CN110558970A - electrocardiosignal analysis method for wearable intelligent underwear - Google Patents

electrocardiosignal analysis method for wearable intelligent underwear Download PDF

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CN110558970A
CN110558970A CN201910953944.3A CN201910953944A CN110558970A CN 110558970 A CN110558970 A CN 110558970A CN 201910953944 A CN201910953944 A CN 201910953944A CN 110558970 A CN110558970 A CN 110558970A
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heart
sinus
heart beat
beat
interval
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王伟江
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Yantai Qichuang Medical Technology Co Ltd
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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/318Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/24Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316Modalities, i.e. specific diagnostic methods
    • A61B5/318Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346Analysis of electrocardiograms
    • A61B5/349Detecting specific parameters of the electrocardiograph cycle
    • A61B5/352Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6802Sensor mounted on worn items
    • A61B5/6804Garments; Clothes
    • A61B5/6805Vests
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/72Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A61B5/7207Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts

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  • Artificial Intelligence (AREA)
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  • Physiology (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Abstract

The invention discloses an electrocardiosignal analysis method for wearable intelligent underwear, which comprises the following steps: s1, collecting electrocardiosignals; s2, basic filtering is carried out; s3, performing band-pass filtering on the acquired electrocardiosignals one by one, and then calculating the difference; s4, setting an initial detection threshold value and a return detection threshold value: setting an initial value of a detection threshold value, and taking 1/2 of the detection threshold value as the initial value of a return detection threshold value; s5, judging whether R waves exist or not by detecting a threshold value every time an electrocardiographic waveform is collected for one second, and determining the vertex position of the R waves; if the R wave is not detected by more than 7/4 of the average RR interval, performing R wave recheck by using a recheck threshold value; and S6, updating the detection threshold value by using the maximum difference value corresponding to the R wave every time one R wave is detected. Therefore, the method effectively eliminates the larger baseline drift of the dynamic electrocardiosignals, and better retains the key characteristics of the electrocardiosignals; external factors such as motion interference, myoelectric interference and the like are effectively filtered, and accurate analysis of the electrocardiosignal is ensured.

Description

electrocardiosignal analysis method for wearable intelligent underwear
Technical Field
the invention relates to the field of electrocardiosignal analysis, in particular to an electrocardiosignal analysis method for wearable intelligent underwear.
Background
With the development of economy, health issues become more and more the focus of attention of people. According to statistics, the incidence rate of cardiovascular diseases is continuously increased, and heart diseases also become the main diseases threatening life and health. The electrocardiosignal is the most direct means for diagnosing heart diseases and can directly reflect heart rhythm and physiological conditions of all parts. Analysis of electrocardiosignals is the focus of research in the medical field at present.
Most of traditional electrocardiosignal tests are static acquisition, namely, the electrocardiosignals are attached to a human body and connected with monitoring equipment through a lead, a tested person lies on a bed for several minutes to several hours generally, and the method greatly occupies the time of medical care personnel and patients.
The electrocardiogram monitor is integrated into the wearable intelligent underwear, so that the intelligent underwear has the electrocardiogram monitoring function, has the characteristics of comfort, portability, real-time performance, unlimited monitoring duration and the like, and is a new development direction of electrocardiogram monitoring. However, the wearable electrocardiograph monitor measures in the state of daily life movement of people, and compared with static acquisition, a plurality of interference factors such as movement interference, electromyographic interference and the like are introduced, and the electrocardiogram obtained by adding such interference signals cannot be identified by the static acquisition electrocardiograph monitor, so that a new method for processing the electrocardiogram detected by the wearable electrocardiograph monitor is needed at present, so that the newly introduced interference factors can be better filtered, and useful information in the electrocardiogram can be retained.
as shown in fig. 2, a normal waveform of cardiac activity mainly includes P-wave, QRS complex and T-wave, wherein the waveforms, the wave band time and the shape represent the activity of each part of the heart, which is as follows:
P wave: the P wave represents the potential change in the depolarization process of the left and right atrial muscles, the P wave is small and circular, the normal P wave width range is 0.08-0.11 seconds, and the amplitude of the limb lead is not more than 0.25 mv.
QRS complex: also called QRS complex, which represents the change of electric potential during the depolarization process of the left and right ventricles. A typical QRS complex consists of three wave bands, wherein the first wave is downward and is called Q wave, the second wave is upward and is high and sharp in shape and is called R wave, the last wave is downward and is called S wave, and the width of the normal QRS complex is 0.06-0.1 second.
T wave: the T wave represents the potential change in the repolarization process of the ventricles, the amplitude is not less than 1/10 of that of the R wave, the direction is consistent with the QRS main wave direction, and the width is generally 0.05-0.25 seconds.
TP-Ri.e., P-R interval: the time interval from the beginning of the P wave to the beginning of the QRS complex represents the time from the start of atrial activation to the start of ventricular activation, i.e., represents the time of conduction of excitation between the atria and ventricles. The time range is 0.12-0.2 seconds, and children should not exceed 0.19 seconds. When atrioventricular conduction is blocked, the P-R interval is prolonged.
and (2) S-T section: the band from the end of the QRS complex to the beginning of the T wave, which is near baseline, represents a slow repolarization process of the ventricles.
TQ-TI.e., Q-T interval: the time interval from the beginning of the QRS complex to the end of the T wave represents the time required for the ventricles to fully recover from excitation, depolarization, and to rest, which is related to the heart rate.
The waveform and interval of electrocardiosignals represent the activity of each part of heart, and can be used for diagnosing various arrhythmia and other cardiovascular diseases. In most cases, the abnormal electrophysiological activity of the heart is low in frequency in the initial disease stage, and the conventional electrocardiograph is difficult to capture the abnormal electrophysiological activity of the heart, so that the electrocardiograph has important significance for long-term electrocardiographic monitoring of patients. The wearable medical technology can be worn for a long time to perform electrocardiographic monitoring in a daily life state, analyze electrocardiographic waveforms in real time, perform abnormity early warning, remotely monitor doctors and communicate in time to give medical advice, but when signals are detected in a motion state, factors such as motion interference and myoelectric interference are introduced, how to filter the external interference factors and accurately identify the position of an R wave is a problem to be solved urgently by the wearable electrocardiographic monitoring method.
disclosure of Invention
the technical problem to be solved by the invention is as follows: how to effectively analyze the dynamic electrocardiogram collected under the motion state.
For the analysis of electrocardiogram, the most important is to determine the position of R wave, in order to solve the above technical problems, the technical scheme adopted by the invention is as follows:
An electrocardiosignal analysis method for a wearable intelligent underwear comprises the following steps:
S1, collecting electrocardiosignals;
S2, basic filtering is carried out;
s3, performing band-pass filtering on the acquired electrocardiosignals one by one, and then calculating the difference; the formula in which the difference is calculated: (x (i) -x (i-4))2+ (x (i-1) -x (i-3)); wherein x (i) is the ith sampling point of the electrocardiosignal;
S4, setting an initial detection threshold value and a return detection threshold value: dividing the difference data of the first 3 seconds into 8 sections, respectively searching the maximum value of each section as Xmax 1-Xmax 8, taking 11/32 of the median value of Xmax 1-Xmax 8 as the initial value of the detection threshold, and taking 1/2 of the detection threshold as the return detection threshold;
S5, judging whether R waves exist or not by detecting a threshold value every time an electrocardiographic waveform is collected for one second, and determining the vertex position of the R waves; if the R wave is not detected by more than 7/4 of the average RR interval, performing R wave recheck by using a recheck threshold value; the RR interval is the time difference of two adjacent R waves; setting an average RR interval initial value to be 3 seconds;
And S6, updating the detection threshold value by using the maximum difference value corresponding to the R wave every time one R wave is detected.
The beneficial effects obtained by the invention are as follows:
The large baseline drift of the dynamic electrocardiosignals is effectively eliminated, and the key characteristics of the electrocardiosignals are better kept; external factors such as motion interference, myoelectric interference and the like are effectively filtered, and accurate analysis of electrocardiosignals collected in a motion state is ensured.
on the basis of the scheme, the scheme can be further improved as follows.
further, the basic filtering in step S2 includes high-pass filtering, 50Hz power frequency filtering, and low-pass filtering, where the high-pass filtering cutoff frequency is 0.26Hz, and the order is 2; the upper and lower limits of a power frequency filter passband are 49.5Hz and 52Hz, the attenuation coefficient is 0.5, the upper and lower limits of a stop band are 50Hz and 51.5Hz, the attenuation coefficient is 3, and the order of the filter is 6; the low-pass filter cut-off frequency is 40Hz, and the order is 3.
Further, according to the two detected adjacent R waves, an RR interval is calculated in real time, wherein the RR interval refers to the time difference of the two adjacent R waves;
further, according to the two adjacent detected R waves, calculating the heart rate in real time: heart rate is 60 seconds/RR interval, where RR interval units are seconds.
Further, according to the detected R wave, whether arrhythmia exists is judged, and the specific steps are as follows:
SS1, judging whether there is any missing beat or asystole condition; the judgment standard of the missed beat is that the RR interval is more than 1.5 seconds, namely the interval of two heart beats is more than 1.5 seconds; the judgment criterion of the asystole is that no R wave is detected for 3 seconds continuously, namely that no heart beat is detected for 3 seconds continuously.
SS2, judging the heart beat type when detecting one R wave;
SS2-1, calculating reference interval, using the average value of the latest 5 sinus heart beat intervals as the reference interval, if the sinus heart beat intervals are less than 5, supplementing with sinus heart beat template intervals.
SS2-2, calculating the correlation distance according to the following formula
Where x is the sinus template heart beat, y is the current heart beat, x and y are both N in length, and the two R wave vertices are aligned. And (3) calculating 3 correlation distances respectively by taking the current heart beat and the previous 3 sinus heart beats, and taking the median as the final correlation distance.
SS2-3, judging the heart beat type according to the interval advance rate, the related distance, the heart beat amplitude and the heart beat width:
i. if the heart beat is 10% ahead and the related distance is more than 0.1, or the heart beat is 10% ahead and the R amplitude exceeds the normal reference value by 1.2 millivolts and more, or the related distance is more than 0.1 and the R amplitude is high and the QRS width exceeds the normal reference value by 0.10s and more, the ventricular heart beat is judged;
Otherwise, if the heart beat is 20% ahead, atrial premature beat;
Otherwise, sinus heartbeat.
SS3, judging whether sinus abnormality is caused according to the heart beat type and RR interval, wherein the sinus abnormality comprises sinus tachycardia and sinus bradycardia; wherein the sinus tachycardia judging standard is that 3 or more sinus heartbeats are continuous, and the heart rate is more than 100; the sinus bradycardia is judged under the condition that 3 or more sinus heartbeats are continuously performed, and the heart rate is less than 60.
SS4, judging whether ventricular abnormality exists according to the heart beat type and RR interval. The ventricular anomalies include single ventricular, paired ventricular, ventricular velocity, ventricular bigeminy, and ventricular trigeminy. Wherein the ventricular rate judgment standard is continuous 3 or more ventricular heart beats; the ventricular bigeminy judgment standard is that sinus heart beat and ventricular heart beat are continuous for 3 pairs or more; the ventricular triple rhythm judgment condition is that sinus heart beat + ventricular heart beat are continuous for 3 pairs or more.
SS5, judging whether atrial premature beat is abnormal according to the heart beat type and RR interval. The atrial premature beat abnormity comprises single atrial premature, paired atrial premature, atrial pace, atrial premature double-joint law and atrial premature triple-joint law. Wherein, the judgment standard of the atrial speed is continuous 3 or more atrial premature beats; the atrial-premature bigeminy law judgment standard is that sinus heart beat and atrial premature heart beat are continuous for 3 pairs or more; the atria triple rhythm judgment standard is that sinus heart beat, sinus heart beat and atria early heart beat are continuous for 3 pairs or more.
SS6, every 10 heartbeats are detected, and whether atrial fibrillation exists or not is judged according to each RR interval. The detection standard of atrial fibrillation is that the continuous 10 heart beat heart rates are absolutely unequal, namely the RR interval is shortened irregularly, and more than 10 continuous QRS waves are atrial fibrillation.
further, statistics are carried out on the detection result in each second, including the number of heart beats, the position, the heart beat type and the RR interval.
further, after the collection is finished, the average heart rate, the fastest heart rate, the slowest heart rate, the over-fast heart rate proportion, the slightly-fast heart rate proportion, the normal heart rate proportion, the slightly-slow heart rate proportion and the over-slow heart rate proportion in the whole monitoring process are calculated in a statistical mode; wherein, the too fast heart rate means the heart rate is more than 120, the slightly fast heart rate means more than 100, the slightly slow heart rate means less than 60, the too slow heart rate means less than 50, and the ratio is the ratio of all heartbeats respectively and forms a report.
Compared with the prior art, the invention has the following technical effects:
The large baseline drift of the dynamic electrocardiosignals is effectively eliminated, and the key characteristics of the electrocardiosignals are better kept; external factors such as motion interference and myoelectric interference are effectively filtered, accurate analysis of electrocardiosignals collected in a motion state is guaranteed, the positions of R waves are accurately identified, electrocardio data are updated in real time according to each detected R wave, and powerful data support is provided for users and doctors to know the body states of the users and the doctors.
drawings
FIG. 1 is a schematic flow chart of an electrocardiosignal analysis method for a wearable intelligent underwear of the invention;
FIG. 2 is a schematic diagram of a normal electrocardiogram;
the meaning of some of the reference symbols in the drawings is as follows:
P, P waves;
q, Q waves;
r, R waves;
s, S waves;
t, T waves;
A P-R, P-R segment;
A section S-T, S-T;
TP-Ra P-R interval;
TQ-TQ-T interval.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
fig. 1 is a schematic structural diagram of an electrocardiosignal analysis method for a wearable intelligent underwear according to the present invention. The electrocardiosignal analysis method for the wearable intelligent underwear comprises the following steps:
S1, collecting electrocardiosignals;
S2, basic filtering is carried out; the basic filtering comprises high-pass filtering, 50Hz power frequency filtering and low-pass filtering, wherein the cut-off frequency of the high-pass filtering is 0.26Hz, and the order is 2; the upper and lower limits of a power frequency filter passband are 49.5Hz and 52Hz, the attenuation coefficient is 0.5, the upper and lower limits of a stop band are 50Hz and 51.5Hz, the attenuation coefficient is 3, and the order of the filter is 6; the low-pass filter cut-off frequency is 40Hz, and the order is 3.
s3, performing band-pass filtering on the acquired electrocardiosignals one by one, and then calculating the difference; the formula in which the difference is calculated: (x (i) -x (i-4))2+ (x (i-1) -x (i-3)); wherein x (i) is the ith sampling point of the electrocardiosignal;
S4, setting an initial detection threshold value and a return detection threshold value: dividing the difference data of the first 3 seconds into 8 sections, respectively searching the maximum value of each section as Xmax 1-Xmax 8, taking 11/32 of the median value of Xmax 1-Xmax 8 as the initial value of the detection threshold, and taking 1/2 of the detection threshold as the return detection threshold;
s5, judging whether R waves exist or not by detecting a threshold value every time an electrocardiographic waveform is collected for one second, and determining the vertex position of the R waves; according to the two detected adjacent R waves, an RR interval is calculated in real time, and the RR interval refers to the time difference of the two adjacent R waves;
if the R wave is not detected by more than 7/4 of the average RR interval, performing R wave recheck by using a recheck threshold value; the RR interval is the time difference of two adjacent R waves; setting an average RR interval initial value to be 3 seconds;
and calculating the heart rate in real time according to the two detected adjacent R waves: heart rate is 60 seconds/RR interval, where RR interval units are seconds.
And S6, updating the detection threshold value by using the maximum difference value corresponding to the R wave every time one R wave is detected.
further, according to the detected R wave, whether arrhythmia exists is judged, and the specific steps are as follows:
SS1, judging whether there is any missing beat or asystole condition; the judgment standard of the missed beat is that the RR interval is more than 1.5 seconds, namely the interval of two heart beats is more than 1.5 seconds; the judgment criterion of the asystole is that no R wave is detected for 3 seconds continuously, namely that no heart beat is detected for 3 seconds continuously.
SS2, judging the heart beat type when detecting one R wave;
SS2-1, calculating reference interval, using the average value of the latest 5 sinus heart beat intervals as the reference interval, if the sinus heart beat intervals are less than 5, supplementing with sinus heart beat template intervals.
SS2-2, calculating the correlation distance according to the following formula
Where x is the sinus template heart beat, y is the current heart beat, x and y are both N in length, and the two R wave vertices are aligned. And (3) calculating 3 correlation distances respectively by taking the current heart beat and the previous 3 sinus heart beats, and taking the median as the final correlation distance.
SS2-3, judging the heart beat type according to the interval advance rate, the related distance, the heart beat amplitude and the heart beat width:
i. If the heart beat is 10% ahead and the related distance is more than 0.1, or the heart beat is 10% ahead and the R amplitude exceeds the normal reference value by 1.2 millivolts and more, or the related distance is more than 0.1 and the R amplitude is high and the QRS width exceeds the normal reference value by 0.10s and more, the ventricular heart beat is judged;
Otherwise, if the heart beat is 20% ahead, atrial premature beat;
Otherwise, sinus heartbeat.
SS3, judging whether sinus abnormality is caused according to the heart beat type and RR interval, wherein the sinus abnormality comprises sinus tachycardia and sinus bradycardia; wherein the sinus tachycardia judging standard is that 3 or more sinus heartbeats are continuous, and the heart rate is more than 100; the sinus bradycardia is judged under the condition that 3 or more sinus heartbeats are continuously performed, and the heart rate is less than 60.
SS4, judging whether ventricular abnormality exists according to the heart beat type and RR interval. The ventricular anomalies include single ventricular, paired ventricular, ventricular velocity, ventricular bigeminy, and ventricular trigeminy. Wherein the ventricular rate judgment standard is continuous 3 or more ventricular heart beats; the ventricular bigeminy judgment standard is that sinus heart beat and ventricular heart beat are continuous for 3 pairs or more; the ventricular triple rhythm judgment condition is that sinus heart beat + ventricular heart beat are continuous for 3 pairs or more.
SS5, judging whether atrial premature beat is abnormal according to the heart beat type and RR interval. The atrial premature beat abnormity comprises single atrial premature, paired atrial premature, atrial pace, atrial premature double-joint law and atrial premature triple-joint law. Wherein, the judgment standard of the atrial speed is continuous 3 or more atrial premature beats; the atrial-premature bigeminy law judgment standard is that sinus heart beat and atrial premature heart beat are continuous for 3 pairs or more; the atria triple rhythm judgment standard is that sinus heart beat, sinus heart beat and atria early heart beat are continuous for 3 pairs or more.
SS6, every 10 heartbeats are detected, and whether atrial fibrillation exists or not is judged according to each RR interval. The detection standard of atrial fibrillation is that the continuous 10 heart beat heart rates are absolutely unequal, namely the RR interval is shortened irregularly, and more than 10 continuous QRS waves are atrial fibrillation.
and counting the detection result in each second, including the number of heart beats, the position, the heart beat type and the RR interval. After the collection is finished, the average heart rate, the fastest heart rate, the slowest heart rate, the over-fast heart rate proportion, the slightly fast heart rate proportion, the normal heart rate proportion, the slightly slow heart rate proportion and the over-slow heart rate proportion in the whole monitoring process are calculated in a statistical mode; wherein, the too fast heart rate means the heart rate is more than 120, the slightly fast heart rate means more than 100, the slightly slow heart rate means less than 60, the too slow heart rate means less than 50, and the ratio is the ratio of all heartbeats respectively and forms a report.
The electrocardiosignal analysis method for the wearable intelligent underwear effectively eliminates the larger baseline drift of dynamic electrocardiosignals, and better retains the key characteristics of the electrocardiosignals; external factors such as motion interference, myoelectric interference and the like are effectively filtered, and accurate analysis of electrocardiosignals collected in a motion state is ensured.
the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (7)

1. An electrocardiosignal analysis method for a wearable intelligent underwear is characterized by comprising the following steps:
S1, collecting electrocardiosignals;
s2, basic filtering is carried out;
S3, performing band-pass filtering on the acquired electrocardiosignals one by one, and then calculating the difference; the formula for calculating the difference is as follows: (x (i) -x (i-4))2+ (x (i-1) -x (i-3)), wherein x (i) is the ith sampling point of the electrocardiosignal;
s4, setting an initial detection threshold value and a return detection threshold value: dividing the difference data of the first 3 seconds into 8 sections, respectively searching the maximum value of each section as Xmax 1-Xmax 8, taking 11/32 of the median value of Xmax 1-Xmax 8 as the initial value of the detection threshold, and taking 1/2 of the detection threshold as the return detection threshold;
s5, judging whether R waves exist or not by detecting a threshold value every time an electrocardiographic waveform is collected for one second, and determining the vertex position of the R waves; if the R wave is not detected by more than 7/4 of the average RR interval, performing R wave recheck by using a recheck threshold value; the RR interval is the time difference of two adjacent R waves;
And S6, updating the detection threshold value by using the maximum difference value corresponding to the R wave every time one R wave is detected.
2. the electrocardiosignal analysis method for the wearable intelligent underwear according to claim 1, wherein the basic filtering in the step S2 comprises high-pass filtering, 50Hz power frequency filtering and low-pass filtering, wherein the high-pass filtering has a cutoff frequency of 0.26Hz and an order of 2; the upper and lower limits of a power frequency filter passband are 49.5Hz and 52Hz, the attenuation coefficient is 0.5, the upper and lower limits of a stop band are 50Hz and 51.5Hz, the attenuation coefficient is 3, and the order of the filter is 6; the low-pass filter cut-off frequency is 40Hz, and the order is 3.
3. the electrocardiosignal analysis method for the wearable intelligent underwear is characterized in that the RR interval is calculated in real time according to the two detected adjacent R waves.
4. the electrocardiosignal analysis method for the wearable intelligent underwear according to claim 3, wherein the heart rate is calculated in real time according to the two detected adjacent R waves: heart rate is 60/RR interval.
5. The electrocardiosignal analysis method for the wearable intelligent underwear according to claim 4, wherein whether arrhythmia exists is judged in real time according to the detected R wave, and the method comprises the following specific steps:
SS1, judging whether there is any missing beat or asystole condition; the judgment standard of the missed beat is that the RR interval is more than 1.5 seconds, namely the interval of two heart beats is more than 1.5 seconds; the judgment standard of the asystole is that the R wave is not detected for 3 seconds continuously, namely the heart beat is not detected for 3 seconds continuously;
SS2, judging the heart beat type when detecting one R wave;
SS2-1, calculating a reference interval, and taking the average value of the latest 5 sinus heartbeat intervals as the reference interval;
SS2-2, calculating the correlation distance according to the following formula
Wherein x is a sinus template heart beat, y is a current heart beat, the lengths of x and y are both N, the vertexes of R waves of the x and y are aligned, 3 correlation distances are respectively calculated by taking the current heart beat and the front 3 sinus heart beats, and the median value is taken as the final correlation distance;
SS2-3, judging the heart beat type according to the interval advance rate, the related distance, the heart beat amplitude and the heart beat width:
i. ventricular heart beat if heart beat is 10% earlier and correlation distance is greater than 0.1, or heart beat is 10% earlier and R amplitude is high, or correlation distance is greater than 0.1 and R amplitude is high and QRS width is large;
otherwise, if the heart beat is 20% ahead, atrial premature beat;
otherwise, sinus heartbeat;
SS3, judging whether sinus abnormality is caused according to the heart beat type and RR interval, wherein the sinus abnormality comprises sinus tachycardia and sinus bradycardia; wherein the sinus tachycardia judging standard is that 3 or more sinus heartbeats are continuous, and the heart rate is more than 100; judging whether the sinus bradycardia is continuous for 3 or more sinus heartbeats, wherein the heart rate is less than 60;
SS4, judging whether the ventricular abnormality exists according to the heart type and RR interval; the ventricular anomalies comprise single ventricular, paired ventricular, ventricular velocity, ventricular bigeminy, and ventricular trigeminy; wherein the ventricular rate judgment standard is continuous 3 or more ventricular heart beats; the ventricular bigeminy judgment standard is that sinus heart beat and ventricular heart beat are continuous for 3 pairs or more; the ventricular triple rhythm judgment condition is that sinus heart beat, sinus heart beat and ventricular heart beat are continuous for 3 pairs or more;
SS5, judging whether atrial premature beat is abnormal according to the heart beat type and RR interval. The atrial premature beat abnormity comprises single atrial premature, paired atrial premature, atrial pace, atrial premature double-joint law and atrial premature triple-joint law; wherein, the judgment standard of the atrial speed is continuous 3 or more atrial premature beats; the atrial-premature bigeminy law judgment standard is that sinus heart beat and atrial premature heart beat are continuous for 3 pairs or more; the atria triple rhythm judgment standard is that the sinus heart beat, the sinus heart beat and the atria early heart beat are continuous for 3 pairs or more;
SS6, judging whether atrial fibrillation exists or not according to each RR interval when 10 heart beats are detected; the detection standard of atrial fibrillation is that the continuous 10 heart beat heart rates are absolutely unequal.
6. the electrocardiosignal analysis method for the wearable intelligent underwear is characterized in that the detection results in each second are counted, wherein the detection results comprise heart beat times, positions, heart beat types and RR intervals.
7. The electrocardiosignal analysis method for the wearable intelligent underwear is characterized in that after the collection is finished, the average heart rate, the fastest heart rate and the slowest heart rate, the over-fast heart rate proportion, the slightly fast heart rate proportion, the normal heart rate proportion, the slightly slow heart rate proportion and the over-slow heart rate proportion in the whole monitoring process are calculated in a statistical mode; wherein, the too fast heart rate means the heart rate is more than 120, the slightly fast heart rate means more than 100, the slightly slow heart rate means less than 60, the too slow heart rate means less than 50, the ratio is the ratio of all heartbeats respectively, and the report is formed.
CN201910953944.3A 2019-10-09 2019-10-09 electrocardiosignal analysis method for wearable intelligent underwear Pending CN110558970A (en)

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Application publication date: 20191213