Second Threshold, and described 3rd fitting data is in described 3rd threshold range.
Consult Fig. 5, a kind of multiparameter family brain cognition detection system that Fig. 5 provides for the present invention the 4th better embodiment, as shown in Figure 5, this system can comprise: eeg signal acquisition device 300, eye move harvester 502, skin pricktest impedance recording equipment 503, DSP date processing box 504 and intelligent terminal 505; The module diagram of above-mentioned all parts as shown in Figure 7.
Wherein, eeg signal acquisition device 300, for gathering EEG signals data flow, and by this EEG signals data flow;
Above-mentioned eeg signal acquisition device as shown in Figure 2, comprising: multiple brain wave acquisition electrode 301, reference electrode 302, rechargeable battery 303, fixing head hoop 304 and bluetooth module; Wherein, the material of brain wave acquisition electrode 301 can be the one of the materials such as Ag or AgAl, rustless steel or gold, can be directly connected in contact point, not need conducting resinl in use.The quantity prioritizing selection of brain wave acquisition electrode 301 3, be used for gathering EEG signals signal, the signal collected is the EEG signals data flow of 10 μ V magnitudes, and brain wave acquisition point is positioned at above forehead left eye or right eye.Reference electrode 302, what this material with reference to electric level 302 and brain wave acquisition electrode 301 adopted is identical electrode material, after can being arranged on ear with reference to the position of electric level or be clipped on ear-lobe.Rechargeable battery 303 can be lithium ion battery, lithium polymer battery, biological fuel cell or radio frequency powered device, biological fuel cell provides electric energy by the glucose of enzyme catalysis self, radio frequency powered device is undertaken by coil in vivo responding to the one produced in electric energy, the position of bluetooth module can be arranged on the position of rechargeable battery 303, certainly also this position can be adjusted in actual applications, this bluetooth module needs the DC voltage of 3.3V; The model of bluetooth module can select bluetooth 4.0 integrated chip of SM01A.Fixing head hoop 304 be by a kind of arbitrarily flexible, there is good plasticity, softness, comfortable, harmless to human non-toxic macromolecular material make, the head hoop of this material can make whole brain wave acquisition device be fixed on same position, the signal of what brain wave acquisition electrode was recorded to is same position, head hoop can have the flexible of certain limit simultaneously, make the head hoop only needing large, medium and small three kinds of sizes, just can dress at the head of all normal persons and use.
Eye harvester 502, for gathering eye movement data stream, and sends this eye movement data stream;
Above-mentioned eye harvester 502, the eye that Tobii company can be adopted to provide moves harvester, the TobiiGlasses2 eye tracker adopted can comprise two parts composition, wear part---glasses and recording equipment can be the one among the senior version of TobiiGlassesLiveView version, TobiiGlassesLiveView wireless version and TobiiGlasses three kinds of versions.Glasses have a Radix Rumicis high definition scene camera, resolution is 1920 × 1080, has 4 eyes and moves video camera, the gyroscope of outfit and acceleration transducer etc.
Skin pricktest impedance recording equipment 503, for gathering skin reactance data flow, and by this skin reactance data flow;
Above-mentioned skin pricktest impedance recording equipment comprises two finger cot type electrodes and connection cord, and cable can be the one in the materials such as copper, aluminum, outside insulating barrier plastic wraps.
DSP date processing box 504, for receiving EEG signals data flow, eye movement data stream and skin reactance data flow, after described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, by the data flow intelligent terminal after preliminary treatment;
Above-mentioned DSP date processing box can comprise: for by TGAM module, TMS320 processor, button, bluetooth module and power supply, wherein TGAM module is the brain electricity hardware module that god reads science and technology, the pretreatment to original EEG signals can be realized, and export α, the E.E.G wave band datas such as β.TMS320 processor is that TI company produces, and concrete model is TMS320f2812, is a fixed point 32 chips, and running clock can reach 150MHz, and every bar instruction cycle is 6.67ns, has the a/d converter of 12.DSP module completes and merges the data syn-chronization of multiple sensor acquisition, and sends to mobile terminal by bluetooth module.
Optionally, above-mentioned DSP date processing box 504, specifically, described EEG signals data flow, eye movement data stream and skin reactance data flow is made to become synchronous data flow for carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow;
In above-mentioned DSP date processing box 504, synchronous process is carried out to data and make described EEG signals data flow, the specifically synchronous mode that eye movement data stream and skin reactance data flow become synchronous data flow can have multiple, such as, in an embodiment of the present invention the 4th better embodiment, obtain time started 1 and the end time 1 of EEG signals data flow, the time started 2 of eye movement data stream and end time 2, the time started 3 of skin reactance data flow and end time 3, extract the time started the latest in 3 time starteds, extract the end time the earliest time in 3 end times, here the hypothesis time started 3 is the time started the latest, end time 2 is earliest finish time, in eeg data stream, then intercept the data flow between time started 3 and end time 2, the data flow between time started 3 and end time 2 is intercepted in eye movement data stream, the data flow between time started 3 and end time 2 is intercepted in skin reactance data flow.
Certain above-mentioned synchronous mode can also adopt other mode, such as in an embodiment of the present invention the 4th better embodiment, directly can obtain a setting-up time section, the data flow of setting-up time section is intercepted in eeg data stream, in eye movement data stream, intercept the data flow of setting-up time section, in skin reactance data flow, intercept the data flow of setting-up time section.
Optionally, above-mentioned DSP date processing box 504, also for the data deletion by exceeding first threshold scope in EEG signals data flow, the data deletion of Second Threshold scope will be exceeded in eye movement data stream, by in skin reactance data flow more than the data deletion of the 3rd threshold range, the data of deleting in EEG signals data flow the first fitting data is filled, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled.
Wherein, above-mentioned first fitting data is within the scope of first threshold, and the second fitting data is within the scope of Second Threshold, and the 3rd fitting data is in the 3rd threshold range.
Intelligent terminal 505, for being obtained the state of brain cognition to the data-flow analysis after preliminary treatment by support vector machine.
It should be noted that, the corresponding function of above-mentioned DSP date processing box also can be remembered on intelligent terminal by the mode of app, and the app interface of this intelligent terminal as shown in Figure 6.
In addition, the specific embodiment of the invention also provides a kind of intelligent terminal, this intelligent terminal comprises multiparameter family brain cognition detection device, and the concrete structure of this multiparameter family brain cognition detection device see the description of the present invention the 3rd better embodiment, can repeat no more here.
It should be noted that, for aforesaid each method embodiment or embodiment, in order to simple description, therefore it is all expressed as a series of combination of actions, but those skilled in the art should know, the present invention is not by the restriction of described sequence of movement, because according to the present invention, some step can adopt other orders or carry out simultaneously.Secondly, those skilled in the art also should know, embodiment described in description or embodiment all belong to preferred embodiment, and involved action and unit might not be that the present invention is necessary.
In the above-described embodiments, the description of each embodiment is all emphasized particularly on different fields, in certain embodiment, there is no the part described in detail, can see the associated description of other embodiments.
Step in embodiment of the present invention method can be carried out order according to actual needs and be adjusted, merges and delete.
Unit in embodiment of the present invention device can carry out merging, divide and deleting according to actual needs.The feature of the different embodiment described in this description and different embodiment can carry out combining or combining by those skilled in the art.
Through the above description of the embodiments, those skilled in the art can be well understood to the present invention can use hardware implementing, or firmware realizes, or their compound mode realizes.When implemented in software, above-mentioned functions can be stored in computer-readable medium or as the one or more instruction on computer-readable medium or code and transmit.Computer-readable medium comprises computer-readable storage medium and communication media, and wherein communication media comprises any medium being convenient to transmit computer program from a place to another place.Storage medium can be any usable medium that computer can access.As example but be not limited to: computer-readable medium can comprise random access memory (RandomAccessMemory, RAM), read only memory (Read-OnlyMemory, ROM), EEPROM (ElectricallyErasableProgrammableRead-OnlyMemory, EEPROM), read-only optical disc (CompactDiscRead-OnlyMemory, or other optical disc storage CD-ROM), magnetic disk storage medium or other magnetic storage apparatus, or the program code that can be used in carrying or storing the expectation with instruction or data structure form also can by any other medium of computer access.In addition.Any connection can be suitable become computer-readable medium.Such as, if software uses coaxial cable, optical fiber cable, twisted-pair feeder, Digital Subscriber Line (DigitalSubscriberLine, DSL) or the wireless technology of such as infrared ray, radio and microwave and so on from website, server or other remote source, so the wireless technology of coaxial cable, optical fiber cable, twisted-pair feeder, DSL or such as infrared ray, wireless and microwave and so on be included in affiliated medium fixing in.As used in the present invention, dish (Disk) and dish (disc) comprise compression laser disc (CD), laser dish, laser disc, Digital Versatile Disc (DVD), floppy disk and Blu-ray Disc, the usual magnetic of its mid-game copy data, what dish then carried out optics with laser copies data.Combination above also should be included within the protection domain of computer-readable medium.
In a word, the foregoing is only the preferred embodiment of technical solution of the present invention, be not intended to limit protection scope of the present invention.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. a multiparameter family brain cognition detection method, is characterized in that, described method comprises the steps:
Receive EEG signals data flow, eye movement data stream and skin reactance data flow;
After described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, by the data flow after preliminary treatment to the good support vector machine of training in advance;
By support vector machine, the data-flow analysis after preliminary treatment is obtained to the state of brain cognition;
Described brain cognitive state comprises: normal condition, state to be confirmed and abnormality.
2. method according to claim 1, is characterized in that, described concrete to described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, comprising:
Carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow makes described EEG signals data flow, eye movement data stream and skin reactance data flow become synchronous data flow.
3. method according to claim 1 and 2, is characterized in that, described method also comprised before preliminary treatment:
The data deletion of first threshold scope will be exceeded in described EEG signals data flow, the data deletion of Second Threshold scope will be exceeded in described eye movement data stream, by the data deletion more than the 3rd threshold range in described skin reactance data flow, the data of deleting in EEG signals data flow the first fitting data is filled, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled;
Wherein, described first fitting data is within the scope of described first threshold, and described second fitting data is within the scope of described Second Threshold, and described 3rd fitting data is in described 3rd threshold range.
4. a multiparameter family brain cognition detection device, is characterized in that, described device comprises:
Receiving element, for receiving EEG signals data flow, eye movement data stream and skin reactance data flow;
Data processing unit, for after described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow;
Transmitting element, for by the data flow after preliminary treatment to the good support vector machine of training in advance;
Analytic unit, for obtaining the state of brain cognition to the data-flow analysis after preliminary treatment by support vector machine;
Described brain cognitive state comprises: normal condition, state to be confirmed and abnormality.
5. device according to claim 4, is characterized in that, described data processing unit is concrete, for:
Carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow makes described EEG signals data flow, eye movement data stream and skin reactance data flow become synchronous data flow.
6. the device according to claim 4 or 5, peculiar, be, described device also comprises:
Delete cells, for the data deletion by exceeding first threshold scope in described EEG signals data flow, will exceed the data deletion of Second Threshold scope, by the data deletion more than the 3rd threshold range in described skin reactance data flow in described eye movement data stream;
Fitting unit, for filling the data of deleting in EEG signals data flow the first fitting data, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled;
Wherein, described first fitting data is within the scope of described first threshold, and described second fitting data is within the scope of described Second Threshold, and described 3rd fitting data is in described 3rd threshold range.
7. a multiparameter family brain cognition detection system, is characterized in that, described system comprises: eeg signal acquisition device, eye harvester, skin pricktest impedance recording equipment, DSP date processing box and intelligent terminal; Wherein,
Eeg signal acquisition device, for gathering EEG signals data flow, and by this EEG signals data flow;
Eye harvester, for gathering eye movement data stream, and sends this eye movement data stream;
Skin pricktest impedance recording equipment, for gathering skin reactance data flow, and by this skin reactance data flow;
DSP date processing box, for receiving EEG signals data flow, eye movement data stream and skin reactance data flow, after described EEG signals data flow, eye movement data stream and the preliminary treatment of skin reactance data flow, by the data flow intelligent terminal after preliminary treatment;
Intelligent terminal, for obtaining the state of brain cognition to the data-flow analysis after preliminary treatment by support vector machine.
8. system according to claim 7, it is characterized in that, described DSP date processing box, specifically, described EEG signals data flow, eye movement data stream and skin reactance data flow is made to become synchronous data flow for carrying out different disposal to described EEG signals data flow, eye movement data stream and skin reactance data flow.
9. the system according to claim 7 or 8, it is characterized in that, described DSP date processing box, also for, the data deletion of first threshold scope will be exceeded in described EEG signals data flow, the data deletion of Second Threshold scope will be exceeded, by the data deletion more than the 3rd threshold range in described skin reactance data flow in described eye movement data stream; For filling the data of deleting in EEG signals data flow the first fitting data, the data of deleting in eye movement data stream the second fitting data is filled, the data of deleting in skin reactance data flow the 3rd fitting data is filled;
Wherein, described first fitting data is within the scope of described first threshold, and described second fitting data is within the scope of described Second Threshold, and described 3rd fitting data is in described 3rd threshold range.
10. an intelligent terminal, is characterized in that, described intelligent terminal comprise as arbitrary in claim 4-6 as described in multiparameter family brain cognition detection device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510876010.6A CN105534520A (en) | 2015-12-02 | 2015-12-02 | Multi-parameter family-type brain cognition detection method, device and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510876010.6A CN105534520A (en) | 2015-12-02 | 2015-12-02 | Multi-parameter family-type brain cognition detection method, device and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105534520A true CN105534520A (en) | 2016-05-04 |
Family
ID=55814474
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510876010.6A Pending CN105534520A (en) | 2015-12-02 | 2015-12-02 | Multi-parameter family-type brain cognition detection method, device and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105534520A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106027164A (en) * | 2016-07-05 | 2016-10-12 | 杜碧玉 | Brain cognition-based fluid communication method, device and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2343970Y (en) * | 1997-01-03 | 1999-10-20 | 中国人民解放军第514医院 | Events related potentiometer |
| US20060058853A1 (en) * | 2004-09-13 | 2006-03-16 | Jonathan Bentwich | Integrated system and method for treating disease using cognitive-training and brain stimulation and computerized magnetic photo-electric stimulator (cmpes) |
| US20090062660A1 (en) * | 2002-07-10 | 2009-03-05 | Britton Chance | Examination and imaging of brain cognitive functions |
| US20090319001A1 (en) * | 1999-06-11 | 2009-12-24 | Cornell Research Foundation, Inc. | Feedback method for deep brain stimulation with detection of generalized efference copy signals |
| CN101690659A (en) * | 2009-09-29 | 2010-04-07 | 华东理工大学 | Brain wave analysis method |
| CN104958072A (en) * | 2015-05-18 | 2015-10-07 | 华南理工大学 | Cerebrum functional zone specificity electroencephalogram detecting method based on vector multi-classification |
-
2015
- 2015-12-02 CN CN201510876010.6A patent/CN105534520A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2343970Y (en) * | 1997-01-03 | 1999-10-20 | 中国人民解放军第514医院 | Events related potentiometer |
| US20090319001A1 (en) * | 1999-06-11 | 2009-12-24 | Cornell Research Foundation, Inc. | Feedback method for deep brain stimulation with detection of generalized efference copy signals |
| US20090062660A1 (en) * | 2002-07-10 | 2009-03-05 | Britton Chance | Examination and imaging of brain cognitive functions |
| US20060058853A1 (en) * | 2004-09-13 | 2006-03-16 | Jonathan Bentwich | Integrated system and method for treating disease using cognitive-training and brain stimulation and computerized magnetic photo-electric stimulator (cmpes) |
| CN101690659A (en) * | 2009-09-29 | 2010-04-07 | 华东理工大学 | Brain wave analysis method |
| CN104958072A (en) * | 2015-05-18 | 2015-10-07 | 华南理工大学 | Cerebrum functional zone specificity electroencephalogram detecting method based on vector multi-classification |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106027164A (en) * | 2016-07-05 | 2016-10-12 | 杜碧玉 | Brain cognition-based fluid communication method, device and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104142583A (en) | Intelligent glasses with blinking detection function and implementation method thereof | |
| CN105446492A (en) | Information interaction system based on brainwave sensing headset and intelligent wearable apparatus | |
| CN107145239A (en) | A kind of intelligence system and its control method that sensor is read based on brain | |
| CN203763056U (en) | Earphone type human health detector | |
| CN108345676A (en) | Information-pushing method and Related product | |
| CN103876720A (en) | Method and system for detecting human body and environment information | |
| CN105816168A (en) | Electrocardiogram detection device | |
| US20140171819A1 (en) | Neurological Monitoring Method and System | |
| CN205758549U (en) | A kind of Low Power Consumption Portable electrocardiogram monitor system | |
| CN203417202U (en) | Dynamic electrocardiogram monitor based on smart phone | |
| CN105813557A (en) | Localized collection of biological signals, cursor control in speech-assistance interface based on biological electrical signals and arousal detection based on biological electrical signals | |
| CN202950649U (en) | Portable electronic health monitoring instrument | |
| CN102871656A (en) | Multifunctional strap-type electroencephalogram collector with functions of computer storage, real-time communication and processing | |
| CN105534520A (en) | Multi-parameter family-type brain cognition detection method, device and system | |
| CN104939824B (en) | A kind of wearable device, detection circuit and method for wearable device | |
| CN204072104U (en) | A kind of wearable wireless detecting blood and oxygen in human brain equipment | |
| Alimbayeva et al. | Portable ECG Monitoring System | |
| CN104808778A (en) | Device and method for determining validity of operation of head-wearing intelligent device | |
| CN110868912A (en) | Removal of artifacts in neurophysiological signals | |
| CN103230269A (en) | Wireless portable ECG (electrocardiograph) monitor | |
| CN114587301A (en) | Method and device for analyzing physical sign signals and storage medium | |
| CN212410976U (en) | Intelligent glasses and glasses box | |
| CN205083510U (en) | Heart sound auscultation device based on smart mobile phone | |
| CN203369902U (en) | Electrocardiogram monitoring system based on intelligent terminal communications | |
| CN207164699U (en) | A kind of intelligence system that sensor is read based on brain |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160504 |