CN105078444A - Noise detection method and device and medical detection equipment - Google Patents
Noise detection method and device and medical detection equipment Download PDFInfo
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Abstract
The invention discloses a noise detection method, a noise detection device, and medical detection equipment. The noise detection method comprises the following steps: calculating input electrocardiosignals to obtain characteristic parameters of the electrocardiosignals; determining that whether the characteristic parameters meet intermediate frequency noise conditions or not, if so, and outputting the detection for the intermediate frequency noises. Through implementation of the implement of the invention, the characteristic parameters of the electrocardiosignals can be calculated, and when the characteristic parameters meet the intermediate frequency noise conditions, the detection for the intermediate frequency noise is output for prompting a doctor that intermediate frequency noises exist in the electrocardiosignals, so that misdiagnose on a patient by a doctor is prevented.
Description
Technical field
The present invention relates to Medical Instruments, particularly relate to a kind of noise detecting method, device and medical treatment detection device.
Background technology
The electrocardiosignal amplitude range of human body, substantially between 0.1mv ~ 5mv, is easy to the impact being subject to various environmental factors.Interference in current electrocardiosignal and noise have the interference of Hz noise, myoelectricity, mid-frequency noise, etc., wherein, frequency is difficult to be filtered out by the method by filters filter together with being aliasing in normal electrocardiosignal at the mid-frequency noise of 5Hz to 40Hz.These noises are superimposed upon in normal electrocardiosignal, and doctor can be caused the erroneous judgement of patient's electrocardio situation, thus cause mistaken diagnosis, hazardness is very big.
Summary of the invention
Embodiment of the present invention technical problem to be solved is, provides a kind of noise detecting method, device and medical treatment detection device, can detect in electrocardiosignal to there is mid-frequency noise.
First aspect, embodiments provides a kind of noise detecting method, comprising: calculate to the electrocardiosignal of input the characteristic parameter obtaining described electrocardiosignal; Judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections is to mid-frequency noise.
Alternatively, after the described electrocardiosignal to input calculates to obtain the characteristic parameter of described electrocardiosignal, also comprise: judge whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections is to baseline drift noise.
Alternatively, described characteristic parameter comprises adjacent cells time crest number and does not change number of times and baseline drift noise proportional coefficient, describedly judge whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections comprises to baseline drift noise: judge whether to meet adjacent cells time crest number simultaneously and do not change number of times and be less than first threshold, with, baseline drift noise proportional coefficient is greater than Second Threshold two conditions; If meet described two conditions simultaneously, then output detections is to baseline drift noise; Or, described characteristic parameter comprises baseline drift noise proportional coefficient, describedly judge whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections comprises to baseline drift noise: judge whether baseline drift noise proportional coefficient is greater than the 3rd threshold value; If baseline drift noise proportional coefficient is greater than the 3rd threshold value, then output detections is to baseline drift noise.
Alternatively, described characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, with, minimum crest interval rule degree parameter, describedly judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections comprises to mid-frequency noise: judge whether that meet unit interval crest number is more than or equal to the 4th threshold value simultaneously, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions, if meet three conditions simultaneously, then output detections is to mid-frequency noise, or, described characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, with, unit interval broad peak number ratio, describedly judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections comprises to mid-frequency noise: judge whether meet unit interval amplitude square simultaneously and be greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, with, unit interval broad peak number ratio is less than the tenth threshold value five conditions, wherein, m is real number, if meet five conditions simultaneously, then output detections is to mid-frequency noise, or, described characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, with, unit interval crest number threshold value, describedly judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections comprises to mid-frequency noise: judge whether that meet unit interval crest number is more than or equal to the 11 threshold value simultaneously, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, wherein, n is real number, if meet four conditions simultaneously, then output detections is to mid-frequency noise.
Alternatively, the described electrocardiosignal to input comprises before calculating to obtain the characteristic parameter of described electrocardiosignal: carry out pretreatment to obtain electrocardiosignal to the detection signal of input.
Second aspect, embodiments provides a kind of noise detection apparatus, comprising: computing module and the first judge module, and described computing module is used for calculating to the electrocardiosignal of input the characteristic parameter obtaining described electrocardiosignal; Described first judge module is for judging whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections is to mid-frequency noise.
Alternatively, described device also comprises the second judge module, described second judge module is for judging whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections is to baseline drift noise.
Alternatively, described characteristic parameter comprises adjacent cells time crest number and does not change number of times and baseline drift noise proportional coefficient, described second judge module does not change number of times be less than first threshold specifically for judging whether to meet adjacent cells time crest number simultaneously, with, baseline drift noise proportional coefficient is greater than Second Threshold two conditions, and when meeting described two conditions at the same time, output detections is to baseline drift noise; Or, described characteristic parameter comprises baseline drift noise proportional coefficient, described second judge module is specifically for judging whether baseline drift noise proportional coefficient is greater than the 3rd threshold value, and when baseline drift noise proportional coefficient is greater than the 3rd threshold value, output detections is to baseline drift noise.
Alternatively, described characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, with, minimum crest interval rule degree parameter, described first judge module is specifically for judging whether that meeting unit interval crest number is more than or equal to the 4th threshold value simultaneously, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions, when meeting three conditions at the same time, output detections is to mid-frequency noise, or, described characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, with, unit interval broad peak number ratio, described first judge module meets unit interval amplitude square simultaneously specifically for judging whether and is greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, with, unit interval broad peak number ratio is less than the tenth threshold value five conditions, wherein, m is real number, and when meeting five conditions at the same time, output detections is to mid-frequency noise, or, described characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, with, unit interval crest number threshold value, described first judge module is specifically for judging whether that meeting unit interval crest number is more than or equal to the 11 threshold value simultaneously, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, wherein, n is real number, and when meeting four conditions at the same time, output detections is to mid-frequency noise.
Alternatively, described device also comprises pretreatment module, and described pretreatment module is used for carrying out pretreatment to obtain electrocardiosignal to the detection signal of input.
The third aspect, embodiments provides a kind of medical treatment detection device, and described medical treatment detection device comprises the noise detection apparatus described in above-mentioned any one.
By implementing the embodiment of the present invention, can calculate the characteristic parameter of electrocardiosignal, and when characteristic parameter meets mid-frequency noise condition, output detections, to mid-frequency noise, is reminded in doctor's electrocardiosignal and be there is mid-frequency noise, prevent doctor to patient's mistaken diagnosis.
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.
Fig. 1 is the flow chart of noise detecting method one embodiment of the present invention;
Fig. 2 is the flow chart of another embodiment of noise detecting method of the present invention;
Fig. 3 is the structural representation of noise detection apparatus one embodiment of the present invention;
Fig. 4 is the structural representation of another embodiment of noise detection apparatus of the present invention.
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.
It should be noted that, the term used in embodiments of the present invention is only for the object describing specific embodiment, and not intended to be limiting the present invention." one ", " described " and " being somebody's turn to do " of the singulative used in the embodiment of the present invention and appended claims is also intended to comprise most form, unless context clearly represents other implications.It is also understood that term "and/or" used herein refer to and comprise one or more project of listing be associated any or all may combine.
See the flow chart that Fig. 1, Fig. 1 are noise detecting method one embodiments of the present invention.The method comprises:
Step S110: the characteristic parameter obtaining electrocardiosignal is calculated to the electrocardiosignal of input.
Particularly, together with mid-frequency noise is aliasing in normal electrocardiosignal, being difficult to be filtered out by the method by filters filter, in order to identify in electrocardiosignal whether have mid-frequency noise, must calculating to the electrocardiosignal of input the characteristic parameter obtaining electrocardiosignal.
Step S120: whether judging characteristic parameter meets mid-frequency noise condition, if characteristic parameter meets mid-frequency noise condition, then output detections is to mid-frequency noise.
Particularly, if characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, with, minimum crest interval rule degree parameter, then can arrange mid-frequency noise condition according to characteristic parameter is that unit time crest number is more than or equal to the 4th threshold value, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions.If the characteristic parameter of statistics all meets three above-mentioned conditions, then output detections is to mid-frequency noise.
Wherein, crest number is the unit interval: the number of the crest in the unit interval recently.
Adjacent peaks width change frequency is: it is right to be made into by adjacent two crests, obtain this change width direction to crest (by wide to narrow still from narrow to wide), thus obtain the change frequency in often pair of wave peak width direction in the unit interval.
Maximum crest interval rule degree parameter is: first within the unit interval, search for crest, it is one group with adjacent three crests, find the maximum crest in every group, then the interval calculating the maximum crest of two adjacent groups, is designated as maximum crest interval, then crest interval rule degree parameter in the unit of account time, initial value is 0, if adjacent maximum crest interval, is less than 10%, rule degree parameter adds 1, otherwise subtract 1, add up the cumulative sum of rule degree parameter in the time period, be designated as maximum crest interval rule degree parameter.
Minimum crest interval rule degree parameter is: first within the unit interval, search for crest, it is one group with adjacent three crests, find the minimum crest in every group, then the interval calculating the minimum crest of two adjacent groups, is designated as minimum crest interval, then crest interval rule degree parameter in the unit of account time, initial value is 0, if adjacent minimum crest interval, is less than 10%, rule degree parameter adds 1, otherwise subtract 1, add up the cumulative sum of rule degree parameter in the time period, be designated as minimum crest interval rule degree parameter.
Be understandable that, in the present embodiment, 4th threshold value can be set to the arbitrary value between 17 ~ 19,5th threshold value can be set to the arbitrary value between 0.8 ~ 1.2,6th threshold value can be set to the arbitrary value between-6 ~-4, in other embodiments, the value of the 4th threshold value, the 5th threshold value and the 6th threshold value also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
Or, if characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, with, unit interval broad peak number ratio, then can arrange mid-frequency noise condition according to characteristic parameter is that unit time-amplitude quadratic sum is greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, with, unit interval broad peak number ratio is less than the tenth threshold value five conditions, wherein, m is real number.If the characteristic parameter of statistics all meets five above-mentioned conditions, then output detections is to mid-frequency noise.
Wherein, unit interval amplitude square and be: within the unit interval, the quadratic sum of 5 hertz of high-pass filtering data.
Amplitude square and threshold value are: time per unit add up amplitude square and, calculate amplitude square in a period of time and meansigma methods as amplitude square and threshold value.
Unit interval crest number is: the number of the crest in the unit interval recently.
Unit interval crest number threshold value is: time per unit adds up a crest number, calculates the meansigma methods of the crest number in a period of time as unit interval crest number threshold value.
Baseline drift noise proportional coefficient is: in the current one time, the ratio of the quadratic sum of 0.1 hertz of high-pass filtering data and 5 hertz of high-pass filtering data quadratic sums.
Unit interval broad peak number ratio is: after crest being detected, broad peak judgement is carried out to each crest, when wave peak width is greater than 35 milliseconds, is designated as a broad peak, the number of broad peak in the statistics current one time, calculates the ratio of current one time inner width peak number and crest number.
Be understandable that, in the present embodiment, m can be set to the arbitrary value between 1.1 ~ 1.3,7th threshold value can be set to the arbitrary value between 7 ~ 9,8th threshold value can be set to the arbitrary value between 5 ~ 7,9th threshold value can be set to the arbitrary value between 0.93 ~ 0.95, tenth threshold value can be set to the arbitrary value between 0.43 ~ 0.47, in other embodiments, the value of m, the 7th threshold value, the 8th threshold value, the 9th threshold value and the tenth threshold value also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
Or, if characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, with, unit interval crest number threshold value, then can arrange mid-frequency noise condition according to characteristic parameter is that unit time crest number is more than or equal to the 11 threshold value, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, and wherein, n is real number.If the characteristic parameter of statistics all meets four above-mentioned conditions, then output detections is to mid-frequency noise.
Wherein, crest number is the unit interval: the number of the crest in the unit interval recently.
Baseline drift noise proportional coefficient is: in the current one time, the ratio of the quadratic sum of 0.1 hertz of high-pass filtering data and 5 hertz of high-pass filtering data quadratic sums.
Adjacent cells time crest number does not change number of times: it is right to be made into by adjacent two crests, obtain this change width direction to crest (by wide to narrow still from narrow to wide), thus obtain the change frequency in often pair of wave peak width direction in the unit interval.
Unit interval crest number threshold value is: time per unit adds up a crest number, calculates the meansigma methods of the crest number in a period of time as unit interval crest number threshold value.
Be understandable that, in the present embodiment, 11 threshold value can be set to the arbitrary value between 7 ~ 9,12 threshold value can be set to the arbitrary value between 5 ~ 7,13 threshold value can be set to 0.93 ~ 0.95, the n arbitrary value that can be set between 1.1 ~ 1.3, in other embodiments, the value of the 11 threshold value, the 12 threshold value, the 13 threshold value and n also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
In addition, characteristic parameter can also comprise parameters such as amplitude probability density etc., and the condition of mid-frequency noise also can be arranged according to the selection of characteristic parameter flexibly, and the present invention does not do concrete restriction.
By implementing the embodiment of the present invention, can calculate the characteristic parameter of electrocardiosignal, and when characteristic parameter meets mid-frequency noise condition, output detections, to mid-frequency noise, is reminded in doctor's electrocardiosignal and be there is mid-frequency noise, prevent doctor to patient's mistaken diagnosis.
See the flow chart that Fig. 2, Fig. 2 are another embodiments of noise detecting method of the present invention.The method comprises:
Step S210: pretreatment is carried out to obtain electrocardiosignal to the detection signal of input.
Particularly, equipment when detecting measured, owing to there is Hz noise, myoelectricity interference and baseline drift noise etc., detection signal detected by equipment, except normal electrocardiosignal, also comprises power frequency interference signals, myoelectricity interfering signal and baseline drift noise etc.So, in order to get rid of these interfering signals and effect of noise, pretreatment must be carried out to obtain electrocardiosignal to the detection signal of input.
Wherein, because power frequency interference signals is generally the signal of 50 hertz and 60 hertz, so, can to arrange bandwidth be respectively the band elimination filter of 48 to 52 hertz take filtration frequencies as the power frequency interference signals of 50 hertz, and to arrange bandwidth be the band elimination filter of 58 hertz to 62 hertz take filtration frequencies as the power frequency interference signals of 60 hertz.Because myoelectricity interfering signal is generally high-frequency signal, so can arrange cut-off frequency is that the low pass filter of 41.7 hertz is to filter myoelectricity interfering signal.And baseline drift noise is generally low frequency signal, so, can be that the high pass filter of 5 hertz is to filter baseline drift noise by arrange cut-off frequency be 0.1 hertz and cut-off frequency.
If be provided with cardiac pacemaker in measured's body, then cardiac pacemaker is when sending the take-off of pulse signal cardiac stimulus, can produce spike, thus makes also to carry spike in measured signal.So, now also need to arrange morphological filter, and utilize morphological filter spike to be filtered out, to prevent spike to be used as normal electrocardiosignal mistakenly, and then cause doctor to judge by accident.
Step S220: the characteristic parameter obtaining electrocardiosignal is calculated to the electrocardiosignal of input.
Particularly, together with mid-frequency noise is aliasing in normal electrocardiosignal, being difficult to be filtered out by the method by filters filter, in order to identify in electrocardiosignal whether have noise, must calculating to the electrocardiosignal of input the characteristic parameter obtaining electrocardiosignal.
Step S230: whether judging characteristic parameter meets mid-frequency noise condition, if characteristic parameter meets mid-frequency noise condition, then output detections is to mid-frequency noise.
Particularly, if characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, with, minimum crest interval rule degree parameter, then can arrange mid-frequency noise condition according to characteristic parameter is that unit time crest number is more than or equal to the 4th threshold value, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions.If the characteristic parameter of statistics all meets three above-mentioned conditions, then output detections is to mid-frequency noise.
Wherein, crest number is the unit interval: the number of the crest in the unit interval recently.
Adjacent peaks width change frequency is: it is right to be made into by adjacent two crests, obtain this change width direction to crest (by wide to narrow still from narrow to wide), thus obtain the change frequency in often pair of wave peak width direction in the unit interval.
Maximum crest interval rule degree parameter is: first within the unit interval, search for crest, it is one group with adjacent three crests, find the maximum crest in every group, then the interval calculating the maximum crest of two adjacent groups, is designated as maximum crest interval, then crest interval rule degree parameter in the unit of account time, initial value is 0, if adjacent maximum crest interval, is less than 10%, rule degree parameter adds 1, otherwise subtract 1, add up the cumulative sum of rule degree parameter in the time period, be designated as maximum crest interval rule degree parameter.
Minimum crest interval rule degree parameter is: first within the unit interval, search for crest, it is one group with adjacent three crests, find the minimum crest in every group, then the interval calculating the minimum crest of two adjacent groups, is designated as minimum crest interval, then crest interval rule degree parameter in the unit of account time, initial value is 0, if adjacent minimum crest interval, is less than 10%, rule degree parameter adds 1, otherwise subtract 1, add up the cumulative sum of rule degree parameter in the time period, be designated as minimum crest interval rule degree parameter.
Be understandable that, in the present embodiment, 4th threshold value can be set to the arbitrary value between 17 ~ 19,5th threshold value can be set to the arbitrary value between 0.8 ~ 1.2,6th threshold value can be set to the arbitrary value between-6 ~-4, in other embodiments, the value of the 4th threshold value, the 5th threshold value and the 6th threshold value also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
Or, if characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, with, unit interval broad peak number ratio, then can arrange mid-frequency noise condition according to characteristic parameter is that unit time-amplitude quadratic sum is greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, with, unit interval broad peak number ratio is less than the tenth threshold value five conditions, wherein, m is real number.If the characteristic parameter of statistics all meets five above-mentioned conditions, then output detections is to mid-frequency noise.
Wherein, unit interval amplitude square and be: within the unit interval, the quadratic sum of 5 hertz of high-pass filtering data.
Amplitude square and threshold value are: time per unit add up amplitude square and, calculate amplitude square in a period of time and meansigma methods as amplitude square and threshold value.
Unit interval crest number is: the number of the crest in the unit interval recently.
Unit interval crest number threshold value is: time per unit adds up a crest number, calculates the meansigma methods of the crest number in a period of time as unit interval crest number threshold value.
Baseline drift noise proportional coefficient is: in the current one time, the ratio of the quadratic sum of 0.1 hertz of high-pass filtering data and 5 hertz of high-pass filtering data quadratic sums.
Unit interval broad peak number ratio is: after crest being detected, broad peak judgement is carried out to each crest, when wave peak width is greater than 35 milliseconds, is designated as a broad peak, the number of broad peak in the statistics current one time, calculates the ratio of current one time inner width peak number and crest number.
Be understandable that, in the present embodiment, m can be set to the arbitrary value between 1.1 ~ 1.3,7th threshold value can be set to the arbitrary value between 7 ~ 9,8th threshold value can be set to the arbitrary value between 5 ~ 7,9th threshold value can be set to the arbitrary value between 0.92 ~ 0.96, tenth threshold value can be set to the arbitrary value between 0.43 ~ 0.47, in other embodiments, the value of m, the 7th threshold value, the 8th threshold value, the 9th threshold value and the tenth threshold value also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
Or, if characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, with, unit interval crest number threshold value, then can arrange mid-frequency noise condition according to characteristic parameter is that unit time crest number is more than or equal to the 11 threshold value, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, and wherein, n is real number.If the characteristic parameter of statistics all meets four above-mentioned conditions, then output detections is to mid-frequency noise.
Wherein, crest number is the unit interval: the number of the crest in the unit interval recently.
Baseline drift noise proportional coefficient is: in the current one time, the ratio of the quadratic sum of 0.1 hertz of high-pass filtering data and 5 hertz of high-pass filtering data quadratic sums.
Adjacent cells time crest number does not change number of times: it is right to be made into by adjacent two crests, obtain this change width direction to crest (by wide to narrow still from narrow to wide), thus obtain the change frequency in often pair of wave peak width direction in the unit interval.
Unit interval crest number threshold value is: time per unit adds up a crest number, calculates the meansigma methods of the crest number in a period of time as unit interval crest number threshold value.
Be understandable that, in the present embodiment, 11 threshold value can be set to the arbitrary value between 7 ~ 9,12 threshold value can be set to the arbitrary value between 5 ~ 7,13 threshold value can be set to the arbitrary value between 0.92 ~ 0.96, and n can be set to the arbitrary value between 1.1 ~ 1.3, in other embodiments, the value of the 11 threshold value, the 12 threshold value, the 13 threshold value and n also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
In addition, characteristic parameter can also comprise parameters such as amplitude probability density etc., and the condition of mid-frequency noise also can be arranged according to the selection of characteristic parameter flexibly, and the present invention does not do concrete restriction.
Step S240: whether judging characteristic parameter meets baseline drift noise conditions, if characteristic parameter meets baseline drift noise conditions, then output detections is to baseline drift noise.
Particularly; due to except mid-frequency noise; usually together with baseline drift noise is aliasing in normal electrocardiosignal in addition; be difficult to be filtered out by the method by filters filter; in order to identify in electrocardiosignal whether have baseline drift noise, also needing whether baseline drift noise conditions is met to characteristic parameter and judging.
If characteristic parameter comprises adjacent cells time crest number do not change number of times and baseline drift noise proportional coefficient, then can arrange baseline drift noise conditions is that adjacent cells time crest number does not change number of times and is less than first threshold, with, baseline drift noise proportional coefficient is greater than Second Threshold two conditions.If the characteristic parameter of statistics all meets two above-mentioned conditions, then output detections is to baseline drift noise.
Wherein, adjacent cells time crest number does not change number of times: it is right to be made into by adjacent two crests, obtain this change width direction to crest (by wide to narrow still from narrow to wide), thus obtain the change frequency in often pair of wave peak width direction in the unit interval.
Baseline drift noise proportional coefficient is: in the current one time, the ratio of the quadratic sum of 0.1 hertz of high-pass filtering data and 5 hertz of high-pass filtering data quadratic sums.
Be understandable that, in the present embodiment, first threshold can be set to the arbitrary value between 4.5 ~ 5.5, Second Threshold can be set to the arbitrary value between 9 ~ 11, in other embodiments, the value of first threshold and Second Threshold also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
Or if characteristic parameter comprises baseline drift noise proportional coefficient, then can arrange baseline drift noise conditions is that baseline drift noise proportional coefficient is greater than the 3rd threshold value.The characteristic parameter of statistics all meets above-mentioned condition, then output detections is to baseline drift noise.
Wherein, baseline drift noise proportional coefficient is: in the current one time, the ratio of the quadratic sum of 0.1 hertz of high-pass filtering data and 5 hertz of high-pass filtering data quadratic sums.
Be understandable that, in the present embodiment, the 3rd threshold value can be set to the arbitrary value between 18 ~ 22, and in other embodiments, the value of the 3rd threshold value also can according to the situation people of reality for arranging, and the present invention does not do concrete restriction.
In addition, characteristic parameter can also comprise other parameter, and the condition of baseline drift noise also can be arranged according to the selection of characteristic parameter flexibly, and the present invention does not do concrete restriction.
By implementing the embodiment of the present invention, can calculate the characteristic parameter of electrocardiosignal, and when characteristic parameter meets mid-frequency noise condition, output detections, to mid-frequency noise, is reminded in doctor's electrocardiosignal and be there is mid-frequency noise, prevent doctor to patient's mistaken diagnosis.
In addition, in present embodiment, judging characteristic parameter baseline drift noise conditions can also whether be met, and when characteristic parameter meets baseline drift noise conditions, output detections, to baseline drift noise, is reminded in doctor's electrocardiosignal and be there is baseline drift noise, prevent doctor to patient's mistaken diagnosis.And, before statistical nature parameter, also pretreatment is carried out to detection signal, some interfering signals are filtered out, improve the correctness detected.
The above-mentioned method illustrating the embodiment of the present invention, below for the ease of implementing the such scheme of the embodiment of the present invention better, correspondingly, is also provided for coordinating the relevant device implementing such scheme below.
Consult Fig. 3, Fig. 3 is the structural representation of noise detection apparatus one embodiment of the present invention.Described noise detection apparatus 300 comprises: computing module 310 and the first judge module 320.
Described computing module 310 is for calculating to the electrocardiosignal of input the characteristic parameter obtaining described electrocardiosignal;
Described first judge module 320 is for judging whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections is to mid-frequency noise.
Alternatively, described characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, and, minimum crest interval rule degree parameter,
Described first judge module 320 is specifically for judging whether that meeting unit interval crest number is more than or equal to the 4th threshold value simultaneously, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions, when meeting three conditions at the same time, output detections is to mid-frequency noise;
Or, described characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, and, unit interval broad peak number ratio,
Described first judge module 320 meets unit interval amplitude square simultaneously specifically for judging whether and is greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, with, unit interval broad peak number ratio is less than the tenth threshold value five conditions, wherein, m is real number, and when meeting five conditions at the same time, output detections is to mid-frequency noise;
Or described characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, and, unit interval crest number threshold value,
Described first judge module 320 is specifically for judging whether that meeting unit interval crest number is more than or equal to the 11 threshold value simultaneously, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, wherein, n is real number, and when meeting four conditions at the same time, output detections is to mid-frequency noise.
Noise detection apparatus 300 shown in Fig. 3 can perform each step of the method shown in Fig. 1, specifically refers to Fig. 1 and associated description, this time does not repeat to repeat.
By implementing the embodiment of the present invention, can calculate the characteristic parameter of electrocardiosignal, and when characteristic parameter meets mid-frequency noise condition, output detections, to mid-frequency noise, is reminded in doctor's electrocardiosignal and be there is mid-frequency noise, prevent doctor to patient's mistaken diagnosis.
Consult Fig. 4, Fig. 4 is the structural representation of another embodiment of noise detection apparatus of the present invention.Described noise detection apparatus 400 comprises: pretreatment module 410, computing module 420, first judge module 430 and the second judge module 440.
Described pretreatment module 410 is for carrying out pretreatment to obtain electrocardiosignal to the detection signal of input;
Described computing module 420 is for calculating to the electrocardiosignal of input the characteristic parameter obtaining described electrocardiosignal;
Described first judge module 430 is for judging whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections is to mid-frequency noise;
Described second judge module 440 is for judging whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections is to baseline drift noise.
Alternatively, described characteristic parameter comprises adjacent cells time crest number and does not change number of times and baseline drift noise proportional coefficient,
Described second judge module 440 does not change number of times be less than first threshold specifically for judging whether to meet adjacent cells time crest number simultaneously, with, baseline drift noise proportional coefficient is greater than Second Threshold two conditions, and when meeting described two conditions at the same time, output detections is to baseline drift noise;
Or described characteristic parameter comprises baseline drift noise proportional coefficient,
Described second judge module 440 is specifically for judging whether baseline drift noise proportional coefficient is greater than the 3rd threshold value, and when baseline drift noise proportional coefficient is greater than the 3rd threshold value, output detections is to baseline drift noise.
Alternatively, described characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, and, minimum crest interval rule degree parameter,
Described first judge module 430 is specifically for judging whether that meeting unit interval crest number is more than or equal to the 4th threshold value simultaneously, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions, when meeting three conditions at the same time, output detections is to mid-frequency noise;
Or, described characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, and, unit interval broad peak number ratio,
Described first judge module 430 meets unit interval amplitude square simultaneously specifically for judging whether and is greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, with, unit interval broad peak number ratio is less than the tenth threshold value five conditions, wherein, m is real number, and when meeting five conditions at the same time, output detections is to mid-frequency noise;
Or described characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, and, unit interval crest number threshold value,
Described first judge module 430 is specifically for judging whether that meeting unit interval crest number is more than or equal to the 11 threshold value simultaneously, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, wherein, n is real number, and when meeting four conditions at the same time, output detections is to mid-frequency noise.
Noise detection apparatus 400 shown in Fig. 4 can perform each step of the method shown in Fig. 1 and Fig. 2, specifically refers to Fig. 1, Fig. 2 and associated description, this time does not repeat to repeat.
By implementing the embodiment of the present invention, can calculate the characteristic parameter of electrocardiosignal, and when characteristic parameter meets mid-frequency noise condition, output detections, to mid-frequency noise, is reminded in doctor's electrocardiosignal and be there is mid-frequency noise, prevent doctor to patient's mistaken diagnosis.
In addition, in present embodiment, judging characteristic parameter baseline drift noise conditions can also whether be met, and when characteristic parameter meets baseline drift noise conditions, output detections, to baseline drift noise, is reminded in doctor's electrocardiosignal and be there is baseline drift noise, prevent doctor to patient's mistaken diagnosis.And, before statistical nature parameter, also pretreatment is carried out to detection signal, some interfering signals are filtered out, improve the correctness detected.
The present invention further comprises a kind of medical treatment detection device, and described medical treatment detection device comprises above-mentioned noise detection apparatus, specifically refers to Fig. 3, Fig. 4 and related description, no longer launches to repeat herein.
One of ordinary skill in the art will appreciate that all or part of flow process realized in above-described embodiment method, that the hardware that can carry out instruction relevant by computer program has come, described program can be stored in a computer read/write memory medium, this program, when performing, can comprise the flow process of the embodiment as above-mentioned each side method.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-OnlyMemory, ROM) or random store-memory body (RandomAccessMemory, RAM) etc.
Above disclosedly be only a kind of preferred embodiment of the present invention, certainly the interest field of the present invention can not be limited with this, one of ordinary skill in the art will appreciate that all or part of flow process realizing above-described embodiment, and according to the equivalent variations that the claims in the present invention are done, still belong to the scope that invention is contained.
Claims (11)
1. a noise detecting method, is characterized in that, comprising:
The characteristic parameter obtaining described electrocardiosignal is calculated to the electrocardiosignal of input;
Judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections is to mid-frequency noise.
2. method according to claim 1, is characterized in that, the described electrocardiosignal to input also comprises after calculating to obtain the characteristic parameter of described electrocardiosignal:
Judge whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections is to baseline drift noise.
3. method according to claim 2, it is characterized in that, described characteristic parameter comprises adjacent cells time crest number and does not change number of times and baseline drift noise proportional coefficient, describedly judge whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections comprises to baseline drift noise:
Judge whether to meet adjacent cells time crest number not change number of times and be less than first threshold, and baseline drift noise proportional coefficient is greater than Second Threshold two conditions simultaneously;
If meet described two conditions simultaneously, then output detections is to baseline drift noise;
Or described characteristic parameter comprises baseline drift noise proportional coefficient, describedly judge whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections comprises to baseline drift noise:
Judge whether baseline drift noise proportional coefficient is greater than the 3rd threshold value;
If baseline drift noise proportional coefficient is greater than the 3rd threshold value, then output detections is to baseline drift noise.
4. method according to claim 1, is characterized in that,
Described characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, with, minimum crest interval rule degree parameter, describedly judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections comprises to mid-frequency noise:
Judge whether that meet unit interval crest number is more than or equal to the 4th threshold value simultaneously, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions;
If meet three conditions simultaneously, then output detections is to mid-frequency noise;
Or, described characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, with, unit interval broad peak number ratio, describedly judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections comprises to mid-frequency noise:
Judge whether meet unit interval amplitude square simultaneously and be greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, with, unit interval broad peak number ratio is less than the tenth threshold value five conditions, and wherein, m is real number;
If meet five conditions simultaneously, then output detections is to mid-frequency noise;
Or, described characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, with, unit interval crest number threshold value, describedly judge whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections comprises to mid-frequency noise:
Judge whether that meet unit interval crest number is more than or equal to the 11 threshold value simultaneously, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, wherein, n is real number;
If meet four conditions simultaneously, then output detections is to mid-frequency noise.
5. method according to claim 1, is characterized in that, the described electrocardiosignal to input comprises before calculating to obtain the characteristic parameter of described electrocardiosignal:
Pretreatment is carried out to obtain electrocardiosignal to the detection signal of input.
6. a noise detection apparatus, is characterized in that, comprising: computing module and the first judge module,
Described computing module is used for calculating to the electrocardiosignal of input the characteristic parameter obtaining described electrocardiosignal;
Described first judge module is for judging whether described characteristic parameter meets mid-frequency noise condition, if described characteristic parameter meets described mid-frequency noise condition, then output detections is to mid-frequency noise.
7. device according to claim 6, is characterized in that, described device also comprises the second judge module,
Described second judge module is for judging whether described characteristic parameter meets baseline drift noise conditions, if described characteristic parameter meets described baseline drift noise conditions, then output detections is to baseline drift noise.
8. device according to claim 7, is characterized in that,
Described characteristic parameter comprises adjacent cells time crest number and does not change number of times and baseline drift noise proportional coefficient,
Described second judge module does not change number of times be less than first threshold specifically for judging whether to meet adjacent cells time crest number simultaneously, with, baseline drift noise proportional coefficient is greater than Second Threshold two conditions, and when meeting described two conditions at the same time, output detections is to baseline drift noise;
Or described characteristic parameter comprises baseline drift noise proportional coefficient,
Described second judge module is specifically for judging whether baseline drift noise proportional coefficient is greater than the 3rd threshold value, and when baseline drift noise proportional coefficient is greater than the 3rd threshold value, output detections is to baseline drift noise.
9. device according to claim 6, is characterized in that,
Described characteristic parameter comprises unit interval crest number, adjacent peaks width change frequency, maximum crest interval rule degree parameter, and, minimum crest interval rule degree parameter,
Described first judge module is specifically for judging whether that meeting unit interval crest number is more than or equal to the 4th threshold value simultaneously, adjacent peaks width change frequency is greater than the 5th threshold value divided by the ratio that unit interval crest number obtains, with, maximum crest interval rule degree parameter and minimum crest interval rule degree parameter are all less than the 6th threshold value three conditions, when meeting three conditions at the same time, output detections is to mid-frequency noise;
Or, described characteristic parameter comprise unit interval amplitude square and, amplitude square and threshold value, unit interval crest number, unit interval crest number threshold value, baseline drift noise proportional coefficient, and, unit interval broad peak number ratio,
Described first judge module meets unit interval amplitude square simultaneously specifically for judging whether and is greater than m double amplitude sum of the squares of the degree threshold value, unit interval crest number is more than or equal to the 7th threshold value, the difference of unit interval crest number and unit interval crest number threshold value is greater than the 8th threshold value, baseline drift noise proportional coefficient is less than the 9th threshold value, and unit interval broad peak number ratio is less than the tenth threshold value five conditions, wherein, m is real number, and when meeting five conditions at the same time, output detections is to mid-frequency noise;
Or described characteristic parameter comprises unit interval crest number, baseline drift noise proportional coefficient, adjacent cells time crest number does not change number of times, and, unit interval crest number threshold value,
Described first judge module is specifically for judging whether that meeting unit interval crest number is more than or equal to the 11 threshold value simultaneously, baseline drift noise proportional coefficient is greater than the 12 threshold value, adjacent cells time crest number does not change number of times and is less than the 13 threshold value, unit interval crest number is greater than n times of unit interval crest number threshold value four conditions, wherein, n is real number, and when meeting four conditions at the same time, output detections is to mid-frequency noise.
10. device according to claim 6, is characterized in that, described device also comprises pretreatment module, and described pretreatment module is used for carrying out pretreatment to obtain electrocardiosignal to the detection signal of input.
11. 1 kinds of medical treatment detection devices, is characterized in that, described medical treatment detection device comprises the noise detection apparatus as described in claim as arbitrary in claim 6-10.
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