CN109363658A - A kind of breathing based on interference of light principle and heartbeat signal extracting method - Google Patents
A kind of breathing based on interference of light principle and heartbeat signal extracting method Download PDFInfo
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- CN109363658A CN109363658A CN201811137374.2A CN201811137374A CN109363658A CN 109363658 A CN109363658 A CN 109363658A CN 201811137374 A CN201811137374 A CN 201811137374A CN 109363658 A CN109363658 A CN 109363658A
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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
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
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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
- A61B5/72—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
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
Abstract
The present invention is about a kind of breathing of wisdom mattress system and heartbeat signal extracting method based on interference of light principle, using wisdom mattress system interference light intensity signal as process object, utilize Short Time Fourier Transform and WAVELET PACKET DECOMPOSITION and reconstruct, it extracts the instantaneous frequency change information of original light intensity signal and other physiological noise signals in extraneous and human body is separated, to extract authentic and valid breath signal and heartbeat signal.This method for extracting signal can not only remove ambient noise and the influence with other physiological signals similar in heartbeat respiratory rate, guarantee the correctness of calculating heartbeat breath signal frequency, and the processing difficulty of non-phase demodulation mode can be effectively reduced, system cost is reduced, can satisfy major application demand of the interference of light type optical fiber sensing in terms of vital sign monitoring.
Description
Technical field
The present invention relates to human life features to monitor field, more particularly, to a kind of wisdom based on interference of light principle
Mattress system breathing and heartbeat signal extracting method.
Background technique
With the raising of social senilization's problem got worse with medical treatment cost, nowadays, be directed to Empty nest elderly or
The vital sign index of bedfast patient such as breathes, heartbeat real-time monitoring have become the hot issue studied both at home and abroad it
One.According to statistics, the disease incidence of sleep disordered breathing accounts for about the 10-20% of entire crowd, and elderly population is up to 40-60% how
The sleep state of monitor patient, and foundation is provided for the early diagnosis of sleep disturbance related disease, increasingly cause people
Pay attention to.Currently, existing photoplethaysmography mode monitors human body physiological characteristics signal, which mostly uses wearable device city
, but prolonged wearing will affect human body comfort.It is exhaled in the market there are also a kind of using piezoelectric transducer monitoring human body
The device piezoelectric material of suction rate and heart rate needs moisture preventive measure, and the DC response exported is poor, over time the biography
Sensor deterioration of sensitivity.
Compared to both the above sensor, the sensor-based system based on interference of light principle has high sensitivity, comfort good, clever
The feature that sensitivity is high, accuracy is strong, but the signal that interference system obtains at present needs to will lead to system in this way by phase demodulating
Cost is excessively high, demodulation method is complicated.Meanwhile having mixed other low frequency physiological signals outside ambient noise in interference signal, it is existing
Method for extracting signal can not extract complete breathing and heartbeat signal well.
Summary of the invention
Aiming at the above defects or improvement requirements of the prior art, the present invention provides a kind of exhaling applied to interference of light system
It inhales and is solving the problems, such as that interference of light system hardware is at high cost, demodulation method is complicated with heartbeat signal extracting method, purpose.
The technical solution that the present invention takes to achieve the above object are as follows:
A kind of breathing based on interference of light principle and heartbeat signal extracting method, the extracting method the following steps are included:
1, low-pass filtering is carried out to original signal, removes high-frequency noise caused by environment；
2, Short Time Fourier Transform is carried out to the signal after low-pass filtering, extract breath signal waveform and it is carried out smoothly
Filtering processing；
3, the frequency spectrum of breath signal after smothing filtering is calculated, the peak-seeking within the scope of certain frequency obtains the frequency of breathing；
4, bandpass filtering is carried out to original signal, removes high-frequency noise caused by environment and filtering appts and human body introduces
Low-frequency fluctuation；
5, Multiscale Wavelet Decomposition is carried out for the signal after bandpass filtering, selection weight is carried out to multi-scale wavelet component
Group；
6, to the signal extraction envelope after recombination, and envelope frequency spectrum is calculated, peak-seeking and obtains the heart in frequency domain a certain range
Frequency hopping rate；
It is preferred that original signal is the light intensity signal that intensity demodulation generates in the step 1, rather than the resulting phase of phase demodulating
Position signal.
It is preferred that the low-pass filter used in the step 1 is window function for the Butterworth filter of Blackman window,
Cutoff frequency is 45HZ, not only removes high-frequency noise caused by environment, additionally it is possible to filter out the power frequency component of 50HZ.
It is preferred that the window function that Short Time Fourier Transform uses is hamming window, window a length of 200, adjacent two partition windows overlapping is counted
It is 10.
It is preferred that smothing filtering uses Gaussian window method, window width is set as 100, standard deviation 100.
It is preferred that the step 3 frequency domain peak-seeking range is 0.1HZ-3HZ, take the frequency values of peak point as the frequency of breathing
Rate.
It is preferred that the bandpass filter used is window function for the Chebyshev filter of Hanning window, low-frequency cut-off frequency is
4HZ, high-frequency cut-off frequency are 45HZ, filter out low-frequency fluctuation, power frequency component and high frequency environment noise.
It is preferred that 4 layers of decomposition are carried out to it based on db5 wavelet function, are obtained using the signal of bandpass filter output as object
Wavelet coefficient cA1, cD1, cA2, cD2, cA3, cD3, cA4, cD4 of different frequency bands, wherein cA1, cA2, cA3, cA4 are respectively small
For Wave Decomposition to first layer, the second layer, third layer, the 4th layer of low frequency coefficient, cD1, cD2, cD3, cD4 are respectively that wavelet decomposition arrives
First layer, the second layer, third layer, the 4th layer of high frequency coefficient, for reconstruction signal wavelet coefficient be cA4, cD1, cD2,
CD3, cD4 carry out selective processing and carry out wavelet reconstruction to obtain heartbeat signal, small echo to the wavelet coefficient for reconstruction signal
Coefficient cD1 and cA4 zero setting, removal high-frequency noise, system dc fluctuation and the other low frequency physiological signals of human body.
It is preferred that extracting the coenvelope signal of reconstruction signal using Hilbert transform, and coenvelope signal is carried out in Fu
Leaf transformation calculates frequency spectrum.
It is preferred that frequency domain heartbeat peak-seeking range is set as 0.5HZ-2HZ, take the frequency values of peak point as the frequency of heartbeat.
In general, through the invention it is contemplated above technical scheme is compared with the prior art, can obtain down and show
Beneficial effect:
1, present invention reduces the sensing system hardware costs based on interference of light principle.
2, compared with conventional interference system signal processing method, the present invention does not need to carry out subsequent signal phase demodulation.
3, method for extracting signal structure of the present invention is simple, is easy to software programming, advantageously reduces human cost.
4, the present invention can not only filter out extraneous ambient noise, additionally it is possible to which drop breathing and heartbeat signal are raw with other low frequencies
Reason signal distinguishing comes.
Detailed description of the invention
Fig. 1 is the sensor-based system figure of optical interference structures of the invention.
Fig. 2 is breathing and heartbeat extracting method flow chart of the invention.
Fig. 3 is Wavelet decomposing and recomposing flow chart of the invention
Fig. 4 is original signal figure of the invention.
Fig. 5 is the breath signal that the present invention extracts.
Fig. 6 is the heartbeat signal after wavelet reconstruction of the present invention.
Specific embodiment
A specific embodiment of the invention is made a detailed explanation with reference to the accompanying drawing.
Referring to Fig. 1, the sensor-based system based on optical interference structures is there are two chief component, system terminal, sensitive mattress,
System terminal is made of Distributed Feedback Laser, coupler, reference optical fiber, PD (photodetector), signal pickup assembly, FPGA, sensing
Mattress is made of silica gel protective pad, sensor fibre.The narrow-linewidth laser that wavelength is 1550nm is issued by Distributed Feedback Laser in the present invention
Reference optical fiber and sensor fibre are respectively enterd by coupler, by the phase of sensor fibre transmission optical signal because of human body respiration
With micro-vibration caused by signal and generate variation, sensor fibre output optical signal and reference optical fiber output optical signal through system
Coupler in terminal and generate interference signal, the light intensity signal of interference is detected and acquired by acquisition device by PD, in FPGA
It is process object with light intensity signal, to extract breathing and heartbeat signal and calculate its frequency.
As shown in Fig. 2, it includes following that the wisdom mattress system based on interference of light principle, which is breathed with heartbeat signal extracting method,
Step:
(1) interference light intensity signal is original signal, and low-pass filtering is carried out to it, removes high-frequency noise and work caused by environment
Frequency signal, and the cutoff frequency of low-pass filter is chosen within the scope of 10-100HZ according to actual signal feature.
(2) Short Time Fourier Transform is carried out to the signal after low-pass filtering, extract breath signal waveform and it is carried out flat
Sliding filtering processing.Window function, the window of Short Time Fourier Transform use are long, overlapping points are chosen all in accordance with actual signal feature, window
Long selection range is 20-200, and overlapping points range of choice is 1-200.Smothing filtering algorithm can be selected according to signal actual features
Mean filter, median filtering, gaussian filtering, bilateral filtering are one of.
(3) frequency spectrum of breath signal after smothing filtering is calculated, the peak-seeking within the scope of certain frequency obtains the frequency of breathing.
Wherein, frequency domain peak-seeking range is 0.05HZ-5HZ, takes the frequency values of peak point as the frequency of breathing.
(4) bandpass filtering is carried out to original signal, removes high-frequency noise caused by environment and filtering appts draws with human body
The low-frequency fluctuation entered.The bandpass filter of use is Chebyshev filter, and according to signal actual features, low-frequency cut-off frequency exists
It is selected within the scope of 4-15HZ, high-frequency cut-off frequency selects within the scope of 35HZ-200HZ.
(5) Multiscale Wavelet Decomposition is carried out for the signal after bandpass filtering, selection weight is carried out to multi-scale wavelet component
Group.
(6) to the signal extraction envelope after recombination, and envelope frequency spectrum is calculated, peak-seeking and obtains the heart in frequency domain a certain range
Frequency hopping rate.Wherein, the method for extracting the coenvelope signal use of reconstruction signal is Hilbert transform, frequency domain heartbeat peak-seeking range
It is set as 0.5HZ-3HZ, takes the frequency values of peak point as the frequency of heartbeat.
The detailed process of Wavelet decomposing and recomposing is as shown in figure 3, for the signal after bandpass filtering to be based on db5 wavelet function
4 layers of decomposition are carried out to it, obtain wavelet coefficient cA1, cD1, cA2, cD2, cA3, cD3, cA4, cD4 of different frequency bands, wherein
CA1, cA2, cA3, cA4 are respectively wavelet decomposition to first layer, the second layer, third layer, the 4th layer of low frequency coefficient, cD1, cD2,
CD3, cD4 are respectively wavelet decomposition to first layer, the second layer, third layer, the 4th layer of high frequency coefficient, cA4, cD1, cD2, cD3,
CD4 is the wavelet coefficient for reconstruction signal.The peak-to-average force ratio of wavelet coefficient cD2, cD3 are calculated, the threshold value of cD2, cD3 are according to its peak
Depending on the size of ratio.When peak-to-average force ratio is greater than 5, corresponding wavelet coefficient threshold is 0.1 times of wavelet coefficient maximum value；Peak is equal
When than less than 5, corresponding wavelet coefficient threshold is 0.8 times of wavelet coefficient maximum value.By wavelet coefficient cA4, cD1 zero setting,
Absolute value is lower than the numerical value zero setting of corresponding threshold value in cD2, cD3, and the numerical value that absolute value is higher than corresponding threshold value remains unchanged, and utilizes
Treated, and wavelet coefficient cA4, cD1, cD2, cD3, cD4 carry out signal reconstruction.
Interference light intensity signal is original signal, such as Fig. 4；Low-pass filter is Blackman window using window function
Butterworth filter, cutoff frequency 45HZ；The window function that Short Time Fourier Transform uses is hamming window, window a length of 200, phase
Adjacent two partition windows overlapping points are 10, obtain breath signal, such as Fig. 5 using Short Time Fourier Transform；Smothing filtering uses Gaussian window
Method, window width are set as 100, standard deviation 100；Frequency domain peak-seeking range is 0.1HZ-3HZ, takes the frequency values of peak point as breathing
Frequency.
Bandpass filter uses window function for the Chebyshev filter of Hanning window, and low-frequency cut-off frequency is set as 4HZ, high
Frequency cutoff frequency is 45HZ；The signal that wavelet decomposition is exported using bandpass filter carries out it as object, based on db5 wavelet function
4 layers decomposition, obtain wavelet coefficient cA1, cD1, cA2, cD2, cA3, cD3, cA4, cD4 of different frequency bands, wherein cA1, cA2,
CA3, cA4 are respectively wavelet decomposition to first layer, the second layer, third layer, the 4th layer of low frequency coefficient, cD1, cD2, cD3, cD4
Respectively wavelet decomposition is to first layer, the second layer, third layer, the 4th layer of high frequency coefficient；Wavelet coefficient cD1 and cA4 zero setting, benefit
Signal reconstruction, which is carried out, with treated wavelet coefficient cA4, cD1, cD2, cD3, cD4 obtains heartbeat signal, such as Fig. 6；Utilize Xi Er
Bert transformation extracts the coenvelope signal of reconstruction signal and calculates envelope frequency spectrum, and frequency domain heartbeat peak-seeking range is set as 0.5HZ-
2HZ takes the frequency values of peak point as the frequency of heartbeat.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all include
Within protection scope of the present invention.
Claims (10)
1. a kind of breathing based on interference of light principle and heartbeat signal extracting method, with the collected interference light intensity of acquisition device
For original signal, which is characterized in that the extracting method the following steps are included:
(1) low-pass filtering is carried out to original signal, removes high-frequency noise caused by environment；
(2) Short Time Fourier Transform is carried out to the signal after low-pass filtering, extract breath signal waveform and it is smoothly filtered
Wave processing；
(3) frequency spectrum of breath signal after smothing filtering is calculated, the peak-seeking within the scope of certain frequency obtains the frequency of breathing；
(4) bandpass filtering is carried out to original signal, removes what high-frequency noise caused by environment and filtering appts were introduced with human body
Low-frequency fluctuation；
(5) Multiscale Wavelet Decomposition is carried out for the signal after bandpass filtering, selection recombination is carried out to multi-scale wavelet component；
(6) to the signal extraction envelope after recombination, and calculate envelope frequency spectrum, in frequency domain a certain range peak-seeking and obtain heartbeat frequency
Rate.
2. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: described
Original signal is the light intensity signal that intensity demodulation generates in step (1), rather than the resulting phase signal of phase demodulating.
3. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: described
The low-pass filter used in step (1) is window function for the Butterworth filter of Blackman window, cutoff frequency 45HZ,
Not only remove high-frequency noise caused by environment, additionally it is possible to filter out the power frequency component of 50HZ.
4. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: in short-term
The window function that Fourier transformation uses is hamming window, window a length of 200, and adjacent two partition windows overlapping points are 10.
5. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: smooth
Filtering uses Gaussian window method, and window width is set as 100, standard deviation 100.
6. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: described
Step (3) frequency domain peak-seeking range is 0.1HZ-3HZ, takes the frequency values of peak point as the frequency of breathing.
7. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: use
Bandpass filter be Chebyshev filter that window function is Hanning window, low-frequency cut-off frequency 4HZ, high-frequency cut-off frequency is
45HZ filters out low-frequency fluctuation, power frequency component and high frequency environment noise.
8. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: with band
The signal of bandpass filter output is object, carries out 4 layers of decomposition to it based on db5 wavelet function, obtains the wavelet systems of different frequency bands
Number cA1, cD1, cA2, cD2, cA3, cD3, cA4, cD4, wherein cA1, cA2, cA3, cA4 be respectively wavelet decomposition to first layer,
The second layer, third layer, the 4th layer of low frequency coefficient, cD1, cD2, cD3, cD4 be respectively wavelet decomposition to first layer, the second layer,
Third layer, the 4th layer of high frequency coefficient, the wavelet coefficient for reconstruction signal is cA4, cD1, cD2, cD3, cD4, to for weight
The wavelet coefficient of structure signal carries out selective processing and carries out wavelet reconstruction obtaining heartbeat signal, and wavelet coefficient cD1 and cA4 is set
Zero, removal high-frequency noise, system dc fluctuation and the other low frequency physiological signals of human body.
9. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle, it is characterised in that: utilize
The coenvelope signal of reconstruction signal is extracted in Hilbert transform, and carries out Fourier transformation to coenvelope signal and calculate frequency spectrum.
10. breathing and heartbeat signal extracting method as described in claim 1 based on interference of light principle: it is characterized in that, frequency
Heartbeat peak-seeking range in domain is set as 0.5HZ-2HZ, takes the frequency values of peak point as the frequency of heartbeat.
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