WO2018082190A1 - 一种ecg信号处理方法及装置 - Google Patents

一种ecg信号处理方法及装置 Download PDF

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Publication number
WO2018082190A1
WO2018082190A1 PCT/CN2016/113967 CN2016113967W WO2018082190A1 WO 2018082190 A1 WO2018082190 A1 WO 2018082190A1 CN 2016113967 W CN2016113967 W CN 2016113967W WO 2018082190 A1 WO2018082190 A1 WO 2018082190A1
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time difference
signal
wave
ecg
threshold
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PCT/CN2016/113967
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English (en)
French (fr)
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吕超
朱萸
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华为技术有限公司
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Priority to US16/086,863 priority Critical patent/US11337638B2/en
Priority to CN201680080606.8A priority patent/CN108601543B/zh
Publication of WO2018082190A1 publication Critical patent/WO2018082190A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/366—Detecting abnormal QRS complex, e.g. widening
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/25—Bioelectric electrodes therefor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/352—Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/364—Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7221—Determining signal validity, reliability or quality

Definitions

  • the present invention relates to the field of terminals, and in particular, to an ECG signal processing method and apparatus.
  • ECG Electrocardio Graph
  • single-lead ECG acquisition devices use analog limb I lead (two-handed) or simulated chest lead (thoracic, trans-heart) measurement methods, which are close to the ECG obtained by the standard lead system. Signals are currently widely used in portable ECG analysis services.
  • large interference may be introduced, and myoelectric interference and motion artifacts are more significant, which seriously affects the accurate calculation of heart rate and accurate analysis of heart rate.
  • Embodiments of the present invention provide an ECG signal processing method and apparatus for solving a single-arm measurement process of single-lead ECG, introducing a large interference, which seriously affects the accurate calculation of heart rate and the accurate analysis of heart rate. .
  • an ECG ECG signal processing method includes:
  • the measuring device collects the ECG signal and extracts the kth effective QRS wave group of the ECG signal, wherein the QRS wave group includes the first extreme point Q before the peak point R of the i-th R wave, and the peak point R of the i-th R wave And a second extreme point S after the peak point R of the i-th R wave, where i ⁇ 2, k ⁇ 2, k ⁇ i, further calculating the kth time difference and the (k+1)th time difference, wherein, the kth time difference is the peak point R of the R wave in the kth effective QRS group and the R wave in the (k+1)th effective QRS group The time difference of the peak point R, the (k+1)th time difference is the peak point R of the R wave in the (k+1)th effective QRS group and the R wave in the (k+2)th effective QRS group The time difference of the peak point R.
  • the measuring device determines the kth The time difference and the (k+1)th time difference are the target time differences; or, if the kth time difference and the (k+1)th time difference are in a preset range, and the (k+1)th time difference and the kth time difference.
  • the measuring device determines that the time difference between the kth time difference and the (k+1)th time difference is less than the average of the time difference is the target time difference, and the time difference average is the first
  • the time difference is the average of all target time differences in the (k-1)th time difference.
  • the target time difference is used to calculate a heart rate value corresponding to the ECG signal.
  • an ECG signal processing method is proposed. First, an effective QRS wave group is extracted from the collected ECG signal, and the accuracy of the ECG feature extraction is improved, and then the R in the adjacent effective QRS group is calculated. The time difference between the peak points of the wave further selects the target time difference that satisfies the condition according to the obtained time difference, thereby determining the heart rate value, greatly eliminating the interference introduced during the one-arm measurement process, and effectively ensuring the heart rate calculation accuracy and heart rate analysis. The accuracy.
  • the extracting the kth valid QRS wave group of the ECG signal comprises: the measuring device determining the first extreme point Q and the second extreme point S corresponding to the i-th R wave Calculating a time difference between the first extreme point Q and the peak point R of the i-th R wave as a first time difference, and a time difference between the peak point R of the i-th R wave and the second extreme point S is a second time The time difference, the time difference between the first extreme point Q and the second extreme point S is a third time difference.
  • the measuring device It is determined that the i-th R wave and the corresponding Q wave and S wave constitute the kth effective QRS wave group.
  • the method provided by the embodiment of the present invention extracts the effective QRS complex from the collected ECG signal, improves the accuracy of the ECG feature extraction, and effectively ensures the accuracy of the heart rate calculation and the accuracy of the heart rhythm analysis.
  • the method further includes:
  • the measuring device calculates a signal parameter corresponding to the ECG signal, and calculates a signal according to at least one signal parameter
  • the evaluation parameter is determined, and the signal quality level of the ECG signal is determined according to the preset evaluation threshold corresponding to the signal evaluation parameter and the signal evaluation parameter.
  • the measuring device can evaluate different signal quality levels, and prompt the user through the terminal, and when the signal quality is poor, prompt the user to find the cause, such as wearing position error, poor contact, and the like.
  • the signal parameters include effective signal power, baseline drift, and in-band noise
  • the signal evaluation parameters include a signal artifact ratio, and a signal-to-band noise ratio, wherein the signal artifact ratio is an effective signal power And the function of baseline drift, the signal-to-band noise ratio is a function of effective signal power and in-band noise;
  • the measuring device determines the signal quality level of the ECG signal according to the preset evaluation threshold corresponding to the signal evaluation parameter and the signal evaluation parameter, including:
  • the signal quality level of the ECG signal is the fourth level when the measuring device determines that the signal artifact ratio is less than or equal to the corresponding preset evaluation threshold, and the signal in-band noise ratio is less than or equal to the corresponding preset evaluation threshold;
  • the first level is better than the second level
  • the second level is better than the third level
  • the third level is better than the fourth level
  • the signal quality level obtained by the method provided by the embodiment of the present invention can be used to predict the quality of the collected signal, and the user can correct the wearing position when determining that the current signal quality level is poor by feeding back the signal quality level to the user.
  • the validity of the collected ECG signal is ensured, thereby effectively ensuring the signal measurement accuracy of the single-arm ECG measuring device.
  • the method before extracting the k-th valid QRS complex of the ECG signal, the method further includes: the measuring device filters the ECG signal, and uses a three-axis accelerometer to fit The motion trajectory of the user compares the filtered ECG signal with the motion trajectory, and deletes the ECG waveform in the filtered ECG signal corresponding to the duration of the motion amplitude value greater than the preset amplitude threshold.
  • the measuring device of the embodiment of the present invention compares the filtered ECG signal with the motion trajectory, and deletes the ECG waveform in the filtered ECG signal corresponding to the motion amplitude value in the motion trajectory that is greater than the preset amplitude threshold. Therefore, the influence of motion artifacts on ECG signal acquisition is eliminated, and the effectiveness of the collected ECG signals is improved.
  • a wearable device in a second aspect, includes: a processor, a memory, a heart rate collector, a power source; wherein, a heart rate collector is configured to collect an ECG signal; a memory is configured to store an instruction; and a processor is configured to call the memory
  • the wearable device proposed in the embodiment of the present invention first extracts the effective QRS wave group from the collected ECG signal, improves the accuracy of the ECG feature extraction, and then calculates the R wave in the adjacent effective QRS wave group.
  • the time difference between the peak points further selects the target time difference that satisfies the condition according to the obtained time difference, thereby determining the heart rate value, greatly eliminating the interference introduced during the one-arm measurement process, and effectively ensuring the accuracy of the heart rate calculation and the accuracy of the heart rate analysis. degree.
  • the method further includes: an accelerometer sensor;
  • Acceleration sensor for detecting the magnitude of acceleration in all directions and fitting the motion trajectory.
  • the filtered ECG signal is compared with the motion trajectory, and the ECG waveform in the filtered ECG signal corresponding to the motion amplitude value in the motion trajectory greater than the preset amplitude threshold is deleted. Therefore, the influence of motion artifacts on ECG signal acquisition is eliminated, and the effectiveness of the collected ECG signals is improved.
  • the present application provides an ECG signal processing apparatus for performing the method of any of the above first aspect or any of the possible implementations of the first aspect.
  • the apparatus comprises means for performing the method of any of the above-described first aspect or any of the possible implementations of the first aspect.
  • FIG. 1 is a flowchart of an overview of an ECG signal processing method in an embodiment of the present invention
  • FIG. 2 is a schematic diagram showing waveform characteristics of a standard ECG signal according to an embodiment of the present invention
  • FIG. 3 is a waveform diagram of an ECG signal after filtering according to an embodiment of the present invention.
  • FIG. 4(a) is a schematic diagram showing an electrode position shift when a user wears a device incorrectly according to an embodiment of the present invention
  • 4(b) is a schematic diagram showing the normal position of the electrode when the user wears the device without error in the embodiment of the present invention
  • FIG. 5 is a schematic diagram of an invalid QRS group in an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of a wearable device according to an embodiment of the present invention.
  • FIG. 7 is a schematic structural diagram of an ECG signal processing apparatus according to an embodiment of the present invention.
  • the embodiment of the present invention provides an ECG signal. Processing method, the method includes:
  • Step 100 The measuring device collects an ECG signal.
  • the measuring device referred to in the embodiment of the present invention is a single-lead ECG collecting device.
  • wearable devices for example, wearable devices and the like.
  • the measuring device collects the ECG signal, for example, the user wears the single-lead ECG acquisition device, opens the switch, and the device enters the self-test phase.
  • the device self-test indicates that the user is wearing the device correctly, the device works normally, otherwise the user is prompted to correct the wearing position. After the device enters the normal working state, it starts to collect the ECG signal of the user.
  • Step 110 The measuring device extracts a kth effective QRS wave group of the ECG signal, wherein the QRS wave group includes a first extreme point Q before the i-th R-wave peak point R, a peak point R of the i-th R-wave, and The second extreme point S after the i-th R-wave peak point R, where i ⁇ 2, k ⁇ 2, k ⁇ i.
  • the measuring device determines whether the peak point R of the current R wave and the two extreme points of the left and right can constitute a valid QRS group. Specifically, the following method can be used to determine the effective method. QRS complex:
  • Figure 2 is a schematic diagram showing the waveform characteristics of a standard ECG signal.
  • the measuring device can determine the first extreme point Q and the second extreme point S corresponding to the i-th R-wave peak point R according to the waveform characteristics of the standard ECG signal, wherein the first extreme point is The first extreme point Q before the i-wave peak point R, and the second extreme point S is the first extreme point Q after the i-th R-wave peak point R, that is, the R-wave peak point R is about two Two extreme points near the side.
  • the measuring device calculates a time difference between the first extreme point Q and the peak point R of the i-th R wave, and records the time difference as the first time difference QS, and calculates the peak point R of the i-th R-wave and the second
  • the time difference between the extreme points S is recorded as the second time difference RS, and the time difference between the first extreme point Q and the second extreme point S is calculated, and the time difference is recorded as the third time difference QS.
  • the measuring device determines that the first time difference, the second time difference, and the third time difference are respectively less than the corresponding first threshold, the second threshold, and the third threshold, determining that the first extreme point Q corresponds to the Q wave, and the second extreme point S corresponds to the S
  • the wave determines that the i-th R-wave and the corresponding Q-wave and S-wave constitute the k-th effective QRS complex.
  • the first threshold, the second threshold, and the third threshold may be set according to an empirical value, as long as the physiological characteristics of the human body are met, and are not limited to the embodiments of the present invention.
  • the first threshold is in the range of 90 to 110 ms, for example, the first threshold may be 100 ms.
  • the second threshold may range from 90 to 110 ms, for example the second threshold may be 100 ms.
  • the third threshold may range from 140 to 160 ms.
  • the third threshold may be 150 ms.
  • the determination condition of the valid QRS group may be QR ⁇ 100 ms, and RS ⁇ 100 ms, and QS ⁇ 150 ms.
  • the QRS complex When any one of the three time differences is greater than or equal to the corresponding threshold, the QRS complex is an invalid QRS complex, and when the three time differences are respectively less than the corresponding threshold, the QRS complex is a valid QRS complex.
  • Step 120 The measuring device calculates a kth time difference and a (k+1)th time difference.
  • the kth time difference is the time difference between the peak point R of the R wave in the kth effective QRS group and the peak point R of the R wave in the (k+1)th effective QRS group, the (k+1)th The time difference is the time difference between the peak point R of the R wave in the (k+1)th effective QRS complex and the peak point R of the R wave in the (k+2)th effective QRS complex.
  • the kth valid QRS group, the (k+1)th effective QRS group, and the (k+2)th effective QRS group are three consecutive groups.
  • the measurement device calculates the time difference of the peak points R of the two R waves in all adjacent valid QRS complexes.
  • Step 130a If the kth time difference and the (k+1)th time difference are in a preset range, and the absolute value of the difference between the (k+1)th time difference and the kth time difference is less than a preset threshold, the measuring device It is determined that the kth time difference and the (k+1)th time difference are the target time differences.
  • Step 130b If the kth time difference and the (k+1)th time difference are in a preset range, and the absolute value of the difference between the (k+1)th time difference and the kth time difference is greater than or equal to a preset threshold, the measurement The device determines that the time difference between the kth time difference and the (k+1)th time difference is less than the average of the time difference is the target time difference, and the time difference average is the target time difference from the first time difference to the (k-1) time difference. average value.
  • the target time difference is used to calculate a heart rate value corresponding to the ECG signal.
  • the measuring device when determining whether the kth time difference and the (k+1)th time difference are target time differences, the measuring device first determines whether the kth time difference and the (k+1)th time difference are both in a preset range. That is, the measuring device determines which time differences calculated in step 120 are within a preset range.
  • the preset range here is 0.3s to 1.5s, and the measuring device deletes the kth time difference or the (k+1)th time difference that does not satisfy the preset range, if the kth time difference and the (k+1)th time difference If they are not within the preset range, the kth time difference and the (k+1)th time difference are deleted. It should be understood that the time difference of deletion is not the target time difference.
  • the values of the above-mentioned preset ranges may be set and adjusted according to actual needs. The above numerical values are merely illustrative and are not intended to limit the embodiments of the present invention.
  • the measuring device determines whether a difference between the kth time difference and the (k+1)th time difference is less than a preset threshold, where
  • the preset threshold may range from 0.1 s to 0.15 s.
  • the preset threshold may be 0.12 s.
  • the values of the above-mentioned preset thresholds may be set and adjusted according to actual needs. The above numerical values are merely illustrative and are not intended to limit the embodiments of the present invention.
  • the measuring device determines that the kth time difference and the (k+1)th time difference are the target time differences.
  • the measuring device determines that the k-th time difference and the (k+1)th time difference have a smaller average deviation time difference
  • a time difference is the target time difference.
  • the average time difference here is the average of all target time differences from the first time difference to the (k-1)th time difference, that is, the average of the time differences that have not been deleted before.
  • the measuring device calculates the heart rate based on the obtained target time difference. Specifically, the measuring device counts the target time difference within the preset duration, calculates an average of the target time differences according to the target time differences, and calculates the heart rate according to the average of the target time differences, wherein the heart rate value is 60/the average of the target time differences.
  • an ECG signal processing method is proposed in the embodiment of the present invention.
  • an effective QRS complex is extracted from the collected ECG signal, the accuracy of the ECG feature extraction is improved, and then the adjacent effective QRS complex is calculated.
  • the time difference between the peak points of the R waves in the middle further selects the target time difference that satisfies the condition according to the obtained time difference, thereby determining the heart rate value, greatly eliminating the interference introduced during the one-arm measurement process, and effectively ensuring the accuracy of the heart rate calculation. And the accuracy of heart rhythm analysis.
  • the measuring device may further perform the following operations:
  • the measuring device filters the ECG signal and uses a three-axis acceleration to fit the user's motion trajectory.
  • the measuring device uses a comb filter to filter the ECG signal.
  • the center point of the stop band can be 1 Hz, 50 Hz, 100 Hz, 150 Hz, etc.
  • the filtered waveform is as shown in FIG. 3 .
  • the measuring device uses a three-axis accelerometer to fit the motion trajectory
  • the three-axis fitting of x, y, and z is fitted to obtain a curve corresponding to the motion trajectory.
  • the measuring device of the embodiment of the present invention compares the filtered ECG signal with the motion trajectory, and deletes the ECG waveform in the filtered ECG signal corresponding to the motion amplitude value in the motion trajectory that is greater than the preset amplitude threshold. Eliminate the influence of motion artifacts on ECG signal acquisition and improve the effectiveness of the collected ECG signals.
  • the measuring device may further perform the following operations to determine the signal quality of the ECG signal.
  • the measuring device calculates a signal parameter corresponding to the ECG signal.
  • the signal parameters herein may be the following parameters but are not limited to the following parameters, including: effective signal power (denoted as PW_ECG), power frequency interference (denoted as PW_50), baseline drift (denoted as PW_1), and in-band noise (denoted as PW_NB) and so on.
  • effective signal power denoted as PW_ECG
  • power frequency interference denoted as PW_50
  • baseline drift denoted as PW_1
  • in-band noise denoted as PW_NB
  • the original signal power is recorded as ECG_original, PW_50 and PW_1 can be obtained by frequency domain transform of the original signal, and PW_ECG can be calculated by R wave amplitude value, QRS width, T wave amplitude value and T wave width.
  • PW_NB ECG_original–PW_50–PW_1–PW_ECG.
  • the measuring device then calculates a signal evaluation parameter based on the at least one signal parameter.
  • the signal evaluation parameters here may be a Signal Artifical Ratio (SAR) and a Signal Noise in Band Ratio (SNBR).
  • SAR Signal Artifical Ratio
  • SNBR Signal Noise in Band Ratio
  • the measuring device determines the signal quality level of the ECG signal according to the preset evaluation threshold corresponding to the signal evaluation parameter and the signal evaluation parameter.
  • the measuring device may notify the user of the signal quality level of the ECG signal, such as a voice prompt, or a dialog box prompting, which is not limited herein.
  • the measuring device determines the ECG signal.
  • the signal quality level is the first level.
  • the measuring device determines that the signal quality level of the ECG signal is the second level
  • the measuring device determines that the signal quality level of the ECG signal is the third level
  • the measuring device determines that the signal quality level of the ECG signal is the fourth level
  • the first level is better than the second level
  • the second level is better than the third level
  • the third level is better than the fourth level
  • Table 1 shows the signal quality level correspondence table. Specifically, as shown in Table 1, the signal quality is classified according to the threshold combination of the SAR and the SNBR, respectively.
  • the signal quality level (SQL) is grading from 1 to 4, where 1 is excellent, decreasing in turn, and 4 is not able to extract large noise features.
  • SQL signal quality level
  • the user can be prompted by the terminal when the signal quality is poor. , prompting the user to find the cause, such as wearing a wrong position, poor contact, and the like.
  • Signal level Signal quality assessment 1 SAR>TH_SAR&&SNBR>TH_SNBR 2 SAR ⁇ TH_SAR&&SNBR>TH_SNBR 3 SAR>TH_SAR&&SNBR ⁇ TH_SNBR 4 SAR ⁇ TH_SAR&&SNBR ⁇ TH_SNBR
  • the ECG signal processing method provided by the embodiment of the present invention is described below by taking a specific ECG measurement process as an example.
  • Step 1 The user wears a single-lead ECG acquisition device, turns on the switch, and the device enters the self-test phase to perform pre-judgment of the collected signal quality.
  • step 4 it is determined whether the number of target time differences continuously measured within one minute satisfies a preset condition. If the target time difference within 1 minute satisfies the preset condition, it indicates that the user is wearing the correct device and the device works normally, otherwise the user is prompted to correct the wearing position.
  • the position of the electrode is shifted.
  • the waveform at this time is as shown in Fig. 4(a).
  • the electrode position is normal.
  • the waveform at this time is as shown in Fig. 4(b). .
  • Step 2 After normal operation, the device performs filtering and artifact processing on the acquired ECG signal.
  • the comb filter is used to filter the collected ECG signal, and the motion trajectory is fitted according to the three-axis accelerometer (take x, y, and z three-axis fitting) to determine that the motion trajectory corresponding curve is greater than the amplitude threshold.
  • the ECG waveform in the corresponding filtered ECG signal in the duration is deleted to delete the corresponding ECG waveform to enhance the accuracy of the ECG signal.
  • Step 3 ECG effective feature extraction, mainly the effective QRS complex and the extraction of the target time difference.
  • the QRS joint detection method is used to first detect the R wave, and then determine the Q point and the S point according to the extreme points before and after the R wave, and compare the corresponding threshold values according to the QR, RS, and QS spacing, for example, when When QR ⁇ 100ms, and RS ⁇ 100ms, and QS ⁇ 150ms, the QRS complex is confirmed to be a valid QRS complex, otherwise it is an invalid QRS complex.
  • the values of the above QR, RS, and QS can be set and adjusted according to actual needs. The above numerical values are merely illustrative and are not intended to limit the embodiments of the present invention.
  • the waveform marked by the ellipse is also a local peak point, but does not satisfy QR ⁇ 100ms, and RS ⁇ 100ms, and QS ⁇ 150ms. Therefore, the waveform marked by the ellipse is an invalid QRS group and will not be misjudged. For effective QRS complexes.
  • calculating a time difference between peak points R of two R waves in each two consecutive effective QRS groups that is, an RR interval
  • the RR interval falls within 0.3 s to 1.5 s, the condition is satisfied, and it is determined whether the condition is satisfied. The next condition, otherwise the RR interval is excluded.
  • it is determined whether the difference between adjacent RR intervals is less than 0.12 s, and if so, the two RR intervals are reserved, that is, the two RR intervals are target time differences, otherwise, the deviation from the RR average is larger.
  • the RR average is the average of the previously retained target time differences.
  • the values of the RR interval and the adjacent RR interval difference can be set and adjusted according to actual needs. The above numerical values are merely illustrative and are not intended to limit the embodiments of the present invention.
  • the average time difference of the selected targets is obtained as an average value of the RR, for example, by the above process, the target time difference within one minute is 30, and then the average of the 30 target time differences is calculated, and then averaged according to the 30 target time differences.
  • the above method is used to remove the waveform that may affect the measurement result to improve the accuracy of ECG feature extraction, and effectively ensure the effectiveness of the signal measurement of the single-arm ECG device.
  • Step 4 the signal quality of the ECG signal is evaluated in real time.
  • the signal parameters including the effective signal power (PW_ECG), power frequency interference (PW_50), baseline drift (PW_1), in-band noise (PW_NB), etc.
  • SAR lg (PW_ECG / PW_1)
  • the values of the above-mentioned TH_SAR and TH_SNBR can be set and adjusted according to actual needs. The above numerical values are merely illustrative and are not intended to limit the embodiments of the present invention.
  • Step1 can determine the signal quality level of the current ECG signal according to the result obtained by Step 4. If the current signal quality level is 4, the user can be prompted to find the cause and re-measure.
  • the signal quality level obtained in Step4 can be used as a criterion for predicting the quality of the collected signal in Step1.
  • the user can correct the wearing position when determining the current signal quality level is poor, and ensure the collected ECG signal.
  • the effectiveness of the signal measurement accuracy of the single-arm ECG measuring device is effectively guaranteed.
  • Embodiments of the present invention provide a wearable device, including: a processor, a memory, a heart rate collector, and a power source.
  • the wearable device herein may be a sports arm band, a heart rate belt or a heart rate sticker, and when the wearable device is a heart rate sticker, the heart rate sticker can communicate with other terminals (eg, a mobile phone) through the Bluetooth module.
  • the components of the wearable device 600 are specifically described below with reference to FIG. 6:
  • the heart rate collector 610 is configured to collect an ECG signal
  • the memory 620 is configured to store an instruction
  • the processor 630 is configured to invoke an instruction in the memory to perform the ECG signal processing process.
  • the power source 640 is configured to supply power to the wearable device.
  • the wearable device further includes: a motion sensor 650;
  • the motion sensor 650 is configured to detect the magnitude of the acceleration in each direction and fit the motion trajectory.
  • the wearable device further includes a display unit 660, a Bluetooth module 670, and the like.
  • the wearable device provided by the embodiment of the present invention is used to perform the method embodiment corresponding to the foregoing FIG. 1 . Therefore, the implementation manner of the wearable device provided by the embodiment of the present invention may be referred to the implementation manner of the method, and details are not described herein again.
  • the method provided by the embodiment of the invention combines the law of motion physiology to improve the accuracy of ECG feature extraction, and effectively guarantees the signal measurement accuracy of the single-arm ECG measuring device.
  • an ECG signal processing apparatus is also provided in the embodiment of the present invention, and the apparatus may be used to perform the method embodiment corresponding to the foregoing FIG. 1. Therefore, the implementation manner of the ECG signal processing apparatus provided by the embodiment of the present invention may be See the implementation of the method, and the repeated description will not be repeated.
  • an embodiment of the present invention provides an ECG signal processing apparatus, including: an acquisition unit 710, an extraction unit 720, a calculation unit 730, and a processing unit 740, where
  • the collecting unit 710 is configured to collect an ECG signal
  • the extracting unit 720 is configured to extract a kth effective QRS wave group of the ECG signal, where the QRS wave group includes a first extreme point Q before the peak point R of the i-th R wave, and a peak of the i-th R wave a second extreme point S after the peak point R of the point R and the i-th R wave, wherein i ⁇ 2, k ⁇ 2, k ⁇ i;
  • the calculating unit 730 is configured to calculate a kth time difference and a (k+1)th time difference, wherein the kth time difference is a peak point R of the R wave in the kth valid QRS group and a (k) +1) the time difference of the peak point R of the R wave in the effective QRS complex, the (k+1)th time difference being the peak point R of the R wave in the (k+1)th effective QRS complex Time difference from the peak point R of the R wave in the (k+2)th effective QRS complex;
  • the processing unit 740 is configured to: if the kth time difference and the (k+1)th time difference are in a preset range, and the difference between the (k+1)th time difference and the kth time difference When the absolute value is less than the preset threshold, determining that the kth time difference and the (k+1)th time difference are target time differences; or, if the kth time difference and the (k+1)th Determining the kth time difference and the (k) when a time difference is in a preset range, and an absolute value of a difference between the (k+1)th time difference and the kth time difference is greater than or equal to a preset threshold a time difference in which the average value of the deviation time difference is less than +1) time difference is a target time difference, and the average value of the time difference is an average value of all target time differences in the first time difference to the (k-1) time difference;
  • the target time difference is used to calculate a heart rate value corresponding to the ECG signal.
  • the extracting unit 720 is configured to: when extracting the kth valid QRS group of the ECG signal, determine a first extreme point corresponding to the ith R wave Q and Second extreme point S;
  • the first time difference, the second time difference, and the third time difference are respectively less than the corresponding first threshold, the second threshold, and the third threshold, the first extreme point Q corresponds to the Q wave, and the second extreme value Point S corresponds to an S wave, and the i-th R wave and the corresponding Q wave and S wave constitute a k-th effective QRS wave group.
  • the device further includes:
  • a signal quality evaluation unit 750 configured to calculate a signal parameter corresponding to the ECG signal
  • the signal parameters include effective signal power, baseline drift, and in-band noise
  • the signal evaluation parameter includes a signal artifact ratio, and a signal in-band noise ratio, wherein the signal artifact ratio is a function of the effective signal power and the baseline drift, the signal to-band noise ratio being a function of effective signal power and said in-band noise;
  • the signal quality evaluation unit 750 is configured to: determine, according to the preset evaluation threshold corresponding to the signal evaluation parameter, the signal quality level of the ECG signal, determine that the signal artifact ratio is greater than corresponding Determining a threshold value, and determining that a signal quality level of the ECG signal is a first level when the signal to-band noise ratio is greater than a corresponding preset evaluation threshold;
  • first level is better than the second level
  • second level is better than the third level
  • third level is better than the fourth level
  • the apparatus further includes: a motion trajectory analyzing unit 760, configured to perform filtering processing on the ECG signal before extracting the kth effective QRS wave group of the ECG signal, and adopt A three-axis accelerometer fits the user's motion trajectory;
  • the filtered ECG signal is compared with the motion trajectory, and the ECG waveform in the filtered ECG signal corresponding to the duration of the motion amplitude value greater than the preset amplitude threshold is deleted.
  • FIG. 1 These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine for the execution of instructions for execution by a processor of a computer or other programmable data processing device.

Abstract

一种ECG信号处理方法及装置(700)，用以解决单导联心电采集的单臂测量过程中引入较大的干扰，严重影响了心率的精确计算和心律的精准分析的问题。该方法包括：测量设备采集ECG信号(100)；提取ECG信号的第k个有效QRS波群(110)；计算第k个时间差和第(k+1)个时间差(120)；判断第k个时间差与第(k+1)个时间差是否为目标时间差(130a、130b)。因此，该方法提高了心电特征提取的准确率，极大地消除了单臂测量过程中引入的干扰，能够有效保证心率计算精确度和心律分析的精准度。

Description

一种ECG信号处理方法及装置
本申请要求于2016年11月3日提交中国专利局、申请号为201610974448.2、发明名称为“一种单臂ECG的测量方法和终端”的CN专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明涉及终端领域，尤其涉及一种ECG信号处理方法及装置。
背景技术
针对传统的心电图(Electro Cardio Graph，ECG)测量需要跨心区测量，应用场景受限、造成用户体验较差。
现有技术中，提出多种便携式单导联心电采集测量方案。具体的，单导联心电采集设备多采用模拟肢体I导联(双手)，或者模拟胸导联(胸区，跨心脏)的测量方式，这些测量方式接近于标准导联体系获取的心电信号，目前在便携式心电分析服务类的产品中得到广泛应用。但是，在单导联心电采集的单臂测量过程中，可能会引入较大的干扰，其中肌电干扰、运动伪迹等较为显著，严重影响了心率的精确计算和心律的精准分析。
发明内容
本发明实施例提供一种ECG信号处理方法及装置，用以解决单导联心电采集的单臂测量过程中，引入较大的干扰，严重影响了心率的精确计算和心律的精准分析的问题。
第一方面，一种心电图ECG信号处理方法，包括：
测量设备采集ECG信号，提取ECG信号的第k个有效QRS波群，其中QRS波群包括第i个R波的峰值点R前的第一极值点Q、第i个R波的峰值点R、和第i个R波的峰值点R后的第二极值点S，其中，i≥2，k≥2，k≤i，进一步计算第k个时间差和第(k+1)个时间差，其中，第k个时间差为第k个有效QRS波群中R波的峰值点R与第(k+1)个有效QRS波群中R波的 峰值点R的时间差，第(k+1)个时间差为第(k+1)个有效QRS波群中的R波的峰值点R与第(k+2)个有效QRS波群中的R波的峰值点R的时间差。如果第k个时间差与第(k+1)个时间差处于预设范围，且第(k+1)个时间差与第k个时间差的差值的绝对值小于预设阈值时，测量设备确定第k个时间差和第(k+1)个时间差为目标时间差；或者，如果第k个时间差与第(k+1)个时间差处于预设范围，且第(k+1)个时间差与第k个时间差的差值的绝对值大于等于预设阈值时，测量设备确定第k个时间差和第(k+1)个时间差中偏离时间差平均值较少的一个时间差为目标时间差，时间差平均值为第1个时间差至第(k-1)个时间差中所有目标时间差的平均值。其中，目标时间差用于计算ECG信号对应的心率值。
因此，本发明实施例中提出一种ECG信号处理方法，首先从采集的ECG信号中提取有效QRS波群，提高了心电特征提取的准确率，然后，计算相邻有效QRS波群中的R波的峰值点之间的时间差，进一步根据获得的时间差筛选出满足条件的目标时间差，从而确定心率值，极大地消除了单臂测量过程中引入的干扰，能够有效保证心率计算精确度和心律分析的精准度。
在一种可能的实现方式中，所述提取所述ECG信号的第k个有效QRS波群，包括：测量设备确定第i个R波对应的第一极值点Q和第二极值点S，计算第一极值点Q与第i个R波的峰值点R之间的时间差为第一时间差，第i个R波的峰值点R与第二极值点S之间的时间差为第二时间差，第一极值点Q与第二极值点S之间的时间差为第三时间差。如果第一时间差、第二时间差、第三时间差分别小于对应的第一阈值、第二阈值、第三阈值时，则第一极值点对应Q波，第二极值点对应S波，测量设备确定第i个R波与对应的Q波和S波构成第k个有效QRS波群。
因此，采用本发明实施例提供的方法从采集的ECG信号中提取有效QRS波群，提高了心电特征提取的准确率，进而有效保证心率计算精确度和心律分析的精准度。
在一种可能的实现方式中，还包括：
测量设备计算ECG信号对应的信号参数，根据至少一个信号参数计算信 号评估参数，并根据信号评估参数与信号评估参数对应的预设评估阈值，确定ECG信号的信号质量等级。
因此，采用本发明实施例提供的方法，测量设备能够评估不同的信号质量等级，通过终端对用户进行提示，当信号质量较差时，提示用户查找原因，例如佩戴位置错误、接触不良等。
在一种可能的实现方式中，信号参数包括有效信号功率，基线漂移，和带内噪声；信号评估参数包括信号伪迹比、和信号带内噪声比，其中，信号伪迹比为有效信号功率和基线漂移的函数，信号带内噪声比为有效信号功率和带内噪声的函数；
测量设备根据信号评估参数与信号评估参数对应的预设评估阈值，确定ECG信号的信号质量等级，包括：
测量设备确定信号伪迹比大于对应的预设评估阈值，且信号带内噪声比大于对应的预设评估阈值时，确定ECG信号的信号质量等级为第一等级；
测量设备确定信号伪迹比小于等于对应的预设评估阈值，且信号带内噪声比大于对应的预设评估阈值时，确定ECG信号的信号质量等级为第二等级；
测量设备确定信号伪迹比大于对应的预设评估阈值，且信号带内噪声比小于等于对应的预设评估阈值时，确定ECG信号的信号质量等级为第三等级；
测量设备确定信号伪迹比小于等于对应的预设评估阈值，且信号带内噪声比小于等于对应的预设评估阈值时，确定ECG信号的信号质量等级为第四等级；
其中，第一等级优于第二等级，第二等级优于第三等级，第三等级优于第四等级。
因此，采用本发明实施例提供的方法获得的信号质量等级可用于对采集信号的质量进行预判，通过将信号质量等级反馈给用户，使用户在确定当前信号质量等级较差时纠正佩戴位置，保证采集到的ECG信号的有效性，进而有效保障单臂心电测量设备的信号测量准确性。
在一种可能的实现方式中，在提取ECG信号的第k个有效QRS波群之前，还包括：测量设备对ECG信号进行滤波处理，并采用三轴加速计拟合用 户的运动轨迹，将滤波后的ECG信号与运动轨迹进行比对，将运动轨迹中运动幅度值大于预设幅度阈值的时长对应的滤波后的ECG信号中的ECG波形删除。
因此，本发明实施例的测量设备通过将滤波后的ECG信号与运动轨迹进行比对，将运动轨迹中运动幅度值大于预设幅度阈值的时长内对应的滤波后的ECG信号中的ECG波形删除，从而消除运动伪迹对ECG信号采集的影响，提高采集到的ECG信号的有效性。
第二方面，一种可穿戴设备，包括：处理器、存储器、心率采集器，电源；其中，心率采集器，用于采集ECG信号；存储器，用于存储指令；处理器，用于调用存储器中的指令，执行第一方面或第一方面中任意一种可能的实现方式。
因此，本发明实施例中提出的可穿戴设备，首先从采集的ECG信号中提取有效QRS波群，提高了心电特征提取的准确率，然后，计算相邻有效QRS波群中的R波的峰值点之间的时间差，进一步根据获得的时间差筛选出满足条件的目标时间差，从而确定心率值，极大地消除了单臂测量过程中引入的干扰，能够有效保证心率计算精确度和心律分析的精准度。
在一种可能的实现方式中，还包括：加速计传感器；
加速传感器，用于检测各个方向上的加速度的大小，拟合运动轨迹。
因此，通过加速传感器拟合运动轨迹，将滤波后的ECG信号与运动轨迹进行比对，将运动轨迹中运动幅度值大于预设幅度阈值的时长内对应的滤波后的ECG信号中的ECG波形删除，从而消除运动伪迹对ECG信号采集的影响，提高采集到的ECG信号的有效性。
第三方面，本申请提供了一种ECG信号处理装置，用于执行上述第一方面或第一方面的任意可能的实现方式中的方法。具体地，该装置包括用于执行上述第一方面或第一方面的任意可能的实现方式中的方法的单元。
附图说明
图1为本发明实施例中的ECG信号处理方法的概述流程图；
图2为本发明实施例中标准ECG信号的波形特征示意图；
图3为本发明实施例中ECG信号滤波后的波形图；
图4(a)为本发明实施例中用户佩戴设备有误时电极位置偏移的示意图；
图4(b)为本发明实施例中用户佩戴设备无误时电极位置正常的示意图；
图5为本发明实施例中无效QRS波群的示意图；
图6为本发明实施例中可穿戴设备的结构示意图；
图7为本发明实施例中ECG信号处理装置的结构示意图。
具体实施方式
下面结合附图，对本发明的实施例进行描述。
参阅图1所示，针对单导联心电采集的单臂测量过程中，引入较大的干扰，严重影响了心率的精确计算和心律的精准分析的问题，本发明实施例提供一种ECG信号处理方法，该方法包括：
步骤100：测量设备采集ECG信号。
本发明实施例中所指的测量设备为单导联心电采集设备。例如，可穿戴设备等。
测量设备采集ECG信号，例如可以为：用户佩戴单导联心电采集设备，打开开关，设备进入自检阶段，设备自检通过表明用户佩戴无误，设备工作正常，否则提示用户纠正佩戴位置，在设备进入正常工作状态后，开始采集用户的ECG信号。
步骤110：测量设备提取ECG信号的第k个有效QRS波群，其中QRS波群包括第i个R波峰值点R前的第一极值点Q、第i个R波的峰值点R、和第i个R波峰值点R后的第二极值点S，其中，i≥2，k≥2，k≤i。
针对ECG信号中的每个R波，测量设备判断当前R波的峰值点R与左右两个极值点能否构成一个有效的QRS波群，具体的，可以采用但不限于以下方法确定有效的QRS波群：
图2为标准ECG信号的波形特征示意图。如图2所示，测量设备可以根据标准ECG信号的波形特征确定第i个R波峰值点R对应的第一极值点Q和第二极值点S，其中，第一极值点为第i个R波峰值点R前的第一个极值点Q，第二极值点S为第i个R波峰值点R后的第一个极值点Q，即R波峰值点R左右两侧临近的两个极值点。
进一步地，测量设备计算第一极值点Q与第i个R波的峰值点R之间的时间差，将该时间差记为第一时间差QS，计算第i个R波的峰值点R与第二极值点S之间的时间差，将该时间差记为第二时间差RS，计算第一极值点Q与第二极值点S之间的时间差，将该时间差记为第三时间差QS。
测量设备确定第一时间差、第二时间差、第三时间差分别小于对应的第一阈值、第二阈值、第三阈值时，确定第一极值点Q对应Q波，第二极值点S对应S波，进而确定第i个R波与对应的Q波和S波构成第k个有效QRS波群。
具体的，这里的第一阈值、第二阈值、第三阈值可根据经验值设定，只要符合人体生理特征即可，不作为对本发明实施例的限定。本发明实施例中，第一阈值的范围为90～110ms，例如第一阈值可以为100ms。第二阈值的范围为90～110ms，例如第二阈值可以为100ms。第三阈值的范围为140～160ms，例如第三阈值可以为150ms，则有效QRS波群的判断条件可以为QR＜100ms，且RS＜100ms，且QS＜150ms。
当三个时间差中任一时间差大于等于对应的阈值时，该QRS波群为无效的QRS波群，当三个时间差分别小于对应的阈值时，该QRS波群为有效QRS波群。
应理解的是，由于可能存在无效的QRS波群，因此，k≤i。
步骤120：测量设备计算第k个时间差和第(k+1)个时间差。
其中，第k个时间差为第k个有效QRS波群中R波的峰值点R与第(k+1)个有效QRS波群中R波的峰值点R的时间差，第(k+1)个时间差为第(k+1)个有效QRS波群中的R波的峰值点R与第(k+2)个有效QRS波群中的R波的峰值点R的时间差。
可选地，第k个有效QRS波群、第(k+1)个有效QRS波群、第(k+2)个有效QRS波群为三个连续的波群。
在确定各个有效QRS波群之后，测量设备计算所有相邻有效QRS波群中两个R波的峰值点R的时间差。
步骤130a：如果第k个时间差与第(k+1)个时间差处于预设范围，且第(k+1)个时间差与第k个时间差的差值的绝对值小于预设阈值时，测量设备确定将第k个时间差和第(k+1)个时间差为目标时间差。
步骤130b：如果第k个时间差与第(k+1)个时间差处于预设范围，且第(k+1)个时间差与第k个时间差的差值的绝对值大于等于预设阈值时，测量设备确定第k个时间差和第(k+1)个时间差中偏离时间差平均值较少的一个时间差为目标时间差，时间差平均值为第1个时间差至第(k-1)个时间差中所有目标时间差的平均值。
其中，目标时间差用于计算ECG信号对应的心率值。
本发明实施例中在确定第k个时间差和第(k+1)个时间差是否为目标时间差时，测量设备首先判断第k个时间差和第(k+1)个时间差是否均处于预设范围，即测量设备判断在步骤120中计算出的哪些时间差处于预设范围。这里的预设范围为0.3s～1.5s，测量设备将不满足预设范围的第k个时间差或第(k+1)个时间差删除，如果第k个时间差和第(k+1)个时间差均不处于预设范围内，则将第k个时间差和第(k+1)个时间差均删除。应理解的是，删除的时间差不为目标时间差。对于上述预设范围的数值可以根据实际需要进行设定和调整，上述数值仅为举例说明，不作为对本发明实施例的限定。
在确定第k个时间差与第(k+1)个时间差处于预设范围时，测量设备进一步判断第k个时间差与第(k+1)个时间差的差值是否小于预设阈值，此处的预设阈值的范围可以为0.1s～0.15s，例如，预设阈值可以为0.12s。对于上述预设阈值的数值可以根据实际需要进行设定和调整，上述数值仅为举例说明，不作为对本发明实施例的限定。
如果第(k+1)个时间差与第k个时间差的差值小于预设阈值时，测量设备确定第k个时间差和第(k+1)个时间差为目标时间差。
如果第(k+1)个时间差与第k个时间差的差值的绝对值大于等于预设阈值时，测量设备确定第k个时间差和第(k+1)个时间差中偏离时间差平均值较少的一个时间差为目标时间差。这里的时间差平均值为第1个时间差至第(k-1)个时间差中所有目标时间差的平均值，即之前未被删除的时间差的平均值。
进一步地，测量设备根据获得的目标时间差计算心率。具体的，测量设备统计预设时长内的目标时间差，根据这些目标时间差计算目标时间差的平均值，并根据目标时间差的平均值计算心率，其中，心率值＝60/目标时间差的平均值。
综上所述，本发明实施例中提出一种ECG信号处理方法，首先从采集的ECG信号中提取有效QRS波群，提高了心电特征提取的准确率，然后，计算相邻有效QRS波群中的R波的峰值点之间的时间差，进一步根据获得的时间差筛选出满足条件的目标时间差，从而确定心率值，极大地消除了单臂测量过程中引入的干扰，能够有效保证心率计算精确度和心律分析的精准度。
进一步的，本发明实施例在执行步骤100之后，执行步骤110之前，测量设备还可以执行如下操作：
测量设备对ECG信号进行滤波处理，并采用三轴加速记拟合用户的运动轨迹。
例如，测量设备采用梳状滤波器对ECG信号进行滤波处理，具体的，阻带中心点可以为1Hz，50Hz，100Hz，150Hz等，滤波后的波形如图3所示。
测量设备采用三轴加速度计拟合运动轨迹时，取x、y、z三轴拟合进行拟合获得运动轨迹对应的曲线。
本发明实施例的测量设备通过将滤波后的ECG信号与运动轨迹进行比对，将运动轨迹中运动幅度值大于预设幅度阈值的时长内对应的滤波后的ECG信号中的ECG波形删除，从而消除运动伪迹对ECG信号采集的影响，提高采集到的ECG信号的有效性。
进一步的，在步骤130a或步骤130b之后，测量设备还可继续执行如下操作，以判断ECG信号的信号质量。
首先，测量设备计算ECG信号对应的信号参数。
例如，这里的信号参数可以为以下参数但不限于以下参数，包括：有效信号功率(记为PW_ECG)，工频干扰(记为PW_50)，基线漂移(记为PW_1)，带内噪声(记为PW_NB)等。
原始信号功率记为ECG_original，PW_50及PW_1可由原始信号经过频域变换获得，PW_ECG可以通过R波幅度值、QRS宽度、T波幅度值和T波宽度计算获得。
PW_NB＝ECG_original–PW_50–PW_1–PW_ECG。
上述信号参数可通过现有技术中提供的方法计算获得。
然后，测量设备根据至少一个信号参数计算信号评估参数。
这里的信号评估参数可以为信号伪迹比(Signal Artifical Ratio，SAR)和信号带内噪声比(Signal Noise in Band Ratio，SNBR)。
其中，SAR＝lg(PW_ECG/PW_1)，SNBR＝lg(PW_ECG/PW_NB)。
最后，测量设备根据信号评估参数与信号评估参数对应的预设评估阈值，确定ECG信号的信号质量等级。
进一步的，测量设备可以将ECG信号的信号质量等级通知给用户，例如语音提示，或弹出对话框提示等方式，在此不作限定。
具体的，当信号评估参数为SAR和SNBR时，如果SAR大于对应的预设评估阈值(记为TH_SAR)，且SNBR大于对应的预设评估阈值(记为TH_SNBR)时，测量设备确定ECG信号的信号质量等级为第一等级。
如果SAR小于等于TH_SAR，且SNBR大于TH_SNBR时，测量设备确定ECG信号的信号质量等级为第二等级；
如果SAR大于TH_SAR，且SNBR小于等于TH_SNBR时，测量设备确定ECG信号的信号质量等级为第三等级；
如果SAR小于等于TH_SAR，且SNBR小于等于TH_SNBR时，测量设备确定ECG信号的信号质量等级为第四等级；
其中，第一等级优于第二等级，第二等级优于第三等级，第三等级优于第四等级。
表1为信号质量等级对应表，具体如表1所示，分别对SAR和SNBR按照阈值组合对信号质量进行分级。信号质量等级(SQL)分级为1～4，其中，1为优，依次递减，4为噪声大特征无法提取，对于不同的信号质量等级，可以通过终端对用户进行提示，当信号质量较差时，提示用户查找原因，例如佩戴位置错误、接触不良等。
表1
信号等级 信号质量评估
1 SAR>TH_SAR&&SNBR>TH_SNBR
2 SAR<TH_SAR&&SNBR>TH_SNBR
3 SAR>TH_SAR&&SNBR<TH_SNBR
4 SAR<TH_SAR&&SNBR<TH_SNBR
下面以一个具体的心电测量流程为例说明本发明实施例提供的ECG信号处理方法。
步骤(Step)1，用户佩戴单导联心电采集设备，打开开关，设备进入自检阶段，进行采集信号质量预判。
具体的，设备执行一遍完整的step1～step4后，判断1分钟内连续测量的目标时间差数量是否满足预设条件。若1分钟内目标时间差数量满足预设条件，则表明用户佩戴无误，设备正常工作，否则提示用户纠正佩戴位置。
例如，当用户佩戴有误时，电极位置出现偏移，此时的波形如图4(a)所示，当用户佩戴无误时，电极位置正常，此时的波形如图4(b)所示。
Step 2，正常工作后，设备将获取到的ECG信号进行滤波和伪迹处理。
具体的，采用梳状滤波器对采集到的ECG信号进行滤波，并根据三轴加速度计拟合运动轨迹(取x、y、z三轴拟合)，判断运动轨迹对应曲线中大于幅度阈值的时长内对应的滤波后的ECG信号中的ECG波形，删除对应的ECG波形，以增强ECG信号的准确性。
Step 3，ECG有效特征提取，主要是有效QRS波群以及目标时间差的提取。
具体的，采用QRS联合检测的方式，首先检测出R波后，依次按照R波前后的极值点确定Q点和S点，根据QR、RS以及QS间距对对应的阈值进行比较，例如，当QR<100ms,且RS<100ms,且QS<150ms时，该QRS波群被确认为是有效QRS波群，否则为无效QRS波群。对于上述QR、RS、QS的数值可以根据实际需要进行设定和调整，上述数值仅为举例说明，不作为对本发明实施例的限定。
如图5所示，椭圆标出来的波形也是局部峰值点，但是不满足QR<100ms,且RS<100ms,且QS<150ms，因此椭圆标出来的波形为无效QRS波群，不会被误判为有效QRS波群。
进一步地，计算每两个连续的有效QRS波群中两个R波的峰值点R之间的时间差，即RR间隔，如果RR间隔落入0.3s～1.5s，则满足条件，继续判断是否满足下一个条件，否则排除该RR间隔。进一步地，在满足前述条件后，判断相邻RR间隔差是否小于0.12s，若是则保留这两个RR间隔，即这两个RR间隔均为目标时间差，否则，排除偏离RR平均值较大的一个，保留另一个RR间隔作为目标时间差。特别地，RR平均值为之前保留的目标时间差的平均值。对于上述RR间隔、相邻RR间隔差的数值可以根据实际需要进行设定和调整，上述数值仅为举例说明，不作为对本发明实施例的限定。
进一步地，将筛选出的所有目标时间差求RR平均值，例如通过上述过程统计得到一分钟内的目标时间差为30个，然后计算这30个目标时间差的平均值，然后根据30个目标时间差的平均值计算心率，其中，心率＝60/30个目标时间差的平均值。
因此，采用上述方法去掉可能影响测量结果的波形以提高心电特征提取的准确率，有效保障单臂心电测量设备信号测量的有效性。
Step 4，ECG信号的信号质量实时评估。
首先计算信号参数，包括有效信号功率(PW_ECG)，工频干扰(PW_50)、基线漂移(PW_1)、带内噪声(PW_NB)等，进一步分别求取信号评估参数，SAR＝lg(PW_ECG/PW_1)，以及SNBR＝lg(PW_ECG/PW_NB)，假设 TH_SAR＝0dB,TH_SNBR＝10dB，进一步根据表1确定当前ECG信号的信号质量等级，以提示用户采集到的ECG信号的有效性。对于上述TH_SAR、TH_SNBR的数值可以根据实际需要进行设定和调整，上述数值仅为举例说明，不作为对本发明实施例的限定。
例如，Step1可根据Step4得到的结果确定当前ECG信号的信号质量等级，若当前信号质量等级为4，可提示用户查找原因，重新测量。
Step4获得的信号质量等级可作为对Step1中采集信号质量进行预判的标准，通过将信号质量等级反馈给用户，使用户在确定当前信号质量等级较差时纠正佩戴位置，保证采集到的ECG信号的有效性，进而有效保障单臂心电测量设备的信号测量准确性。
本发明实施例提供一种可穿戴设备，包括：处理器、存储器、心率采集器，电源。例如，这里的可穿戴设备可以为运动臂带、心率带或心率贴，在可穿戴设备为心率贴时，心率贴可通过蓝牙模块与其他终端(例如，手机)进行通信。
下面结合图6对可穿戴设备600的各个构成部件进行具体的介绍：
所述心率采集器610，用于采集ECG信号；
所述存储器620，用于存储指令；
所述处理器630，用于调用所述存储器中的指令，执行上述ECG信号处理过程；
所述电源640，用于为所述可穿戴设备供电。
在一种可能的设计中，所述可穿戴设备还包括：运动传感器650；
所述运动传感器650，用于检测各个方向上的加速度的大小，拟合运动轨迹。
在一种可能的设计中，所述可穿戴设备还包括显示单元660，蓝牙模块670等。
采用本发明实施例提供的可穿戴设备用于执行上述图1对应的方法实施例，因此本发明实施例提供的可穿戴设备的实施方式可以参见该方法的实施方式，重复之处不再赘述。
综上所述，采用本发明实施例提供的方法，结合运动生理变化规律，提高心电特征提取的准确率，有效保障单臂心电测量设备的信号测量准确性。
基于同一发明构思，本发明实施例中还提供了一种ECG信号处理装置，该装置可以用于执行上述图1对应的方法实施例，因此本发明实施例提供的ECG信号处理装置的实施方式可以参见该方法的实施方式，重复之处不再赘述。
参阅图7所示，本发明实施例提供一种ECG信号处理装置，包括：采集单元710，提取单元720，计算单元730，处理单元740，其中，
采集单元710，用于采集ECG信号；
提取单元720，用于提取所述ECG信号的第k个有效QRS波群，其中QRS波群包括第i个R波的峰值点R前的第一极值点Q、第i个R波的峰值点R、和第i个R波的峰值点R后的第二极值点S，其中，i≥2，k≥2，k≤i；
计算单元730，用于计算第k个时间差和第(k+1)个时间差，其中，所述第k个时间差为所述第k个有效QRS波群中R波的峰值点R与第(k+1)个有效QRS波群中R波的峰值点R的时间差，所述第(k+1)个时间差为所述第(k+1)个有效QRS波群中的R波的峰值点R与第(k+2)个有效QRS波群中的R波的峰值点R的时间差；
处理单元740，用于如果所述第k个时间差与所述第(k+1)个时间差处于预设范围，且所述第(k+1)个时间差与所述第k个时间差的差值的绝对值小于预设阈值时，确定所述第k个时间差和所述第(k+1)个时间差为目标时间差；或者，如果所述第k个时间差与所述第(k+1)个时间差处于预设范围，且所述第(k+1)个时间差与所述第k个时间差的差值的绝对值大于等于预设阈值时，确定所述第k个时间差和所述第(k+1)个时间差中偏离时间差平均值较少的一个时间差为目标时间差，所述时间差平均值为第1个时间差至第(k-1)个时间差中所有目标时间差的平均值；
其中，所述目标时间差用于计算所述ECG信号对应的心率值。
在一种可能的实现方式中，所述提取单元720，用于：所述提取所述ECG信号的第k个有效QRS波群时，确定所述第i个R波对应的第一极值点Q和 第二极值点S；
计算所述第一极值点Q与所述第i个R波的峰值点R之间的时间差为第一时间差，所述第i个R波的峰值点R与所述第二极值点S之间的时间差为第二时间差，所述第一极值点Q与所述第二极值点S之间的时间差为第三时间差；
如果所述第一时间差、第二时间差、第三时间差分别小于对应的第一阈值、第二阈值、第三阈值时，则所述第一极值点Q对应Q波，所述第二极值点S对应S波，所述第i个R波与对应的Q波和S波构成第k个有效QRS波群。
在一种可能的实现方式中，所述装置，还包括：
信号质量评估单元750，用于计算所述ECG信号对应的信号参数；
根据至少一个所述信号参数计算信号评估参数；
根据所述信号评估参数与所述信号评估参数对应的预设评估阈值，确定所述ECG信号的信号质量等级。
在一种可能的实现方式中，所述信号参数包括有效信号功率，基线漂移，和带内噪声；
所述信号评估参数包括信号伪迹比、和信号带内噪声比，其中，所述信号伪迹比为所述有效信号功率和所述基线漂移的函数，所述信号带内噪声比为所述有效信号功率和所述带内噪声的函数；
所述信号质量评估单元750，用于：根据所述信号评估参数与所述信号评估参数对应的预设评估阈值，确定所述ECG信号的信号质量等级时，确定所述信号伪迹比大于对应的预设评估阈值，且所述信号带内噪声比大于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第一等级；
确定所述信号伪迹比小于等于对应的预设评估阈值，且所述信号带内噪声比大于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第二等级；
确定所述信号伪迹比大于对应的预设评估阈值，且所述信号带内噪声比小于等于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第三 等级；
确定所述信号伪迹比小于等于对应的预设评估阈值，且所述信号带内噪声比小于等于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第四等级；
其中，所述第一等级优于所述第二等级，所述第二等级优于所述第三等级，所述第三等级优于所述第四等级。
在一种可能的实现方式中，所述装置还包括：运动轨迹分析单元760，用于在提取所述ECG信号的第k个有效QRS波群之前，对所述ECG信号进行滤波处理，并采用三轴加速计拟合用户的运动轨迹；
将滤波后的ECG信号与所述运动轨迹进行比对，将所述运动轨迹中运动幅度值大于预设幅度阈值的时长对应的所述滤波后的ECG信号中的ECG波形删除。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分步骤是可以通过程序来指令处理器完成，所述的程序可以存储于计算机可读存储介质中，所述存储介质是非短暂性(英文：non-transitory)介质，例如随机存取存储器，只读存储器，快闪存储器，硬盘，固态硬盘，磁带(英文：magnetic tape)，软盘(英文：floppy disk)，光盘(英文：optical disc)及其任意组合。
本发明是参照本发明实施例的方法和设备各自的流程图和方框图来描述的。应理解可由计算机程序指令实现流程图和方框图中的每一流程和方框、以及流程图和方框图中的流程和方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和方框图一个方框或多个方框中指定的功能的装置。
以上所述，仅为本发明较佳的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应该以权利要求的保护范围为准。

Claims (12)

  1. 一种心电图ECG信号处理方法，其特征在于，包括：
    测量设备采集ECG信号；
    提取所述ECG信号的第k个有效QRS波群，其中QRS波群包括第i个R波的峰值点R前的第一极值点Q、第i个R波的峰值点R、和第i个R波的峰值点R后的第二极值点S，其中，i≥2，k≥2，k≤i；
    所述测量设备计算第k个时间差和第(k+1)个时间差，其中，所述第k个时间差为所述第k个有效QRS波群中R波的峰值点R与第(k+1)个有效QRS波群中R波的峰值点R的时间差，所述第(k+1)个时间差为所述第(k+1)个有效QRS波群中的R波的峰值点R与第(k+2)个有效QRS波群中的R波的峰值点R的时间差；
    如果所述第k个时间差与所述第(k+1)个时间差处于预设范围，且所述第(k+1)个时间差与所述第k个时间差的差值的绝对值小于预设阈值时，所述测量设备确定所述第k个时间差和所述第(k+1)个时间差为目标时间差；或者，如果所述第k个时间差与所述第(k+1)个时间差处于预设范围，且所述第(k+1)个时间差与所述第k个时间差的差值的绝对值大于等于预设阈值时，所述测量设备确定所述第k个时间差和所述第(k+1)个时间差中偏离时间差平均值较少的一个时间差为目标时间差，所述时间差平均值为第1个时间差至第(k-1)个时间差中所有目标时间差的平均值；
    其中，所述目标时间差用于计算所述ECG信号对应的心率值。
  2. 如权利要求1所述的方法，其特征在于，所述提取所述ECG信号的第k个有效QRS波群，包括：
    所述测量设备确定所述第i个R波对应的第一极值点Q和第二极值点S；
    所述测量设备计算所述第一极值点Q与所述第i个R波的峰值点R之间的时间差为第一时间差，所述第i个R波的峰值点R与所述第二极值点S之间的时间差为第二时间差，所述第一极值点Q与所述第二极值点S之间的时间差为第三时间差；
    如果所述第一时间差、第二时间差、第三时间差分别小于对应的第一阈 值、第二阈值、第三阈值时，则所述第一极值点对应Q波，所述第二极值点对应S波，所述测量设备确定所述第i个R波与对应的Q波和S波构成第k个有效QRS波群。
  3. 如权利要求1或2所述的方法，其特征在于，还包括：
    所述测量设备计算所述ECG信号对应的信号参数；
    所述测量设备根据至少一个所述信号参数计算信号评估参数；
    所述测量设备根据所述信号评估参数与所述信号评估参数对应的预设评估阈值，确定所述ECG信号的信号质量等级。
  4. 如权利要求3所述的方法，其特征在于，所述信号参数包括有效信号功率，基线漂移，和带内噪声；
    所述信号评估参数包括信号伪迹比、和信号带内噪声比，其中，所述信号伪迹比为所述有效信号功率和所述基线漂移的函数，所述信号带内噪声比为所述有效信号功率和所述带内噪声的函数；
    所述测量设备根据所述信号评估参数与所述信号评估参数对应的预设评估阈值，确定所述ECG信号的信号质量等级，包括：
    所述测量设备确定所述信号伪迹比大于对应的预设评估阈值，且所述信号带内噪声比大于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第一等级；
    所述测量设备确定所述信号伪迹比小于等于对应的预设评估阈值，且所述信号带内噪声比大于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第二等级；
    所述测量设备确定所述信号伪迹比大于对应的预设评估阈值，且所述信号带内噪声比小于等于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第三等级；
    所述测量设备确定所述信号伪迹比小于等于对应的预设评估阈值，且所述信号带内噪声比小于等于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第四等级；
    其中，所述第一等级优于所述第二等级，所述第二等级优于所述第三等 级，所述第三等级优于所述第四等级。
  5. 如权利要求1-4任一项所述的方法，其特征在于，在所述提取所述ECG信号的第k个有效QRS波群之前，还包括：
    所述测量设备对所述ECG信号进行滤波处理，并采用三轴加速计拟合用户的运动轨迹；
    所述测量设备将滤波后的ECG信号与所述运动轨迹进行比对，将所述运动轨迹中运动幅度值大于预设幅度阈值的时长对应的所述滤波后的ECG信号中的ECG波形删除。
  6. 一种可穿戴设备，其特征在于，包括：处理器、存储器、心率采集器，电源；
    所述心率采集器，用于采集ECG信号；
    所述存储器，用于存储指令；
    所述处理器，用于调用所述存储器中的指令，执行上述权1-5任一项所述的方法。
  7. 如权利要求6所述的设备，其特征在于，还包括：加速计传感器；
    所述加速传感器，用于检测各个方向上的加速度的大小，拟合运动轨迹。
  8. 一种ECG信号处理装置，其特征在于，包括：采集单元，提取单元，计算单元，处理单元，其中，
    所述采集单元，用于采集ECG信号；
    所述提取单元，用于提取所述ECG信号的第k个有效QRS波群，其中QRS波群包括第i个R波的峰值点R前的第一极值点Q、第i个R波的峰值点R、和第i个R波的峰值点R后的第二极值点S，其中，i≥2，k≥2，k≤i；
    所述计算单元，用于计算第k个时间差和第(k+1)个时间差，其中，所述第k个时间差为所述第k个有效QRS波群中R波的峰值点R与第(k+1)个有效QRS波群中R波的峰值点R的时间差，所述第(k+1)个时间差为所述第(k+1)个有效QRS波群中的R波的峰值点R与第(k+2)个有效QRS波群中的R波的峰值点R的时间差；
    所述处理单元，用于如果所述第k个时间差与所述第(k+1)个时间差处 于预设范围，且所述第(k+1)个时间差与所述第k个时间差的差值的绝对值小于预设阈值时，确定所述第k个时间差和所述第(k+1)个时间差为目标时间差；或者，如果所述第k个时间差与所述第(k+1)个时间差处于预设范围，且所述第(k+1)个时间差与所述第k个时间差的差值的绝对值大于等于预设阈值时，确定所述第k个时间差和所述第(k+1)个时间差中偏离时间差平均值较少的一个时间差为目标时间差，所述时间差平均值为第1个时间差至第(k-1)个时间差中所有目标时间差的平均值；
    其中，所述目标时间差用于计算所述ECG信号对应的心率值。
  9. 如权利要求8所述的装置，其特征在于，所述提取单元，用于：
    所述提取所述ECG信号的第k个有效QRS波群时，确定所述第i个R波对应的第一极值点Q和第二极值点S；
    计算所述第一极值点Q与所述第i个R波的峰值点R之间的时间差为第一时间差，所述第i个R波的峰值点R与所述第二极值点S之间的时间差为第二时间差，所述第一极值点Q与所述第二极值点S之间的时间差为第三时间差；
    如果所述第一时间差、第二时间差、第三时间差分别小于对应的第一阈值、第二阈值、第三阈值时，则所述第一极值点Q对应Q波，所述第二极值点S对应S波，所述第i个R波与对应的Q波和S波构成第k个有效QRS波群。
  10. 如权利要求8或9所述的装置，其特征在于，所述装置，还包括：
    信号质量评估单元，用于计算所述ECG信号对应的信号参数；
    根据至少一个所述信号参数计算信号评估参数；
    根据所述信号评估参数与所述信号评估参数对应的预设评估阈值，确定所述ECG信号的信号质量等级。
  11. 如权利要求10所述的装置，其特征在于，所述信号参数包括有效信号功率，基线漂移，和带内噪声；
    所述信号评估参数包括信号伪迹比、和信号带内噪声比，其中，所述信号伪迹比为所述有效信号功率和所述基线漂移的函数，所述信号带内噪声比 为所述有效信号功率和所述带内噪声的函数；
    所述信号质量评估单元，还用于：根据所述信号评估参数与所述信号评估参数对应的预设评估阈值，确定所述ECG信号的信号质量等级时，确定所述信号伪迹比大于对应的预设评估阈值，且所述信号带内噪声比大于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第一等级；
    确定所述信号伪迹比小于等于对应的预设评估阈值，且所述信号带内噪声比大于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第二等级；
    确定所述信号伪迹比大于对应的预设评估阈值，且所述信号带内噪声比小于等于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第三等级；
    确定所述信号伪迹比小于等于对应的预设评估阈值，且所述信号带内噪声比小于等于对应的预设评估阈值时，确定所述ECG信号的信号质量等级为第四等级；
    其中，所述第一等级优于所述第二等级，所述第二等级优于所述第三等级，所述第三等级优于所述第四等级。
  12. 如权利要求8-11任一项所述的装置，其特征在于，所述装置还包括：
    运动轨迹分析单元，用于在提取所述ECG信号的第k个有效QRS波群之前，对所述ECG信号进行滤波处理，并采用三轴加速计拟合用户的运动轨迹；
    将滤波后的ECG信号与所述运动轨迹进行比对，将所述运动轨迹中运动幅度值大于预设幅度阈值的时长对应的所述滤波后的ECG信号中的ECG波形删除。
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