CN109542021A - A kind of sensor weak signal data acquisition method and device - Google Patents
A kind of sensor weak signal data acquisition method and device Download PDFInfo
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- CN109542021A CN109542021A CN201811585522.7A CN201811585522A CN109542021A CN 109542021 A CN109542021 A CN 109542021A CN 201811585522 A CN201811585522 A CN 201811585522A CN 109542021 A CN109542021 A CN 109542021A
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- G05B19/00—Programme-control systems
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Abstract
The invention discloses a kind of sensor weak signal data acquisition method and devices, since the collected electric signal of sensor is to carry out segment transmissions by data packet, difference processing, which is carried out, by the electric signal for acquiring sensor obtains the differential threshold denoising that differential signal calculates electric signal, and dynamic adjusts differential threshold, it can be when the sensor in strongly disturbing environment be acquired weak electric signal, differential threshold can dynamically be adjusted, previous differential threshold can be modified, make its with electric signal true value close to；Make algorithm that there is good robustness, fault-tolerant ability is strong, and the data acquired in strongly disturbing environment can be made accurate, is suitble to the sensor of low speed embedded microprocessor to the continuous acquisition of signal.
Description
Technical field
This disclosure relates to sensor data acquisition technical field, and in particular to a kind of sensor weak signal data acquisition method
And device.
Background technique
The Embedded sensor of low speed is being used when there are strongly disturbing environment acquisition data, due to the original of sensor itself
Cause and signal source are very weak, and strongly disturbing environment can generate the electric current of different signal strength, frequency and waveform, electric and magnetic fields
Sensor is interfered, these electromagnetic fields can generate strong influence, especially sensor to the normal work of sensor
Microprocessor C8051F300 or S3C44B0 since it is desired that continue to monitor for a long time, to operate under tens MHz, easily by
Lead to the unstable of collected weak signal to interference, possible noise source has: 1, baseline drift, low-frequency interference signal,
Frequency range is 0.15~0.3Hz, and waveform is sine wave curve, and baseline drift is mainly that exterior vibration causes；2, motion artifacts:
Since monitoring object or sensor will lead to due to some form of physical displacement the transition of the mobile generation of electrode in sensor
Interference, the duration is up to 100~500ms；3, power supply magnetic fields Hz noise: are mainly derived from monitoring object and sensing
Caused by loop circuit between device, frequency content includes the fundamental wave and its each harmonic of 50Hz.Waveform is the superposition of sine wave.
Therefore, during weak signal data acquisition, can all make to pass from vibration interference, displacement interference and Hz noise etc.
The signal-to-noise ratio of sensor declines, or even the weak signal acquired required for being completely covered, seriously affects after sensor acquires to weak letter
Number it is further analysis and processing.In order to filter the various noises in weak signal, existing method mainly has: average filter, frequency
Domain filtering, adaptive-filtering and most emerging wavelet filtering etc., these methods are still unsuitable for embedded using low speed
Acquisition of the sensor of microprocessor to signal is sensed for example, by using the ST-03A type methane of embedded microprocessor MCF5307
Device, the acceleration transducer of embedded scm STM32F101R8T6, the various types using embedded microprocessor S3C44B0X
Number temperature sensor and using embedded microprocessor S3C44B0X gas sensor.
Summary of the invention
The disclosure provides a kind of sensor weak signal data acquisition method and device, due to the collected electric signal of sensor
It is to carry out segment transmissions by data packet, difference processing is carried out by the electric signal for acquiring sensor and obtains differential signal calculating electricity
The differential threshold of signal denoises, and dynamic adjusts differential threshold, can be acquired in the sensor in strongly disturbing environment weak
Electric signal when, can dynamically adjust differential threshold, previous differential threshold can be modified, make itself and electric signal true value
Close to.
To achieve the goals above, according to the one side of the disclosure, a kind of sensor weak signal data acquisition method is provided,
It the described method comprises the following steps:
Step 1, the electric signal of sensor acquisition is subjected to difference processing and obtains differential signal；
Step 2, the differential threshold of electric signal is calculated according to differential signal；
Step 3, second differnce minimum point is positioned according to differential threshold；
Step 4, it removes the noise in the position of minimum point and obtains denoising minimum point position；
Step 5, according to the crest value in denoising minimum point position positioning electric signal；
Step 6, dynamic adjustment differential threshold.
Further, in step 1, the electric signal of sensor acquisition is subjected to the method that difference processing obtains differential signal
Are as follows:
If the sampled value difference of the electric signal X (n) of sensor acquisition is exported as filtering, difference equation are as follows: y (n)
=[X (n-3)+X (n-2)+X (n-1)+X (n)]/4；The l that y (n), n=1,2 obtained after filtering ..., wherein l is signal length, to y
(n) it carries out single order and second differnce obtains differential signal e (n): d (n)=y (n+1)-y (n), n=1,2 ..., l-1；E (n)=d
(n+1)-d (n), n=1,2 ..., l-2, sensor is to be sensed using the ST-03A type methane of embedded microprocessor MCF5307
Device, using the acceleration transducer of embedded scm STM32F101R8T6, using the temperature of embedded microprocessor S3C44B0X
Spend sensor and the gas sensor using embedded microprocessor S3C44B0X.
Further, in step 2, the method for the differential threshold of electric signal is calculated according to differential signal are as follows:
The electrical signal data that 300 milliseconds of sensor continuous acquisition, withSample frequency length be averaged to e (n)
It is divided into k sampling interval, calculates the differential threshold of electric signalWherein, fsFor sample frequency, fs
Frequency range is 30~500Hz.
Further, in step 3, the method for the differential threshold of electric signal is calculated according to differential signal are as follows:
Sensor continues to acquire electrical signal data, as e (n) the < th for detecting electrical signal data, startsSampling frequency
The minimum value of search e (n) in rate length, record minimum value are the position Re (i) in second differnce e (n), i.e. minimum point, Re
(i) be positive set of integers.
Further, in step 4, it removes the noise in the position of minimum point and obtains the side of denoising minimum point position
Method are as follows:
Noise is removed to positive integer collection Re (i), introduces rr (i) and mean (rr), Ime (j) the difference sequence that wherein rr (i) is
Column, mean (rr) indicate the mean value of rr (i), i=1,2 ..., L-1；
If rr (i) >=1.5mean (rr), according to half differential threshold, i.e.,The weight between Re (i) and Re (i+1)
New search minimum point position ought detect electrical signal data as denoising minimum point positionStartThe minimum value of search e (n) in sample frequency length, record minimum value are the position Re (i) in second differnce e (n), that is, are gone
It makes an uproar minimum point position；
If rr (i)≤0.35mean (rr), the big minimum point position of the signal amplitude of selection Re (i) and Re (i+1)
As denoising minimum point position；
Further, in steps of 5, according to the method for the crest value in denoising minimum point position positioning electric signal are as follows:
The minimum min (e) in filtering signal e (n) is found out, if position of the minimum in e filtering signal sequence is Ime (i), i
=1,2 ..., m, m are the sum of local minimum, respectively at Re (i) -4 of the Re (i) -5 of raw electrical signal x (n) and y (n)
Beginning is set to existFor search local maximum as crest value, crest value is before denoising minimum point position in sample frequency length
One sampled point；
Further, in step 6, the method that dynamic adjusts differential threshold are as follows:
Since the collected electric signal of sensor is to carry out segment transmissions by data packet, 300 milliseconds of sensor continuous acquisition
Electrical signal data, withSample frequency length k sampling interval is averagely divided into e (n), carry out according to the following formula
Dynamic adjustment differential threshold,Wherein, e [Re (i)] is that electric signal corresponds to second order difference value；When adopting
When collecting jth segment data, respectively according to formulaThe differential threshold of acquisition
It is th (j) and TH (j) respectively, then adjusts the differential threshold TH (j+1) of+1 segment signal of jth are as follows:
TH (j+1)=0.75 × TH (j)+0.25 × th (j+1).
The present invention also provides a kind of sensor weak signal data acquisition device, described device includes: memory, processor
And the computer program that can be run in the memory and on the processor is stored, the processor executes the meter
Calculation machine program operates in the unit of following device:
Difference processing unit, the electric signal for acquiring sensor carry out difference processing and obtain differential signal；
Threshold computation unit, for calculating the differential threshold of electric signal according to differential signal；
Minimum positioning unit, for positioning second differnce minimum point according to differential threshold；
Minimum denoises unit, and the noise in position for removing minimum point obtains denoising minimum point position；
Wave crest positioning unit, for according to the crest value in denoising minimum point position positioning electric signal；
Threshold adjustment unit, for dynamically adjusting differential threshold.
The disclosure has the beneficial effect that the present invention provides a kind of sensor weak signal data acquisition method and device, strong
When sensor in the environment of interference is acquired weak electric signal, differential threshold can be dynamically adjusted, it can be to previous difference
Threshold value is modified, make its with electric signal true value close to；Make algorithm that there is good robustness, fault-tolerant ability is strong, can make
The data acquired in strongly disturbing environment are accurate, are suitble to the sensor of low speed embedded microprocessor to the continuous acquisition of signal.
Detailed description of the invention
By the way that the embodiment in conjunction with shown by attached drawing is described in detail, above-mentioned and other features of the disclosure will
More obvious, identical reference label indicates the same or similar element in disclosure attached drawing, it should be apparent that, it is described below
Attached drawing be only some embodiments of the present disclosure, for those of ordinary skill in the art, do not making the creative labor
Under the premise of, it is also possible to obtain other drawings based on these drawings, in the accompanying drawings:
Fig. 1 show a kind of flow chart of sensor weak signal data acquisition method；
Fig. 2 show a kind of sensor weak signal data acquisition device figure.
Specific embodiment
It is carried out below with reference to technical effect of the embodiment and attached drawing to the design of the disclosure, specific structure and generation clear
Chu, complete description, to be completely understood by the purpose, scheme and effect of the disclosure.It should be noted that the case where not conflicting
Under, the features in the embodiments and the embodiments of the present application can be combined with each other.
As shown in Figure 1 for according to a kind of flow chart of sensor weak signal data acquisition method of the disclosure, below with reference to
Fig. 1 illustrates a kind of sensor weak signal data acquisition method according to embodiment of the present disclosure.
The disclosure proposes a kind of sensor weak signal data acquisition method, specifically includes the following steps:
Step 1, the electric signal of sensor acquisition is subjected to difference processing and obtains differential signal；
Step 2, the differential threshold of electric signal is calculated according to differential signal；
Step 3, second differnce minimum point is positioned according to differential threshold；
Step 4, it removes the noise in the position of minimum point and obtains denoising minimum point position；
Step 5, according to the crest value in denoising minimum point position positioning electric signal；
Step 6, dynamic adjustment differential threshold.
Further, in step 1, the electric signal of sensor acquisition is subjected to the method that difference processing obtains differential signal
Are as follows:
If the sampled value difference of the electric signal X (n) of sensor acquisition is exported as filtering, difference equation are as follows: y (n)
=[X (n-3)+X (n-2)+X (n-1)+X (n)]/4；The l that y (n), n=1,2 obtained after filtering ..., wherein l is signal length, to y
(n) it carries out single order and second differnce obtains differential signal e (n): d (n)=y (n+1)-y (n), n=1,2 ..., l-1；E (n)=d
(n+1)-d (n), n=1,2 ..., l-2, sensor is to be sensed using the ST-03A type methane of embedded microprocessor MCF5307
Device, using the acceleration transducer of embedded scm STM32F101R8T6, using the temperature of embedded microprocessor S3C44B0X
Spend sensor and the gas sensor using embedded microprocessor S3C44B0X.
Further, in step 2, the method for the differential threshold of electric signal is calculated according to differential signal are as follows:
The electrical signal data that 300 milliseconds of sensor continuous acquisition, withSample frequency length be averaged to e (n)
It is divided into k sampling interval, calculates the differential threshold of electric signalWherein, fsFor sample frequency, fs
Frequency range is 30~500Hz.
Further, in step 3, the method for the differential threshold of electric signal is calculated according to differential signal are as follows:
Sensor continues to acquire electrical signal data, as e (n) the < th for detecting electrical signal data, startsSampling
The minimum value of search e (n) in frequency length, record minimum value are the position Re (i) in second differnce e (n), i.e. minimum point,
Re (i) is positive set of integers.
Further, in step 4, it removes the noise in the position of minimum point and obtains the side of denoising minimum point position
Method are as follows:
Noise is removed to positive integer collection Re (i), introduces rr (i) and mean (rr), Ime (j) the difference sequence that wherein rr (i) is
Column, mean (rr) indicate the mean value of rr (i), i=1,2 ..., L-1；
If rr (i) >=1.5mean (rr), according to half differential threshold, i.e.,The weight between Re (i) and Re (i+1)
New search minimum point position ought detect electrical signal data as denoising minimum point positionStartThe minimum value of search e (n) in sample frequency length, record minimum value are the position Re (i) in second differnce e (n), that is, are gone
It makes an uproar minimum point position；
If rr (i)≤0.35mean (rr), the big minimum point position of the signal amplitude of selection Re (i) and Re (i+1)
As denoising minimum point position；
Further, in steps of 5, according to the method for the crest value in denoising minimum point position positioning electric signal are as follows:
The minimum min (e) in filtering signal e (n) is found out, if position of the minimum in e filtering signal sequence is Ime (i), i
=1,2 ..., m, m are the sum of local minimum, respectively at Re (i) -4 of the Re (i) -5 of raw electrical signal x (n) and y (n)
Beginning is set to existFor search local maximum as crest value, crest value is before denoising minimum point position in sample frequency length
One sampled point；
Further, in step 6, the method that dynamic adjusts differential threshold are as follows:
Since the collected electric signal of sensor is to carry out segment transmissions by data packet, 300 milliseconds of sensor continuous acquisition
Electrical signal data, withSample frequency length k sampling interval is averagely divided into e (n), carry out according to the following formula
Dynamic adjustment differential threshold,Wherein, e [Re (i)] is that electric signal corresponds to second order difference value；When adopting
When collecting jth segment data, respectively according to formulaThe differential threshold of acquisition
It is th (j) and TH (j) respectively, then adjusts the differential threshold TH (j+1) of+1 segment signal of jth are as follows:
TH (j+1)=0.75 × TH (j)+0.25 × th (j+1).
A kind of sensor weak signal data acquisition device that embodiment of the disclosure provides, is illustrated in figure 2 the disclosure
A kind of sensor weak signal data acquisition device figure, a kind of sensor weak signal data acquisition device of the embodiment include: place
The computer program managing device, memory and storage in the memory and can running on the processor, the processing
Device realizes the step in a kind of above-mentioned sensor weak signal data acquisition Installation practice when executing the computer program.
Described device includes: memory, processor and storage in the memory and can transport on the processor
Capable computer program, the processor execute the computer program and operate in the unit of following device:
Difference processing unit, the electric signal for acquiring sensor carry out difference processing and obtain differential signal；
Threshold computation unit, for calculating the differential threshold of electric signal according to differential signal；
Minimum positioning unit, for positioning second differnce minimum point according to differential threshold；
Minimum denoises unit, and the noise in position for removing minimum point obtains denoising minimum point position；
Wave crest positioning unit, for according to the crest value in denoising minimum point position positioning electric signal；
Threshold adjustment unit, for dynamically adjusting differential threshold.
A kind of sensor weak signal data acquisition device can run on desktop PC, notebook, palm electricity
Brain and cloud server etc. calculate in equipment.A kind of sensor weak signal data acquisition device, the device that can be run can wrap
It includes, but is not limited only to, processor, memory.It will be understood by those skilled in the art that the example is only that a kind of sensor is weak
The example of signal data acquisition device does not constitute the restriction to a kind of sensor weak signal data acquisition device, may include
Components more more or fewer than example perhaps combine certain components or different components, such as the weak letter of a kind of sensor
Number acquisition device can also include input-output equipment, network access equipment, bus etc..
Alleged processor can be central processing unit (Central Processing Unit, CPU), can also be it
His general processor, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng the processor is a kind of control centre of sensor weak signal data acquisition device running gear, is connect using various
Mouthful and connection entirely a kind of sensor weak signal data acquisition device can running gear various pieces.
The memory can be used for storing the computer program and/or module, and the processor is by operation or executes
Computer program in the memory and/or module are stored, and calls the data being stored in memory, described in realization
A kind of various functions of sensor weak signal data acquisition device.The memory can mainly include storing program area and storage number
According to area, wherein storing program area can application program needed for storage program area, at least one function (for example sound plays function
Energy, image player function etc.) etc.；Storage data area can store according to mobile phone use created data (such as audio data,
Phone directory etc.) etc..In addition, memory may include high-speed random access memory, it can also include nonvolatile memory, example
Such as hard disk, memory, plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure
Digital, SD) card, flash card (Flash Card), at least one disk memory, flush memory device or other volatibility are solid
State memory device.
Although the description of the disclosure is quite detailed and especially several embodiments are described, it is not
Any of these details or embodiment or any specific embodiments are intended to be limited to, but should be considered as is by reference to appended
A possibility that claim provides broad sense in view of the prior art for these claims explanation, to effectively cover the disclosure
Preset range.In addition, the disclosure is described with inventor's foreseeable embodiment above, its purpose is to be provided with
Description, and those equivalent modifications that the disclosure can be still represented to the unsubstantiality change of the disclosure still unforeseen at present.
Claims (8)
1. a kind of sensor weak signal data acquisition method, which is characterized in that the described method comprises the following steps:
Step 1, the electric signal of sensor acquisition is subjected to difference processing and obtains differential signal；
Step 2, the differential threshold of electric signal is calculated according to differential signal；
Step 3, second differnce minimum point is positioned according to differential threshold；
Step 4, it removes the noise in the position of minimum point and obtains denoising minimum point position；
Step 5, according to the crest value in denoising minimum point position positioning electric signal；
Step 6, dynamic adjustment differential threshold.
2. a kind of sensor weak signal data acquisition method according to claim 1, which is characterized in that in step 1, will
The electric signal of sensor acquisition carries out the method that difference processing obtains differential signal are as follows:
If the sampled value difference of the electric signal X (n) of sensor acquisition is exported as filtering, difference equation are as follows: y (n)=[X
(n-3)+X(n-2)+X(n-1)+X(n)]/4；The l that y (n), n=1,2 obtained after filtering ..., wherein l is signal length, to y (n)
It carries out single order and second differnce obtains differential signal e (n): d (n)=y (n+1)-y (n), n=1,2 ..., l-1；E (n)=d (n+
1)-d (n), n=1,2 ..., l-2.
3. a kind of sensor weak signal data acquisition method according to claim 1, which is characterized in that in step 2, root
The method of the differential threshold of electric signal is calculated according to differential signal are as follows:
The electrical signal data that 300 milliseconds of sensor continuous acquisition, withSample frequency length e (n) is averagely divided into
K sampling interval calculates the differential threshold of electric signalWherein, fsFor sample frequency, fsFrequency model
It encloses for 30~500Hz.
4. a kind of sensor weak signal data acquisition method according to claim 1, which is characterized in that in step 3, root
The method of the differential threshold of electric signal is calculated according to differential signal are as follows:
Sensor continues to acquire electrical signal data, as e (n) the < th for detecting electrical signal data, startsSample frequency is long
The minimum value of search e (n) in degree, record minimum value are the position Re (i) in second differnce e (n), i.e. minimum point, Re (i) is
Positive integer collection.
5. a kind of sensor weak signal data acquisition method according to claim 1, which is characterized in that in step 4, go
The method for obtaining denoising minimum point position except the noise in the position of minimum point are as follows:
Noise is removed to positive integer collection Re (i), is introduced rr (i) and mean (rr), Ime (j) difference sequence that wherein rr (i) is,
Mean (rr) indicates the mean value of rr (i), i=1,2 ..., L-1；
If rr (i) >=1.5mean (rr), according to half differential threshold, i.e.,It is searched again between Re (i) and Re (i+1)
Rope minimum point position ought detect electrical signal data as denoising minimum point positionStart
The minimum value of search e (n) in sample frequency length, record minimum value are the position Re (i) in second differnce e (n), i.e. denoising pole
Small value point position；
If rr (i)≤0.35mean (rr), the minimum point position that selects the signal amplitude of Re (i) and Re (i+1) big as
Denoise minimum point position.
6. a kind of sensor weak signal data acquisition method according to claim 1, which is characterized in that in steps of 5, press
According to the method for the crest value in denoising minimum point position positioning electric signal are as follows: find out the minimum min in filtering signal e (n)
(e), if position of the minimum in e filtering signal sequence is Ime (i), i=1,2 ..., m, m are the total of local minimum
Number, starts in -4 position Re (i) of the Re (i) -5 of raw electrical signal x (n) and y (n) respectivelyIt is searched in sample frequency length
For rope local maximum as crest value, crest value is the denoising previous sampled point in minimum point position.
7. a kind of sensor weak signal data acquisition method according to claim 1, which is characterized in that in step 6, move
The method of state adjustment differential threshold are as follows:
Since the collected electric signal of sensor is to carry out segment transmissions, the electricity that 300 milliseconds of sensor continuous acquisition by data packet
Signal data, withSample frequency length k sampling interval is averagely divided into e (n), according to the following formula carry out dynamic
Differential threshold is adjusted,Wherein, e [Re (i)] is that electric signal corresponds to second order difference value；When acquisition jth
When segment data, respectively according to formulaThe differential threshold of acquisition is respectively
Th (j) and TH (j), then adjust the differential threshold TH (j+1) of+1 segment signal of jth are as follows:
TH (j+1)=0.75 × TH (j)+0.25 × th (j+1).
8. a kind of sensor weak signal data acquisition device, which is characterized in that described device include: memory, processor and
The computer program that can be run in the memory and on the processor is stored, the processor executes the computer
Program operates in the unit of following device:
Difference processing unit, the electric signal for acquiring sensor carry out difference processing and obtain differential signal；
Threshold computation unit, for calculating the differential threshold of electric signal according to differential signal；
Minimum positioning unit, for positioning second differnce minimum point according to differential threshold；
Minimum denoises unit, and the noise in position for removing minimum point obtains denoising minimum point position；
Wave crest positioning unit, for according to the crest value in denoising minimum point position positioning electric signal；
Threshold adjustment unit, for dynamically adjusting differential threshold.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111767887A (en) * | 2020-07-08 | 2020-10-13 | 吉林大学 | Transient electromagnetic data processing method based on wavelet decomposition and IME frequency estimation |
| CN111938640A (en) * | 2020-08-05 | 2020-11-17 | 深圳大学 | Method and device for positioning point C of cardiac impedance differential signal and storage medium |
| CN112903132A (en) * | 2021-03-05 | 2021-06-04 | 南京交想科技有限公司 | Embedded system-based field information sensor |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102247143A (en) * | 2011-06-03 | 2011-11-23 | 吉林大学珠海学院 | Integratable fast algorithm for denoising electrocardiosignal and identifying QRS waves |
| CN107184203A (en) * | 2017-07-03 | 2017-09-22 | 重庆大学 | Electrocardiosignal Feature point recognition method based on adaptive set empirical mode decomposition |
| US9879630B2 (en) * | 2014-11-19 | 2018-01-30 | Fca Us Llc | Intake oxygen sensor rationality diagnostics |
| CN108537100A (en) * | 2017-11-17 | 2018-09-14 | 吉林大学 | A kind of electrocardiosignal personal identification method and system based on PCA and LDA analyses |
| CN108836305A (en) * | 2018-05-08 | 2018-11-20 | 北京理工大学 | A kind of ECG feature extracting method of fusion Butterworth filtering and wavelet transformation |
-
2018
- 2018-12-24 CN CN201811585522.7A patent/CN109542021A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102247143A (en) * | 2011-06-03 | 2011-11-23 | 吉林大学珠海学院 | Integratable fast algorithm for denoising electrocardiosignal and identifying QRS waves |
| US9879630B2 (en) * | 2014-11-19 | 2018-01-30 | Fca Us Llc | Intake oxygen sensor rationality diagnostics |
| CN107184203A (en) * | 2017-07-03 | 2017-09-22 | 重庆大学 | Electrocardiosignal Feature point recognition method based on adaptive set empirical mode decomposition |
| CN108537100A (en) * | 2017-11-17 | 2018-09-14 | 吉林大学 | A kind of electrocardiosignal personal identification method and system based on PCA and LDA analyses |
| CN108836305A (en) * | 2018-05-08 | 2018-11-20 | 北京理工大学 | A kind of ECG feature extracting method of fusion Butterworth filtering and wavelet transformation |
Non-Patent Citations (1)
| Title |
|---|
| 王洪涛: "人体体表信息特征提取及其算法的研究", 《中国优秀硕士学位论文信息科技辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111767887A (en) * | 2020-07-08 | 2020-10-13 | 吉林大学 | Transient electromagnetic data processing method based on wavelet decomposition and IME frequency estimation |
| CN111767887B (en) * | 2020-07-08 | 2022-06-28 | 吉林大学 | Transient electromagnetic data processing method based on wavelet decomposition and IME frequency estimation |
| CN111938640A (en) * | 2020-08-05 | 2020-11-17 | 深圳大学 | Method and device for positioning point C of cardiac impedance differential signal and storage medium |
| CN111938640B (en) * | 2020-08-05 | 2023-02-07 | 深圳大学 | Method and device for positioning point C of cardiac impedance differential signal and storage medium |
| CN112903132A (en) * | 2021-03-05 | 2021-06-04 | 南京交想科技有限公司 | Embedded system-based field information sensor |
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