WO2019014931A1 - Procédé et appareil d'analyse des interférences pour signal biologique, et dispositif portable - Google Patents

Procédé et appareil d'analyse des interférences pour signal biologique, et dispositif portable Download PDF

Info

Publication number
WO2019014931A1
WO2019014931A1 PCT/CN2017/093906 CN2017093906W WO2019014931A1 WO 2019014931 A1 WO2019014931 A1 WO 2019014931A1 CN 2017093906 W CN2017093906 W CN 2017093906W WO 2019014931 A1 WO2019014931 A1 WO 2019014931A1
Authority
WO
WIPO (PCT)
Prior art keywords
interference
parameter
waveform
signal
motion
Prior art date
Application number
PCT/CN2017/093906
Other languages
English (en)
Chinese (zh)
Inventor
王鑫山
李国梁
杨柯
罗朝洪
Original Assignee
深圳市汇顶科技股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳市汇顶科技股份有限公司 filed Critical 深圳市汇顶科技股份有限公司
Priority to PCT/CN2017/093906 priority Critical patent/WO2019014931A1/fr
Priority to CN201780000781.6A priority patent/CN109640789A/zh
Publication of WO2019014931A1 publication Critical patent/WO2019014931A1/fr

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons

Definitions

  • the present application relates to the field of signal processing technologies, and in particular, to a method and device for interference analysis of a biological signal, and a wearable device.
  • Heart rate refers to the number of beats per minute of the human heart, which is a very important physiological indicator in clinical diagnosis.
  • Traditional medical devices require the user to be at rest while measuring heart rate, and are not convenient to carry; therefore, many manufacturers produce wearable devices that can perform heart rate measurement so that the user can measure heart rate in daily life.
  • the most commonly used heart rate measurement method is the photoplethysmography (PPG) method, which uses light-emitting diodes (LEDs) to emit light of a specific wavelength and returns, diffuses, diffracts, and reflects through human tissue, and returns the returned light signal into An electrical signal to obtain the corresponding PPG signal.
  • the light beam is attenuated by the absorption of human tissue during the propagation of human tissue.
  • the absorption of static tissues such as skin, fat, muscle, etc. is a constant value, and the blood undergoes periodic volume changes due to the contraction and diastolic cycles of the heart.
  • the PPG signal contains a periodic waveform consistent with the heartbeat, so the heartbeat frequency can be measured according to the PPG signal, and measuring the heart rate using the photoelectric pulse volume method is a non-invasive measurement method.
  • the prior art has at least the following problem: the heart rate measurement on the wearable device is more demanding on the photoelectric pulse volume method because the user needs to measure the heart rate under the motion state, and the muscle and pressure will change under the motion state, resulting in the light beam.
  • the propagation optical path changes; in addition to the pulse wave signal, the photoelectric pulse volume (PPG) signal is superimposed with the motion interference signal. Movement caused by different movement states Interference frequency and intensity are different, and the frequency and intensity of motion interference are constantly changing; the range of human heart rate is generally in the range of 0.5Hz-4Hz, and many moving frequencies of the human body are also in this range, so it is impossible to Various types of interfering signals in the PPG signal are removed by filtering.
  • the degree of interference of the PPG signal is different when the user is in different motion states. If the PPG signal with different degrees of interference is processed in the same manner to obtain the heart rate value, the accuracy of the obtained heart rate value is different; The currently measured PPG signal is subject to a greater degree of interference, and the calculated heart rate value is less accurate, and it is currently not distinguishable.
  • the purpose of some embodiments of the present application is to provide a method and a device for analyzing interference of a biological signal, and a wearable device, which can analyze the degree of interference of a biological signal, so that different degrees of interference of the biological signal can be selected in subsequent processing.
  • the embodiment of the present application provides a method for analyzing interference of a biological signal, which is applied to a wearable device, and the wearable device can acquire a biological signal and a motion interference signal.
  • the method includes: acquiring a waveform parameter according to the biological signal; and acquiring a motion interference parameter according to the motion interference signal; The waveform parameters and the motion interference parameters are analyzed to obtain the degree of interference of the biological signals.
  • the embodiment of the present application further provides a biological signal interference analysis device, which is applied to a wearable device, and the wearable device can acquire a biological signal and a motion interference signal;
  • the device includes: a waveform parameter acquisition module, configured to acquire a waveform parameter according to the biological signal;
  • the interference parameter acquisition module is configured to obtain the motion interference parameter according to the motion interference signal;
  • the interference analysis module is configured to analyze the waveform parameter and the motion interference parameter to obtain the degree of interference of the biological signal.
  • the embodiment of the present application further provides a wearable device, including: a first sensor, a second sensor, a memory, and a processor connected to the first sensor, the second sensor, and the memory; the first sensor is configured to acquire a biosignal; The sensor is configured to acquire a motion interference signal; the memory is configured to store a plurality of instructions; and the processor is configured to load the plurality of instructions and perform the function of the interference analysis device of the biosignal described above.
  • the present application acquires a waveform parameter according to a biological signal, acquires a motion interference parameter according to the motion interference signal, and separately analyzes the waveform parameter and the motion interference parameter, thereby acquiring the characteristics of the biological signal itself and the motion-to-biological signal.
  • the influence of the biosignal can be obtained, so that different types of processing methods can be selected according to the degree of interference of the biosignal in the subsequent processing to obtain more accurate biological parameters.
  • the waveform parameters and the motion interference parameters are analyzed to obtain the degree of interference of the biological signal, which specifically includes: if the waveform parameter satisfies the first preset condition and the motion interference parameter satisfies the second preset condition, determining that the biological signal is interfered The degree belongs to the first interference level; if the waveform parameter does not satisfy the first preset condition or the motion interference parameter does not satisfy the second preset condition, the degree of interference of the biosignal is determined to be the second interference level; the interference characterized by the first interference level The intensity is lower than the interference intensity characterized by the second interference level.
  • This embodiment provides a specific way of determining the extent to which a biological signal is interfered.
  • the waveform parameters and the motion interference parameters are analyzed to obtain the degree of interference of the biological signal, and specifically: if the waveform parameter does not satisfy the first preset condition and the motion interference parameter does not satisfy the second preset condition, the biological signal is determined.
  • the degree of interference is the third interference level; the interference level characterized by the second interference level is lower than the interference strength characterized by the third interference level. This embodiment further refines the level of the degree to which the biosignal is disturbed.
  • the waveform parameters include one or any combination of the following parameters: the mean value of the adjacent peak interval and the adjacent valley interval, the time difference between adjacent peak intervals, the adjacent peak interval and the adjacent valley The variance of the interval and the waveform time eigenvalue.
  • This embodiment provides a specific kind of waveform parameters.
  • the motion interference signal is an acceleration signal;
  • the motion interference parameter includes a sum of absolute values of accelerations at each moment and an absolute value of acceleration differences of adjacent moments. This embodiment provides a specific type of motion interference parameter.
  • the calculation formula of the waveform time characteristic value R dis is: Where N all is the number of periods of the waveform; N nor is the number of periods in which the ratio of the length of the rising section to the falling section belongs to the preset range in all periods of the waveform.
  • This embodiment provides a specific calculation formula of the waveform time feature value.
  • acquiring waveform parameters according to the biological signal specifically includes: filtering out interference in the biological signal; and calculating waveform parameters according to the biological signal after filtering the interference.
  • This embodiment provides a specific implementation manner for acquiring waveform parameters, and filtering the motion parameters in the biological signal and then calculating the waveform parameters, thereby reducing the computational complexity.
  • the acceleration signal is a multi-dimensional acceleration signal
  • the motion interference parameter is obtained according to the motion interference signal, specifically: performing dimensionality reduction processing on the multi-dimensional acceleration signal, and obtaining a one-dimensional acceleration signal characterizing the motion interference; calculating the motion interference according to the one-dimensional acceleration signal parameter.
  • the dimensionality reduction processing of the multi-dimensional acceleration signal can reduce the computational complexity.
  • FIG. 1 is a specific flowchart of a method for analyzing interference of a biological signal according to a first embodiment of the present application
  • FIG. 2 is a waveform diagram of a typical PPG signal in accordance with a first embodiment of the present application
  • FIG. 3 is a specific flowchart of a method for analyzing interference of a biological signal according to a second embodiment of the present application
  • FIG. 4 is a specific flowchart of a method for analyzing interference of a biological signal according to a third embodiment of the present application.
  • FIG. 5 is a specific flowchart of a method for analyzing interference of a biological signal according to a fourth embodiment of the present application.
  • FIG. 6 is a specific flowchart of a method for analyzing interference of a biological signal according to a fifth embodiment of the present application.
  • FIG. 7 is a block diagram showing an interference analysis device for a biosignal according to a sixth embodiment of the present application.
  • FIG. 8 is a block diagram showing an interference analysis apparatus for a biosignal according to a seventh embodiment of the present application.
  • FIG. 9 is a block diagram showing an interference analysis device for a biosignal according to an eighth embodiment of the present application.
  • FIG. 10 is a block diagram showing an interference analysis apparatus for a biosignal according to a ninth embodiment of the present application.
  • Figure 11 is a block schematic diagram of a wearable device in accordance with a tenth embodiment of the present application.
  • the first embodiment of the present application relates to a method for analyzing interference of a biological signal, which is applied to a wearable device, such as an earphone, a wristband, a headband, etc., and the wearable device can acquire a biological signal and a motion interference signal; wherein the biological signal is, for example, a photoelectric volume.
  • Pulse (PPG) signal, ECG signal, etc. the motion interference signal can be an acceleration signal.
  • the biosignal is a photoplethysmographic pulse (PPG) signal as an example, and the specific flow of the biosignal interference analysis method is shown in FIG. 1 .
  • PPG photoplethysmographic pulse
  • Step 101 Acquire waveform parameters according to the biological signal.
  • the acquired biosignal is processed to extract an active component of the biosignal;
  • the biosignal is a PPG signal
  • the active component of the PPG signal is a component closely related to the heart rate, that is, the AC component ppg ac in the PPG signal.
  • the DC component ppg dc (n) of the PPG signal can be obtained by finding the average value of the PPG signal value in the window time.
  • the specific formula is as follows:
  • N represents the normal window time for calculating the average value of the PPG signal
  • n represents the current time at which the average value of the PPG signal is calculated
  • ppg amp (i) represents the value of the PPG signal at the ith time.
  • the DC component ppg dc (n) of the PPG signal can also be obtained by means of an alpha filter.
  • the specific formula is as follows:
  • ⁇ denotes a filtering parameter
  • a biosignal is used as a PPG signal, and a method for obtaining an active component of a PPG signal is given.
  • the biosignal is an electrocardiogram (ECG) signal, and it is necessary to identify a heartbeat based on its R-waveform, and calculate the heart rate based on the RR interval, that is, the active component of the ECG signal.
  • ECG electrocardiogram
  • the waveform parameter can be calculated according to the active component in the extracted biosignal, and the waveform parameter includes one or any combination of the following parameters: the mean value of the adjacent peak interval and the adjacent trough interval, the time difference between adjacent peak intervals, The variance of the adjacent peak interval and the adjacent valley interval and the waveform time characteristic value; wherein the more parameters included in the waveform parameter, the more accurate the judgment of the degree of interference of the biological signal.
  • the waveform parameters include all of the above four parameters.
  • the following is a description of the specific calculation method of the waveform parameters by taking the biosignal as the PPG signal as an example:
  • Stage 1 represents the rising phase of the pulse wave, representing the rapid ejection cycle of the ventricle, which is characterized by rapid and smooth rise, the rate of rise and the ejection capacity of the ventricle, and the arterial vessels.
  • the resistance is related to the elasticity of the vessel wall.
  • the time of a pulse wave fluctuation cycle is relatively short.
  • the position of point a is the end of ventricular ejection, followed by the closure of the aorta and entering the descending segment.
  • Stage 2 represents the falling phase of the pulse wave, which is a period from the end of the ventricular ejection to the start of the next ejection, and the time of a pulse fluctuation period is relatively long; the PPG signal data of a length of M seconds is acquired, and the data is counted within M seconds.
  • the position of the peak of the PPG signal [peak pos (1),...,peak pos (n),...] and the position of the trough [valley pos (1),...,valley pos (n),...].
  • the mean Avg dis of the adjacent peak interval and the adjacent valley interval can be calculated.
  • the specific calculation formula is as follows:
  • N disp is the number of peak intervals in M seconds
  • N disv is the number of valley intervals in M seconds
  • dis peak ( ⁇ ) is the adjacent peak interval
  • dis valley ( ⁇ ) is the adjacent valley interval
  • the time difference Diff dis (n) of the adjacent peak interval is calculated as follows:
  • dis peak ( ⁇ ) is the adjacent peak interval.
  • dis peak ( ⁇ ) is the adjacent peak interval
  • dis valley ( ⁇ ) is the adjacent trough interval
  • Avg dis is the mean of the adjacent peak interval and the adjacent trough interval
  • N disp is the number of peak intervals in M seconds.
  • N disv is the number of valley intervals in M seconds.
  • peak pos ( ⁇ ) indicates the position of the peak
  • valley pos ( ⁇ ) indicates the position of the valley
  • ratio(n) dis rise /dis des
  • ratio th1 , ratio th2 Calculating the number of cycles of nor (n) in a preset range (ratio th1 , ratio th2 ) according to ratio(n) of all periods of the calculated waveform; wherein ratio th1 and ratio th2 may be according to the user of the wearable device to age, weight, sex and other initial settings, then according to the characteristics of the user PPG signals continue to accumulate, adjusted by way of deep learning, so that more accurate preset range, typically ratio th1 ⁇ ratio th2 ⁇ 1.
  • N all is the number of periods of the waveform; N nor is the number of periods in which the ratio of the length of the rising section to the falling section belongs to the preset range in all periods of the waveform.
  • the biosignal may first determine whether the acquired biosignal is in a normal interval. If the biosignal is outside the normal interval, the biosignal may be incorrect and needs to be adjusted to The biosignal is placed in a normal interval, so that the waveform parameters acquired according to the biosignal are higher in accuracy; wherein the normal interval can be set according to experimental experience.
  • the biosignal is a PPG signal, and its normal interval is (light th1 , light th2 ). If the PPG signal value PPG amp is smaller than light th1 , the light intensity of the light source can be increased by adjusting the light source parameter to increase the PPG signal. Value; if the PPG signal value PPG amp is greater than light th2 , the light intensity of the light source can be reduced by adjusting the light source parameter to reduce the PPG signal value.
  • Step 102 Acquire a motion interference parameter according to the motion interference signal.
  • the motion interference signal is an acceleration signal
  • the corresponding motion interference parameter is calculated according to the acceleration signal, where the motion interference parameter includes a sum of absolute values of the accelerations at each moment, Sum acc, and an absolute value of the acceleration difference of the adjacent moments.
  • Sum difacc the specific calculation formula is as follows;
  • the motion interference signal in this embodiment is an acceleration signal, but is not limited thereto, and different motion interference signals need to be selected for different biological signals.
  • the waveform parameters acquired according to the biological signal cannot fully represent the motion interference, so it is still necessary to obtain the motion interference parameter according to the motion interference signal to analyze the motion interference to the biological The effect of the signal.
  • step 103 the waveform parameters and the motion interference parameters are analyzed to obtain the degree of interference of the biological signals.
  • the waveform parameters and the motion interference parameters of the calculated biosignal are analyzed, and the characteristics of the biosignal itself can be obtained by analyzing the waveform parameters, and the influence of the motion on the biosignal can be obtained by analyzing the motion interference parameters. Thereby, the degree to which the biological signal is disturbed can be obtained.
  • the present embodiment acquires a waveform parameter according to a biological signal, acquires a motion interference parameter according to the motion interference signal, and separately analyzes the waveform parameter and the motion interference parameter, thereby acquiring the characteristics of the biological signal itself and the motion to the biological
  • the influence of the signal can then obtain the degree of interference of the biological signal, so that different types of processing methods can be selected according to the degree of interference of the biological signal in the subsequent processing to obtain more accurate biological parameters.
  • the second embodiment of the present application relates to a method for analyzing interference of a biological signal.
  • This embodiment is a refinement of the first embodiment, and the main refinement is that the waveform parameters and motion interference are performed on step 103 of the first embodiment.
  • the parameters are analyzed to obtain the degree of interference of the biological signal, and a detailed introduction is made.
  • the specific flow of the interference analysis method of the biosignal in this embodiment is as shown in FIG. 3.
  • Step 201 and step 202 are substantially the same as steps 101 and 102, and are not described here.
  • step 203 analyzes waveform parameters and motion interference parameters to obtain interference of biological signals. The extent of this includes:
  • Sub-step 2031 determining whether the waveform parameter satisfies the first preset condition. If yes, go to sub-step 2032; if no, go to sub-step 2034.
  • the first preset condition is to determine whether the parameters included in the waveform parameter respectively satisfy the corresponding preset.
  • the waveform parameters include the mean of the adjacent peak interval and the adjacent valley interval, the time difference between the adjacent peak intervals, the variance of the adjacent peak interval and the adjacent valley interval, and the waveform time characteristic value, which are set differently for different parameters. Threshold to determine whether it meets the preset conditions, as follows:
  • Var dis When the variance of the adjacent peak interval and the adjacent valley interval Var dis is less than or equal to the preset variance threshold Th varup , it is determined that Var dis satisfies the corresponding preset condition; otherwise, it is determined that Var dis is not satisfied. Its corresponding preset condition.
  • the mean range (Th avgup , Th avgdown ), the time difference threshold Th avgup , the variance threshold Th varup , and the waveform characteristic threshold Th R can be obtained according to the waveform characteristics of the biosignal, which is not used in this embodiment. Any restrictions.
  • the selected waveform parameter is one or any combination of the above four parameters.
  • Sub-step 2032 determining whether the motion interference parameter satisfies the second preset condition. If yes, go to sub-step 2033, and if no, go to sub-step 2034.
  • the motion interference parameter includes a sum of absolute values of accelerations at each moment, Sum acc, and a sum of absolute values of acceleration moments of adjacent moments, Sum difacc , when Sum acc is less than or equal to a preset first threshold of acceleration or Sum difacc is less than Or equal to the preset second threshold of acceleration, determining that the motion interference parameter satisfies the second preset condition; otherwise, determining that the motion interference parameter does not satisfy the second preset condition.
  • the first threshold of the acceleration and the second threshold of the acceleration are set according to the motion state of the user of the wearable device, and the embodiment does not impose any limitation.
  • Sub-step 2033 the degree to which the biosignal is disturbed belongs to the first interference level.
  • the waveform parameter satisfies the first preset condition and the motion interference parameter satisfies the second preset condition, it is determined that the degree of interference of the biological signal belongs to the first interference level, and at this time, the degree of interference of the biological signal is low.
  • the biosignal can be processed by a relatively simple method such as time domain waveform method.
  • the degree of interference of the biological signal can be considered to be lower, that is, the biological signal The less interference signals are included.
  • Sub-step 2034 the degree to which the biosignal is disturbed belongs to the second interference level.
  • the interference signal included in the biosignal is compared. More or more received motion interference, determine the degree of interference of the biological signal is the second interference level, and subsequently need to adopt a stronger anti-interference ability to filter out the interference in the biological signal; wherein, the interference level characterized by the first interference level The interference strength is lower than the second interference level.
  • the actual execution order of the sub-step 2031 and the sub-step 2032 is not limited. That is, in this embodiment, it may also be determined whether the motion interference parameter satisfies the second preset condition, and then the waveform parameter is determined. The first preset condition is met; wherein, if it is determined that the motion interference parameter satisfies the second preset condition and the waveform parameter does not satisfy the first preset condition, the degree of interference of the biological signal is also determined to be the second interference level.
  • this embodiment determines the biometric letter by whether the parameter satisfies the preset condition.
  • the degree of interference of the number is not limited thereto, and other methods, such as an accumulation method, a weighted accumulation method, and the like, may be adopted, and this embodiment does not impose any limitation.
  • the waveform parameter includes one or any combination of the above four parameters, and respectively determines whether the parameter included in the waveform parameter satisfies the corresponding preset condition, and when the parameter When it meets its corresponding preset condition, it is recorded as 1, when it is not satisfied, it is recorded as 0, and the value of all judgment results is accumulated as the value of the waveform parameter; when the motion interference parameter satisfies the second preset condition, it is recorded as 1, when it is not satisfied It is 0; finally, the value of the accumulated waveform parameter is added to the value of the motion interference parameter, and the larger the added value is, the weaker the degree of interference of the biological signal is.
  • This embodiment provides a specific way of determining the extent to which a biosignal is interfered with respect to the first embodiment.
  • the third embodiment of the present application relates to a method for analyzing interference of a biological signal.
  • the improvement of the present embodiment based on the second embodiment is mainly improved in that the level of the degree to which the biological signal is interfered is refined.
  • the specific flow of the interference analysis method of the biosignal in this embodiment is as shown in FIG. 4.
  • Step 301 and step 302 are substantially the same as steps 201 and 202.
  • Sub-step 3031 to sub-step 3034 are substantially the same as sub-step 2031 to sub-step 2034, and are not described here again. The main difference is that in this embodiment. , sub-step 3035 and sub-step 3036 are added as follows:
  • Sub-step 3035 determining whether the motion interference parameter satisfies the second preset condition. If yes, go to sub-step 3034; if no, go to sub-step 3036.
  • the process proceeds to sub-step 3035, that is, whether the motion interference parameter satisfies the second preset condition, and the specific determination is made.
  • Process and sub-step 2032 in the second embodiment (sub-step 3032 in this embodiment) The same, no longer repeat here.
  • the determination result of the sub-step 3035 is YES (ie, it is determined that the motion interference parameter satisfies the second preset condition)
  • the sub-step 3034 is entered to determine that the degree of interference of the bio-signal belongs to the second interference level; otherwise, the sub-step 3036 is entered. .
  • Sub-step 3036 the degree to which the biosignal is disturbed belongs to the third interference level.
  • the waveform parameter does not satisfy the first preset condition and the motion interference parameter does not satisfy the second preset condition, indicating that the biological signal includes more interference signals and is subjected to strong motion interference, determining that the biological signal is interfered
  • the degree is the third interference level, in which case the biosignal needs to be re-acquired or the interference is further filtered out in subsequent processing.
  • the interference level characterized by the second interference level is lower than the interference intensity characterized by the third interference level.
  • the actual execution order of the sub-step 3031 and the sub-step 3032 is not limited. That is, in this embodiment, it may also be determined whether the motion interference parameter satisfies the second preset condition, and then the waveform parameter is determined. The first preset condition is met. At this time, the sub-step 3035 is to determine whether the waveform parameter satisfies the first preset condition.
  • the embodiment determines whether the motion interference parameter satisfies the second preset condition, and further refines the degree of interference of the biological signal. grade.
  • the fourth embodiment of the present application relates to a method for analyzing interference of a biological signal.
  • This embodiment is a refinement of the first embodiment, and the main refinement is that step 101 of the first embodiment acquires waveform parameters according to a biological signal. , a detailed introduction was made.
  • the specific flow of the interference analysis method of the biosignal in this embodiment is as shown in FIG. 5.
  • Step 402 and step 403 are substantially the same as steps 102 and 103, and are not described here.
  • the main difference is that in the embodiment, step 401 acquires waveform parameters according to the biological signal. Specifically include:
  • Sub-step 4011 filters out interference in the biosignal.
  • the interference in the biosignal is divided into in-band interference and out-of-band interference
  • the out-of-band interference can use a finite impulse response (FIR) or an infinite impulse response (IIR) filter to filter out interference.
  • FIR finite impulse response
  • IIR infinite impulse response
  • a FIR filter based on Hanning window function is used to filter out-of-band interference.
  • the function of Hanning window w hn (n) is as follows:
  • the passband bandwidth of the FIR filter can be selected as [0.4, 10] Hz, and the information of the active component can be retained as much as possible while effectively removing the breathing and other disturbances. It should be noted that, in this embodiment, the passband bandwidth of the FIR filter is not limited, and may be specifically set according to the type of out-of-band interference included in the biosignal.
  • In-band interference is mainly motion interference, and a filter that adaptively filters motion interference can be used to filter motion interference in biological signals.
  • Sub-step 4012 calculates waveform parameters based on the filtered biosignal.
  • the waveform parameters are calculated according to the waveform characteristics of the biosignal.
  • the present embodiment provides a specific implementation manner for acquiring waveform parameters, and filtering the motion parameters in the biological signal and then calculating the waveform parameters, thereby reducing the computational complexity. It should be noted that the present embodiment can also be refined on the basis of any of the second embodiment to the fourth embodiment, and the same technical effects can be achieved.
  • the fifth embodiment of the present application relates to a method for analyzing interference of a biological signal.
  • This embodiment is a refinement of the first embodiment, and the main refinement is that the step 102 of the first embodiment is based on motion drying.
  • the disturbance signal acquires the motion interference parameters and is described in detail.
  • the specific flow of the interference analysis method of the biosignal in this embodiment is as shown in FIG. 6.
  • Step 501 and step 503 are substantially the same as steps 101 and 103, and are not described here.
  • the motion interference signal is a multi-dimensional acceleration signal
  • step 502 acquires motion interference according to the motion interference signal. Parameters, including:
  • Sub-step 5021 performing dimensionality reduction on the multi-dimensional acceleration signal, and obtaining a one-dimensional acceleration signal characterizing motion interference.
  • the acceleration signal of the motion state is generally a multi-dimensional acceleration signal, so that the multidimensional acceleration signal needs to be subjected to dimensionality reduction processing to obtain a one-dimensional acceleration signal that characterizes motion interference.
  • the dimensionality reduction processing method such as the principal component analysis method and the independent component analysis method may be used for the dimensionality reduction processing.
  • the embodiment does not impose any limitation on the manner of the dimensionality reduction processing.
  • Sub-step 5022 calculating a motion interference parameter based on the one-dimensional acceleration signal.
  • the motion interference parameter can be calculated, that is, the sum of the absolute values of the accelerations at each moment Sum acc and the absolute difference of the acceleration moments at the adjacent moments.
  • the present embodiment performs dimensionality reduction processing on the multi-dimensional acceleration signal, which can reduce the computational complexity. It should be noted that the embodiment can also be refined on the basis of any of the second embodiment to the fifth embodiment, and the same technical effects can be achieved.
  • the sixth embodiment of the present application relates to a biological signal interference analysis device, which is applied to a wear setting
  • the wearable device can acquire the biological signal and the motion interference signal
  • the biological signal is, for example, a photoelectric volume pulse (PPG) signal, an electrocardiogram signal, etc.
  • the motion interference signal can be an acceleration signal.
  • the interference analysis device for the biosignal includes a waveform parameter acquisition module 1 , a motion interference parameter acquisition module 2 , and an interference analysis module 3 .
  • the waveform parameter acquisition module 1 is configured to acquire waveform parameters according to the biological signal.
  • the waveform parameter includes one or any combination of the following parameters: the mean value of the adjacent peak interval and the adjacent valley interval, the time difference between adjacent peak intervals, the variance of the adjacent peak interval and the adjacent valley interval, and the waveform time. Eigenvalues.
  • N all is the number of periods of the waveform; N nor is the number of periods in which the ratio of the length of the rising section to the falling section belongs to the preset range in all periods of the waveform.
  • the motion interference parameter acquisition module 2 is configured to acquire motion interference parameters according to the motion interference signal.
  • the motion interference signal is an acceleration signal; the motion interference parameter includes a sum of an absolute value of the acceleration of each moment and an absolute value of the acceleration difference of the adjacent moment.
  • the interference analysis module 3 is configured to analyze the waveform parameters and the motion interference parameters to obtain the degree of interference of the biological signals.
  • this embodiment is an apparatus embodiment corresponding to the first embodiment, and this embodiment can be implemented in cooperation with the first embodiment.
  • the related technical details mentioned in the first embodiment are still effective in this embodiment, and are not described herein again in order to reduce repetition. Accordingly, the related art details mentioned in the embodiment can also be applied to the first embodiment.
  • waveform parameters are acquired according to biological signals
  • the dynamic interference signal acquires the motion interference parameter, and analyzes the waveform parameter and the motion interference parameter respectively, so that the characteristics of the biological signal itself and the influence of the motion on the biological signal can be obtained, and then the degree of interference of the biological signal can be obtained, enabling subsequent Different types of processing methods are selected according to the degree of interference of biological signals in the process to obtain more accurate biological parameters.
  • the seventh embodiment of the present application relates to a biosignal interference analysis apparatus.
  • This embodiment is a refinement of the sixth implementation.
  • the main refinement is that, referring to FIG. 8, the interference analysis module 3 includes a waveform parameter judging.
  • the waveform parameter determination sub-module 31 is configured to determine whether the waveform parameter satisfies the first preset condition.
  • the interference parameter determination sub-module 32 is configured to determine whether the motion interference parameter satisfies the second preset condition.
  • the interference level judging sub-module 33 is for determining the degree to which the biosignal is interfered.
  • the interference degree judging sub-module 33 determines that the waveform parameter satisfies the first preset condition, and the interference parameter judging sub-module 32 determines that the motion interference parameter satisfies the second preset condition, and determines that the degree of interference of the bio-signal is The first interference level.
  • the interference level determining sub-module 33 determines that the biological signal is interfered when the waveform parameter determining sub-module 31 determines that the waveform parameter does not satisfy the first preset condition, or the interference parameter determining sub-module 32 determines that the motion interference parameter does not satisfy the second preset condition.
  • the degree is the second interference level; the interference level characterized by the first interference level is weaker than the second interference level.
  • the interference level determining sub-module 33 determines that the waveform parameter does not satisfy the first preset condition, and the interference parameter determining sub-module 32 determines that the motion interference parameter does not satisfy the second preset condition, and determines that the biological signal is interfered.
  • the degree is the third interference level; the interference level characterized by the second interference level is weaker than the third interference level.
  • the embodiment can The second embodiment and the third embodiment are implemented in cooperation with each other.
  • the related technical details mentioned in the second embodiment and the third embodiment are still effective in the embodiment, and the technical effects that can be achieved in the second embodiment and the third embodiment can also be implemented in the embodiment. In order to reduce duplication, we will not repeat them here. Accordingly, the related art details mentioned in this embodiment can also be applied to the second embodiment and the third embodiment.
  • This embodiment provides a specific way of determining the degree to which a biological signal is interfered with respect to the sixth embodiment.
  • the eighth embodiment of the present application relates to a biosignal interference analysis apparatus.
  • This embodiment is a refinement of the sixth implementation.
  • the main refinement is that, referring to FIG. 9, the waveform parameter acquisition module 1 includes an interference filter. Module 11 and waveform parameter calculation sub-module 12.
  • the interference filtering sub-module 11 is used to filter out interference in the biological signal.
  • the waveform parameter calculation sub-module 12 is configured to calculate a waveform parameter according to the biological signal after filtering the interference.
  • the present embodiment can be implemented in cooperation with the fourth embodiment.
  • the technical details mentioned in the fourth embodiment are still effective in this embodiment.
  • the technical effects that can be achieved in the fourth embodiment can also be implemented in the embodiment. To reduce the repetition, details are not described herein again. Accordingly, the related art details mentioned in the embodiment can also be applied to the fourth embodiment.
  • the present embodiment provides a specific implementation manner for acquiring waveform parameters, and filtering the motion parameters in the biological signal to calculate the waveform parameters, thereby reducing the computational complexity. It should be noted that the present embodiment can also be refined on the basis of the seventh embodiment, and the same technical effects can be achieved.
  • the ninth embodiment of the present application relates to a device for analyzing interference of a biological signal.
  • the present embodiment is a refinement of the sixth embodiment.
  • the main refinement is as follows: Referring to FIG. 10, the motion interference parameter acquiring module 2
  • the dimension reduction processing sub-module 21 and the motion interference parameter calculation sub-module 22 are included.
  • the acceleration signal in this embodiment is a multi-dimensional acceleration signal.
  • the dimensionality reduction processing sub-module 21 is configured to perform dimensionality reduction processing on the multi-dimensional acceleration signal, and obtain a one-dimensional acceleration signal that characterizes motion interference; wherein the motion interference signal is a multi-dimensional acceleration signal.
  • the motion interference parameter calculation sub-module 22 is configured to calculate a motion interference parameter according to the one-dimensional acceleration signal.
  • the present embodiment can be implemented in cooperation with the fifth embodiment.
  • the related technical details mentioned in the fifth embodiment are still effective in this embodiment, and the technical effects that can be achieved in the fifth embodiment can also be implemented in the present embodiment. To reduce repetition, details are not described herein again. Accordingly, the related art details mentioned in the embodiment can also be applied to the fifth embodiment.
  • the present embodiment can reduce the computational complexity by performing dimensionality reduction on the multi-dimensional acceleration signal. It should be noted that the present embodiment can also be refined on the basis of the seventh embodiment or the eighth embodiment, and the same technical effects can be achieved.
  • the tenth embodiment of the present application relates to a wearable device, such as an earphone, a wristband, a headband, and the like.
  • the wearable device includes a first sensor 4, a second sensor 5, a memory 6, and a processor 7.
  • the processor 7 is connected to the first sensor 4, the second sensor 5, and the memory 6.
  • the first sensor 4 is used to acquire a biosignal.
  • the second sensor 5 is used to acquire a motion interference signal.
  • the memory 6 is used to store a plurality of instructions.
  • the processor 7 is configured to load a plurality of instructions and perform the function of the interference analysis device of the biosignal of any of the sixth to ninth embodiments.
  • This embodiment provides a wearable device that can analyze the extent to which a biosignal is interfered with respect to the prior art.

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
  • Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)

Abstract

L'invention concerne un procédé et un appareil d'analyse des interférences pour un signal biologique, et un dispositif portable. Le procédé d'analyse des interférences pour un signal biologique comprend : l'acquisition d'un paramètre de forme d'onde conforme au signal biologique (201) ; l'acquisition d'un paramètre d'interférence associé aux mouvements conforme à un signal d'interférence associé aux mouvements (202) ; et l'analyse du paramètre de forme d'onde et du paramètre d'interférence associé aux mouvements pour obtenir le degré d'interférence avec le signal biologique. Grâce à ce procédé, il est possible d'analyser le degré d'interférence avec un signal biologique, si bien que différents types de procédés de traitement peuvent être sélectionnés en fonction du degré d'interférence avec le signal biologique, de façon à effectuer un traitement ultérieur sur le signal biologique, et obtenir ainsi un paramètre biologique plus précis.
PCT/CN2017/093906 2017-07-21 2017-07-21 Procédé et appareil d'analyse des interférences pour signal biologique, et dispositif portable WO2019014931A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/CN2017/093906 WO2019014931A1 (fr) 2017-07-21 2017-07-21 Procédé et appareil d'analyse des interférences pour signal biologique, et dispositif portable
CN201780000781.6A CN109640789A (zh) 2017-07-21 2017-07-21 生物信号的干扰分析方法及装置、穿戴设备

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/093906 WO2019014931A1 (fr) 2017-07-21 2017-07-21 Procédé et appareil d'analyse des interférences pour signal biologique, et dispositif portable

Publications (1)

Publication Number Publication Date
WO2019014931A1 true WO2019014931A1 (fr) 2019-01-24

Family

ID=65014967

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/093906 WO2019014931A1 (fr) 2017-07-21 2017-07-21 Procédé et appareil d'analyse des interférences pour signal biologique, et dispositif portable

Country Status (2)

Country Link
CN (1) CN109640789A (fr)
WO (1) WO2019014931A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112494001A (zh) * 2020-11-25 2021-03-16 青岛歌尔智能传感器有限公司 Ppg信号质量评估方法、装置、穿戴式设备及存储介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104323769A (zh) * 2014-09-19 2015-02-04 中国人民解放军第三军医大学 一种抑制心肺复苏引起的心电干扰的方法、系统及体外除颤仪
CN105286845A (zh) * 2015-11-29 2016-02-03 浙江师范大学 一种适用于可穿戴式心率测量设备的运动噪声消除方法
CN105380602A (zh) * 2015-11-13 2016-03-09 汪毅 可穿戴人体跟腱信息采集及监控系统
CN105997034A (zh) * 2016-04-29 2016-10-12 京东方科技集团股份有限公司 一种心率检测装置、可穿戴设备和心率检测方法

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100871565B1 (ko) * 2006-05-30 2008-12-02 삼성전자주식회사 동잡음 제거된 혈류량 신호 검출 장치 및 방법
JP4964953B2 (ja) * 2007-06-08 2012-07-04 パナソニック株式会社 脈波検出装置、機器制御装置および脈波検出方法
US8827917B2 (en) * 2008-06-30 2014-09-09 Nelleor Puritan Bennett Ireland Systems and methods for artifact detection in signals
WO2010042790A2 (fr) * 2008-10-10 2010-04-15 Cardiac Pacemakers, Inc. Stratégie faisant appel à de multiples capteurs pour la prise en charge d'un patient souffrant d'une défaillance cardiaque
US8755876B2 (en) * 2011-12-02 2014-06-17 Worcester Polytechnic Institute Methods and systems for atrial fibrillation detection
CN104684459B (zh) * 2012-08-01 2017-09-12 皇家飞利浦有限公司 光体积描记术测量中识别运动伪影并且改善测量结果和警报的可靠性的方法和系统
US10045702B2 (en) * 2013-10-17 2018-08-14 Koninklijke Philips N.V. Automatic camera adjustment for remote photoplethysmography
US20150190077A1 (en) * 2014-01-07 2015-07-09 Samsung Electronics Co., Ltd. Electronic device and photoplethysmography method
US10258288B2 (en) * 2014-03-24 2019-04-16 Samsung Electronics Co., Ltd. Confidence indicator for physiological measurements using a wearable sensor platform
US9794653B2 (en) * 2014-09-27 2017-10-17 Valencell, Inc. Methods and apparatus for improving signal quality in wearable biometric monitoring devices
CN104720787A (zh) * 2015-04-01 2015-06-24 深圳柔微传感科技有限公司 一种实现疲劳实时监测的方法和智能服装

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104323769A (zh) * 2014-09-19 2015-02-04 中国人民解放军第三军医大学 一种抑制心肺复苏引起的心电干扰的方法、系统及体外除颤仪
CN105380602A (zh) * 2015-11-13 2016-03-09 汪毅 可穿戴人体跟腱信息采集及监控系统
CN105286845A (zh) * 2015-11-29 2016-02-03 浙江师范大学 一种适用于可穿戴式心率测量设备的运动噪声消除方法
CN105997034A (zh) * 2016-04-29 2016-10-12 京东方科技集团股份有限公司 一种心率检测装置、可穿戴设备和心率检测方法

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112494001A (zh) * 2020-11-25 2021-03-16 青岛歌尔智能传感器有限公司 Ppg信号质量评估方法、装置、穿戴式设备及存储介质

Also Published As

Publication number Publication date
CN109640789A (zh) 2019-04-16

Similar Documents

Publication Publication Date Title
JP7019611B2 (ja) 被検者の呼吸情報を決定するための方法及び装置
KR102622403B1 (ko) 생물학적 데이터 처리
JP6516846B2 (ja) 睡眠監視のデバイス及び方法
Paalasmaa et al. Adaptive heartbeat modeling for beat-to-beat heart rate measurement in ballistocardiograms
JP3787336B2 (ja) Ｐｐｇを用いた心拍検出装置及びその方法
JP5529796B2 (ja) 移動式生理学的モニタリングからのデータを処理する方法及びシステム
US6393311B1 (en) Method, apparatus and system for removing motion artifacts from measurements of bodily parameters
EP1224566B1 (fr) Appareil d'elimination d'artefacts dus au mouvement a partir de mesures de parametres corporels
US8668649B2 (en) System for cardiac status determination
CN109222949A (zh) 心率检测方法和心率检测装置
AU2016202374B2 (en) System and method for characterizing circulatory blood flow
JP5760351B2 (ja) 睡眠評価装置、睡眠評価システムおよびプログラム
JP6310401B2 (ja) 生理的リズムを表す信号を処理する方法、システム及びコンピュータプログラム
JP6079824B2 (ja) 睡眠評価装置およびプログラム
US20120157791A1 (en) Adaptive time domain filtering for improved blood pressure estimation
US10470717B2 (en) Pulse validation
JP6627112B2 (ja) 生体機能検査装置、生体機能検査装置の作動方法及びプログラム
KR20070087787A (ko) 생체신호를 통해 실시간으로 감정을 분류하는감정분류시스템과, 감정분류방법
CN102197998B (zh) 示波测量法中伪影的频谱的使用
Tun Photoplethysmography (PPG) scheming system based on finite impulse response (FIR) filter design in biomedical applications
Nagura et al. A practical BCG measuring system with bed sensors and algorithm for heartbeat detection
KR20100027460A (ko) 다중 윈도우를 이용한 생체신호의 특성 파라미터 추출 장치및 방법
Aarthi et al. Fingertip based estimation of heart rate using photoplethysmography
WO2019014931A1 (fr) Procédé et appareil d'analyse des interférences pour signal biologique, et dispositif portable
CN108201440B (zh) 基于生理参数的报警装置及方法、医用设备

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17918128

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 17918128

Country of ref document: EP

Kind code of ref document: A1