CN102551690B - Method for adaptively analyzing human signal - Google Patents
Method for adaptively analyzing human signal Download PDFInfo
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- CN102551690B CN102551690B CN 201110452454 CN201110452454A CN102551690B CN 102551690 B CN102551690 B CN 102551690B CN 201110452454 CN201110452454 CN 201110452454 CN 201110452454 A CN201110452454 A CN 201110452454A CN 102551690 B CN102551690 B CN 102551690B
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Abstract
The invention discloses a method for adaptively analyzing a human signal and relates to the technical field of detection of human signals. The method comprises the following steps of: 1, superposing a human signal which is acquired in real time with a standard human signal to ensure that voltage maximum in the acquired human signal and voltage maximum in the standard human signal are coincided with each other to establish an individual data model; 2, receiving one or more characteristic points which are selected from the individual data model by a user, and grouping the individual data model loaded with the characteristic points according to distribution of the characteristic points so as to determine a temporal point of the characteristic points; and 3, transmitting a feedback signal when a temporal point of an individual signal is coincided with the temporal point of the characteristic points. By the method for adaptively analyzing the human signal, a feedback point of the signal can be rapidly found by comparing the characteristic points of the individual signal with reference points of a standard signal.
Description
Technical field
The present invention relates to human body signal detection technique field, particularly a kind of human body signal adaptive analysis method.
Background technology
In recent years, along with being on the increase of cardiovascular intervene operation, for can be in cardiac cycle certain or a plurality of specified point implement the needs of corresponding apparatus treatment, and prompting doctor that can be promptly and accurately or output signal to other operating equipment, this class technology seems more and more urgent.
Be example with big C equipment, to static organ clearly three-dimensional separate into picture, location.In prior art to twice imaging in patient front and side, the data of twice imaging are carried out matrixing form three-dimensional image, but for the dynamic organ of this class of heart, utilize this method imaging not only to can not get valuable image, on the contrary can be because of becoming aberration to cause repeatedly to patient's irradiation.
Utilize the present invention to carry out front or side irradiation imaging to the patient at the specific characteristic point of the different cardiac cycles of patient and since characteristic point corresponding when aroused in interest to unanimity, so imaging effect is better, reduce patient's umber of exposures simultaneously.
Summary of the invention
(1) technical problem that will solve
The technical problem to be solved in the present invention is: certain or some specified point output feedback signal in cardiac cycle how.
(2) technical scheme
For solving the problems of the technologies described above, the invention provides a kind of human body signal adaptive analysis method, may further comprise the steps:
S1: the human body signal that will collect in real time and the stack of the human body signal of standard, the time point of the appearance voltage max in the human body signal of the feasible human body signal that collects and standard is consistent, to set up the individual data items model;
S2: receive one or more characteristic points that the user selects at the individual data items model, the individual data items model after the loading characteristic point is divided into groups to determine the time point at characteristic point place by the distribution of characteristic point;
S3: when individual signal time point overlaps with the characteristic point time point, send feedback signal.
Wherein, the concrete mode of dividing into groups among the described step S2 is: after the grouping of individual data items model, according to cutting apart of datum mark, user's characteristic specified point one fixes on certain position between two datum marks, so with the unit of time integration, can determine the time point at characteristic point place at point-to-point transmission.
Wherein, if the heart rate of the human body signal that collects is the heart rate of not learning, then also comprise after the grouping among the described step S2: described individual data items model is learnt, under different heart rate situations, to adjust the time point that characteristic point occurs.
Wherein, the process learnt of described individual signal comprises:
In a period of time, gather human body signal and calculate heart rate;
Superpose according to the electrocardiosignal of current heart rate and the human body signal of standard, make the signal that collects carry datum mark;
According to user's specific characteristic point, calculate the time point at characteristic point place under current heart rate after the Fourier expansion.
Wherein, send feedback signal among the step S3 and also comprise before: adjust feedback signal in advance when individual signal time domain overlaps with the characteristic point time point or delay an appointment millisecond number, the time point of pressing after adjusting sends feedback signal.
Wherein, also comprise recording individual signal source, user's specific characteristic point and feedback signal point after the described step S3.
Wherein, before contrast, also comprise the pretreated process of the human body signal that real-time detects among the described step S1:
Signal is extracted from noise, carry out the data pick-up compression, carry out smoothing processing, baseline correction and digital filtering.
Wherein, described human body signal comprises: electrocardio and/or invasive blood pressure signal.
(3) beneficial effect
Human body signal adaptive analysis method of the present invention can find the feedback point of signal rapidly by with the characteristic point of individual signal and the contrast of standard signal datum mark.With the armarium imaging time, can carry out front or side irradiation imaging to the patient at the specific characteristic point of the different cardiac cycles of patient, owing to characteristic point corresponding when aroused in interest to unanimity, so imaging effect is better, reduce patient's umber of exposures simultaneously.
Description of drawings
Fig. 1 is a kind of human body signal adaptive analysis method flow diagram of the embodiment of the invention;
Fig. 2 adopts electrocardio and the aortic blood pressure comparison diagram of said method with the time.
The specific embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples are used for explanation the present invention, but are not used for limiting the scope of the invention.
As shown in Figure 1, human body signal adaptive analysis method of the present invention comprises:
Step S101, human body signal stack with the human body signal that collects in real time and standard, the time point of the appearance voltage max in the human body signal of the feasible human body signal that collects and standard is consistent, to set up the individual data items model, and export each signal waveform at screen, human body signal is often referred to electrocardio and/or invasive blood pressure signal (can analyze separately these two kinds of signals, also can analyze simultaneously).The standard cardioelectric that equipment carries and invasive blood pressure signal data are that each is connected and composed by 2000 datum marks.The standard cardioelectric signal is sinus rate 80 times/minute, the output joint rate of invasive blood pressure is identical simultaneously, because the electrocardio that real-time detects or invasive blood pressure signal are not necessarily in this scope, so utilize interval mobile method that the standard signal data are amplified or dwindle to adapt to the signal data that collects, on output waveform, namely the time coordinate of the appearance voltage max in the human body signal of the feasible human body signal that collects and standard is identical.Form one group data model by the overlapping back of standard signal and the human body signal that collects, be referred to as the individual data items model.The individual data items model has reacted the human body signal of being gathered the people really, will gather the electrocardio and the invasive blood pressure signal that come with datum mark simultaneously and carry out Region Segmentation.Screen output be electrocardio and invasive blood pressure signal mode through amplifying.
The standard human body signal that has electrocardio and invasive blood pressure in the collecting device according to the different characteristics of electrocardio or invasive blood pressure, indicates several datum marks to standard signal.Because human body signal is very complicated, a large amount of noise that mixing preferably, also comprised before contrast: live signal is extracted from noise, carry out the data pick-up compression, carry out smoothing processing, baseline correction, digital filtering and related operation.
The device of above-mentioned collection heart real time and invasive blood pressure signal includes:
The pick device of electrocardiosignal is the skin electrode measurement electromotive force that dirty electrical activity produces of getting into the frame of mind for work with the Zn-Cu electrode.
The invasive blood pressure signal is the piezo-electric conversion equipment, adopts invasive blood pressure sensor as pressure transducer.
The small-signal amplifying device: ecg signal amplifier adopts three grades of amplifications, and prestage input noise 50 microvolts, high input impedance, 80db are with the Pi common mode rejection ratio, the 0.2-200Hz frequency response.Have wound to press signal amplifier to gather two-stage differential and amplify, and corresponding temperature-compensating is arranged, amplification is adjustable at 500-3000.
The low pass of noise reduction, high pass and bandreject filtering device.
Wherein, the main adult's of electrocardiosignal frequency range is at 1～100Hz, for suppressing noise and convenient back level work, after preamplifier, design and band resistance, low pass and high pass filter, the mid frequency of band elimination filter is 50Hz, notch depth 40db, Q-value are 0.75; The cut-off frequency of low pass filter is 150Hz, and 150Hz has the decay of 6db/ octave with upper frequency; The cut-off frequency of high pass filter is 1Hz, and the low side frequency has the decay of 5db/ octave.
Have wound to press signal to press the signal transducer encapsulation through wound is arranged, difference is isolated and can be used.
To signal collected collection maintenance and analog-digital commutator;
Because frequency acquisition is higher, before mould/number conversion, there is one to gather holding circuit, and controls multi channel selecting with CPLD, mould/number conversion chip is selected MAX1168 for use, real-time 8 tunnel 16 samplings, sample frequency stuck-at-00KHz.
Auxiliary facilities includes: checkout gear, realization human computer conversation device, feedback signal that electrode comes off are sent port.
Step S102 receives the user and select one or more characteristic points respectively on above-mentioned individual data items model, and the individual data items model after the loading characteristic point is divided into groups.Particularly, the user selects one or more characteristic points by the human-computer interaction device at the individual data items model of output.To the individual data items model with Fourier expansion after, according to cutting apart of datum mark, user's characteristic specified point one fixes on certain position between two datum marks, thus at point-to-point transmission with the unit of time integration, can determine the time point at characteristic point place.
Except Fourier transformation, can also divide into groups by three order derivative methods, interval mobile method.
Step S103 sends feedback signal when individual signal time point overlaps with the characteristic point time point, can also adjust feedback signal in advance or delay an appointment millisecond number, sends feedback signal by the time point after adjusting.Send back recording individual signal source, user's specific characteristic point and feedback signal point.
Before step S102 and the S103, if the heart rate of the human body signal that collects is that (the different time sections heart rate may be different for the heart rate of not learning, the time point of adjusting the characteristic point appearance under the different heart rate situations is also different, as: adjusted the time point that characteristic point occurs when the heart rate 80 times/minute, just need not learn when collecting 80 times/minute heart rate next time, otherwise carry out following learning process), then also comprise after the grouping among the described step S2: described individual signal is learnt, under different heart rate situations, to adjust the time point that characteristic point occurs.Concrete learning process is as follows:
In a period of time, gather human body signal and calculate heart rate;
Superpose according to the electrocardiosignal of current heart rate and the human body signal of standard, make the signal that collects carry datum mark;
According to user's specific characteristic point, calculate the time point at characteristic point place under current heart rate after the Fourier expansion.
With the armarium imaging time, can carry out front or side irradiation imaging to the patient at the specific characteristic point of the different cardiac cycles of patient by said method, since characteristic point corresponding when aroused in interest to unanimity, so imaging effect is better, reduce patient's umber of exposures simultaneously.
As shown in Figure 2, suppose that user's characteristic specified point opens for aortic valve, aortic valve closes two condition.
The adaptive characteristics according to the present invention are gathered human body electrocardio and invasive blood pressure signal earlier, superpose with standard human body electrocardio and invasive blood pressure signal, and the time point of the appearance voltage max in the human body signal of the feasible human body signal that collects and standard is consistent.Standard signal is to be connected and composed by several datum marks, and through clinical verification, this datum mark is relative with the heart working state consistent.
Set up the signal learning model through previous step, the new electrocardiosignal that collects again later on compares learning model earlier, and the contrast during this mainly is to revise heart rate, signal voltage value, and conversion signal trend is to revise learning model.
With revised learning model and the combination of user's specific characteristic point, the rising flex point of the summit of the R ripple in the legend and the kurtosis of S ripple, T ripple, the incisura of fighting of blood pressure signal is datum mark.
The above datum mark revised learning model that is added to is formed individual signal data model.
First user specified point is between R ripple and S ripple as requested, and after the new independent trend analysis algorithm process of revised learning model data process, software can judge whether these data approach or arrive user specified point.Control the transmission feedback signal thus.
The judgement of second user specified point is the same with the decision method of first specified point.
The present invention can analyze separately electrocardiosignal and invasive blood pressure signal, also can analyze simultaneously both.
Above embodiment only is used for explanation the present invention; and be not limitation of the present invention; the those of ordinary skill in relevant technologies field; under the situation that does not break away from the spirit and scope of the present invention; can also make a variety of changes and modification; therefore all technical schemes that are equal to also belong to category of the present invention, and scope of patent protection of the present invention should be defined by the claims.
Claims (7)
1. a human body signal adaptive analysis method is characterized in that, may further comprise the steps:
S1: the human body signal that will collect in real time and the stack of the human body signal of standard, the time point of the appearance voltage max in the human body signal of the feasible human body signal that collects and standard is consistent, to set up the individual data items model, described human body signal comprises: electrocardio and/or invasive blood pressure signal;
S2: receive one or more characteristic points that the user selects at the individual data items model, the individual data items model after the loading characteristic point is divided into groups to determine the time point at characteristic point place by the distribution of characteristic point;
S3: when individual signal time point overlaps with the characteristic point time point, send feedback signal.
2. human body signal adaptive analysis method as claimed in claim 1, it is characterized in that, the concrete mode of dividing into groups among the described step S2 is: after the grouping of individual data items model, according to cutting apart of datum mark, user's characteristic specified point one fixes on certain position between two datum marks, so with the unit of time integration, can determine the time point at characteristic point place at point-to-point transmission.
3. human body signal adaptive analysis method as claimed in claim 1, it is characterized in that, if the heart rate of the human body signal that collects is the heart rate of not learning, then also comprise after the grouping among the described step S2: described individual data items model is learnt, under different heart rate situations, to adjust the time point that characteristic point occurs.
4. human body signal adaptive analysis method as claimed in claim 3 is characterized in that, the process that described individual signal is learnt comprises:
In a period of time, gather human body signal and calculate heart rate;
Superpose according to the electrocardiosignal of current heart rate and the human body signal of standard, make the signal that collects carry datum mark;
According to user's specific characteristic point, calculate the time point at characteristic point place under current heart rate after the Fourier expansion.
5. human body signal adaptive analysis method as claimed in claim 1, it is characterized in that, also comprise before sending feedback signal among the step S3: when individual signal time point overlaps with the characteristic point time point, adjust feedback signal in advance or delay an appointment millisecond number, send feedback signal by the time point after adjusting.
6. human body signal adaptive analysis method as claimed in claim 1 is characterized in that, also comprises recording individual signal source, user's specific characteristic point and feedback signal point after the described step S3.
7. human body signal adaptive analysis method as claimed in claim 1 is characterized in that, also comprises the pretreated process of the human body signal that real-time detects before contrast among the described step S1:
Signal is extracted from noise, carry out the data pick-up compression, carry out smoothing processing, baseline correction and digital filtering.
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| CN105748051B (en) * | 2016-02-18 | 2018-10-09 | 京东方科技集团股份有限公司 | A kind of blood pressure measuring device |
| CN109567775A (en) * | 2018-10-15 | 2019-04-05 | 广东宝莱特医用科技股份有限公司 | A kind of IBP addition of waveforms method and device thereof |
| CN110881970B (en) * | 2019-11-28 | 2023-06-02 | 深圳市善行医疗科技有限公司 | Electrocardiogram measuring method, electrocardiogram measuring device, electronic equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101176660A (en) * | 2007-12-06 | 2008-05-14 | 山东大学 | Detector methods and apparatus of cardiovascular system combining with variability guideline |
| CN101264011A (en) * | 2007-03-12 | 2008-09-17 | 三星电子株式会社 | Method and apparatus for cufflessly and non-invasively measuring wrist blood pressure |
| CN101773392A (en) * | 2010-02-06 | 2010-07-14 | 珠海康心电子科技有限公司 | Self-adaptive high-efficiency storage method of dynamic electrocardiogram (ECG) data |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101264011A (en) * | 2007-03-12 | 2008-09-17 | 三星电子株式会社 | Method and apparatus for cufflessly and non-invasively measuring wrist blood pressure |
| CN101176660A (en) * | 2007-12-06 | 2008-05-14 | 山东大学 | Detector methods and apparatus of cardiovascular system combining with variability guideline |
| CN101773392A (en) * | 2010-02-06 | 2010-07-14 | 珠海康心电子科技有限公司 | Self-adaptive high-efficiency storage method of dynamic electrocardiogram (ECG) data |
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