CN104581516A - Dual-microphone noise reduction method and device for medical acoustic signals - Google Patents
Dual-microphone noise reduction method and device for medical acoustic signals Download PDFInfo
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Abstract
The invention discloses a dual-microphone noise reduction method and device applied to medical acoustic signals such as heart and lung sounds, fetal heart sounds and the like. The dual-microphone noise reduction method for the medical acoustic signals comprises steps as follows: acquiring medical acoustic signal data with noises and ambient noise data, and processing the medical acoustic signal data and the ambient noise data respectively to obtain a time-frequency unit; calculating a characteristic value for the time-frequency unit; generating a masking value according to the relation between the characteristic value and a masking threshold, and marking a part, which mainly comprises the medical acoustic signals, of the time-frequency unit; masking the time-frequency unit of the medical acoustic signal data with the noises according to the generated masking value, reserving the part which mainly comprises the medical acoustic signals, and reconstructing the masked data to obtain a noise reduction result. According to the noise reduction method, the medical acoustic signals with the noises and ambient noises are acquired respectively by the aid of dual microphones, and the medical acoustic signals and the ambient noises are effectively separated.
Description
Technical field
The present invention relates to the digital processing field of medicine equipment, particularly a kind of dual microphone noise-eliminating method of medical science acoustical signal and device.
Background technology
Angiocardiopathy and respiratory disease are common disease and the frequently-occurring disease of harm humans health, along with the enhancing of people's health-care hospital consciousness, bring the demand for cardiovascular fitness monitoring.
Electrocardiogram, echocardiogram, auscultation etc. is had to heart disease Common Diagnostic Methods.The electrical activity characteristic of electrocardiogram reflection heart, can be used for differentiating arrhythmia cordis, atrial ventricle's functional defect.But electrocardiogram is not associated with ventricular contraction and diastole accurately, can not conclude that cardiac function is normal completely by normal electrocardiogram.Echocardiogram produces high frequency sound wave pulse, utilizes echo to locate and study motion and the tangent plane of various cardiac structure.Ultrasonic wave has certain thermal effect and acoustic effect to tissue, may there is potential hazard to health.The inspection method that respiratory disease uses has imaging examination of chest, bronchoscope, auscultation etc.Imaging examination of chest can well show lung lesion situation, and bronchoscope stretches into bronchus can directly spy on tracheal strips situation, and the two has important application on clinical treatment.Auscultation is as a kind of method simple to operate, and hurtless measure and have good comfort level, has applicability at large in clinical treatment and health care.
Heart and lung sounds is detected as the passive type monitoring method based on auscultation, record heart and lung sounds, simple to operate and without wound.More preferably, hear sounds detects can be early stage in angiocardiopathy, and electrocardiogram does not show extremely, is diagnosed by the noise occurred in hear sounds, takes corresponding remedy measures as early as possible; Apnea phenomenon when lungs sound monitoring can record sleep, the bronchial spasm of asthmatic patient, and supplemental treatment.
Heart disease easily brings out in nervous, physical exertion, smoking, the situation such as to drink, and cardiechema signals is nonstationary random process, only have stable statistical property at short notice, this makes cannot guarantee Accurate Diagnosis disease in the process of examination in hospital.By portable monitoring system, gather cardiechema signals whenever and wherever possible, facilitate data record and reproduction, to health care, assist medical diagnosis to do a great deal of good.
Lung Sounds shows as nonstationary random process equally, and within the hospital, after lungs sound auscultation is applied to intensive care unit monitor patients breath state, operating room Monitored anesthesia, patient lung changes; In daily use, may be used for apnea when recording sleep, the bronchial spasm of asthmatic patient.Therefore, adopt portable monitoring system, gather Lung Sounds whenever and wherever possible, have great help to medical treatment, health care.
Another application background is that fetal heart sound detects.At pregnant woman's period of gestation, especially conceived middle and advanced stage, guards the indices of fetus, can understand fetus health status in uterus, find the exception of fetus early.Monitoring fetal rhythm is mainly in order to obtain the real-time heart rate of fetus, and whether fetal heart frequency is normal, is the important indicator judging fetus whether anoxic in parent.Therefore fetal rhythm monitoring is the big event checked in the pregnancy period.The conventional Doppler ultrasonography on monitoring of fetal heart sound monitoring, uses and can launch hyperacoustic probe, and to heart of fetus position transmitting ultrasonic wave, ultrasonic wave runs into the heart of beating and produces echo, utilizes Doppler effect to calculate echo-signal, obtains fetal heart frequency.Doppler ultrasonography on monitoring can initiatively be launched ultrasonic wave and detect, and effectively can detect the faint heartbeat of fetus, analyzes accuracy rate high.But ultrasonic wave may have potential hazard to foetus health, ultrasonic wave dosage needs strict test and monitoring.
And based on the passive type monitoring method of auscultation, fetal well-being be can't harm.Acoustic sensor is used to collect the monitoring system of the voice signal of parent abdominal surface, simple to operate without wound.Pregnant woman and family members can use portable monitoring system, gather fetal heart sound data at any time, and shake rails hear sounds is to reappear and medical assistance.
In typical medical science acoustical signal monitoring system, while voice collection device monitoring medical science acoustical signal, also collect ambient noise around.Ambient noise has had a strong impact on the signal quality collected, and is unfavorable for physiology and the pathological diagnosis in later stage.
In clinical, auscultation needs medical personnel by prolonged exercise, and accumulation clinical experience, to distinguish noise and useful medical science acoustical signal.The frequency of medical science acoustical signal is all lower, as: the frequency range of hear sounds is at below 1kHz, and lungs sound frequency range is at 60 ~ 1000Hz, and fetal heart sound frequency is mainly within 170Hz, and the best audibility range of people is at 1k ~ 2kHz, this makes the medical science acoustical signal of low frequency not easily hear.Meanwhile, medical science acoustical signal is faint, easily by noise takeover.These all cause auscultation to be easy to be subject to the impact of ambient noise, the auscultation environment needed peace and quiet.In medical science acoustical signal monitoring system, medical science acoustical signal, can the method for Applied Digital signal transacting after amplifying, gather, storing, and carries out noise elimination to the signal collected, the requirement of auscultation environment is reduced greatly, conveniently detects health status whenever and wherever possible.
In the noise-eliminating method of medical science acoustical signal, common method has directly employing low pass filter filter out-band external noise, spectrum-subtraction and sef-adapting filter.Low pass filter is the simplest, but cannot eliminate logical in-band noise.Spectrum-subtraction uses Short Time Fourier Transform, and algorithm is more complicated than low pass filter, uses spectrum-subtraction can produce stronger music noise.Sef-adapting filter is most widely used general, but there is the compromise problem of convergence time and precision.
Summary of the invention
(1) technical problem that will solve
The technical problem to be solved in the present invention is: for the interference of ambient noise in medical science acoustical signal monitoring system, how to realize a kind of noise-eliminating method and device of effective elimination ambient noise.
(2) technical scheme
For solving the problem, the invention provides a kind of dual microphone noise-eliminating method of medical science acoustical signal, comprise: the medical science acoustical signal data and the environmental noise data that obtain band noise, process respectively described medical science acoustical signal data and described environmental noise data, obtain time frequency unit; To described time frequency unit computation of characteristic values; According to the relation of described characteristic value and masking threshold, generate masking value, marking described time frequency unit traditional Chinese medicine acoustical signal is main part; The time frequency unit of masking value to the acoustical signal data of described band noise according to generating is sheltered, and retaining medical science acoustical signal is main part, is reconstructed the data after sheltering, and obtains de-noising result.
Preferably, the acoustical signal data of noise are with to be obtained by the acoustic sensor being in body surface placement.
Preferably, described acoustical signal data and described environmental noise data are divided subband, and temporally time division frame, obtain described time frequency unit.
Preferably, also comprising: according to human hearing characteristic, use the bank of filters of uneven division subband, is the subband exponentially distributed by frequency band division, and the high frequency relative coarseness to the careful of low frequency division, can be conducive to differentiating low-frequency sound;
Preferably, also comprise: according to auditory properties and the auscultation needs of people's ear, filtering is carried out to the dual microphone data obtained, the data in scheduled frequency range are strengthened.
Preferably, described computation of characteristic values is the energy Ratios of described dual microphone data time frequency unit.
Preferably, also comprise: to the smoothing process of described masking value, make de-noising result keep continuity in time domain.
Preferably, the data after described sheltering temporally are superposed each time frame, superpose each subband, obtain de-noising result.
The present invention also provides a kind of dual microphone noise cancellation apparatus of acoustical signal, comprise: peripheral analysis module, for obtaining medical science acoustical signal data and the environmental noise data of band noise, described medical science acoustical signal data and described environmental noise data being processed respectively, obtains time frequency unit; Characteristic extracting module, for described time frequency unit computation of characteristic values; Shelter separation module, for the relation according to described characteristic value and masking threshold, generate masking value, marking acoustical signal in described time frequency unit is main part; Signal reconstruction module, for sheltering according to the time frequency unit of masking value to the medical science acoustical signal data of described band noise generated, retaining medical science acoustical signal is main part, is reconstructed the data after sheltering, and obtains de-noising result.
Preferably, described peripheral analysis module also comprises signal and strengthens module, for according to the auditory properties of people's ear and auscultation needs, carries out filtering, strengthen the data in scheduled frequency range the dual microphone data obtained.
Preferably, described in shelter separation module and also comprise Leveling Block, for the smoothing process of described masking value, make de-noising result keep continuity in time domain.
(3) beneficial effect
The noise-eliminating method that the present invention proposes, adopts dual microphone to gather medical science acoustical signal and the ambient noise of band noise respectively, effectively medical science acoustical signal is separated with ambient noise.Use this method, measured can carry out adult's heart and lung sounds, fetal heart sound monitoring whenever and wherever possible, carries out denoising Processing, for health care provides reference to the data obtained.
Accompanying drawing explanation
Fig. 1 is the dual microphone noise-eliminating method schematic flow sheet according to one embodiment of the present invention;
Fig. 2 is the dual microphone structural representation according to one embodiment of the present invention;
Fig. 3 is the dual microphone noise-eliminating method schematic flow sheet of the optimization according to one embodiment of the present invention;
Fig. 4 is the schematic diagram of one of them subband data after the division subband according to one embodiment of the present invention;
Fig. 5 is the schematic diagram of the characteristic value result of calculation according to one embodiment of the present invention;
Fig. 6 is the effect schematic diagram of the level and smooth front and back of masking value according to one embodiment of the present invention.
Embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples for illustration of the present invention, but are not used for limiting the scope of the invention.
As shown in Figure 1, dual microphone noise-eliminating method provided by the invention, comprises peripheral analysis, feature extraction, shelters separation and signal reconstruction four parts.
Wherein, described periphery is analyzed, and obtain medical science acoustical signal data and the environmental noise data of band noise, process two groups of data respectively, acquired results is time frequency unit, for feature extraction and signal reconstruction;
Described feature extraction, to described time frequency unit computation of characteristic values, for sheltering separation;
Describedly shelter separation, according to the relation of described characteristic value and masking threshold, generate masking value, marking described time frequency unit traditional Chinese medicine acoustical signal is main part, for signal reconstruction;
Described signal reconstruction, the time frequency unit of masking value to the medical science acoustical signal data of described band noise according to generating is sheltered, and retaining medical science acoustical signal is main part, is reconstructed the data after sheltering, and obtains de-noising result.
For the medical science voice data with noise described in guarantee Obtaining Accurate and described environmental noise data, require that the medical science acoustical signal data of band noise are obtained by the acoustic sensor 1 that is close to body surface placement: when being close to the placement of adult's wall of the chest, obtain adult's heart and lung sounds data of band noise; When being close to her abdominal placement, obtain the fetal heart sound data of band noise; The acoustic sensor 2 that environmental noise data is not close to human body by another obtains.In the present embodiment, this is close to the acoustic sensor 1 that body surface places and the acoustic sensor 2 not being close to human body can be all microphone.
Wherein, when described periphery is analyzed, by Data Placement subband, and temporally time division frame, obtain described time frequency unit.
Wherein, described periphery is analyzed and is also comprised signal enhancement unit further, according to auditory properties and the auscultation needs of people's ear, carries out filtering, strengthen the data in particular frequency range the dual microphone data obtained.
Wherein, described feature extraction, computation of characteristic values is the energy Ratios of described dual microphone Data Placement time frequency unit.
Wherein, shelter separation and also comprise smooth unit, for the smoothing process of described masking value, ensure the continuity in de-noising result time domain.
Wherein, the data after described sheltering temporally are superposed each time frame by described signal reconstruction, superpose each subband by frequency, obtain de-noising result.
The present invention can be applied to cardiophony according to dual microphone structure as shown in Figure 2, obtains heart sound data and the environmental noise data of band noise.
The present invention's noise-eliminating method below obtains de-noising result, as shown in Figure 3, is the flow chart of the dual microphone noise-eliminating method of optimization.
S1, according to human hearing characteristic and auscultation needs, respectively the band heart sound data of noise and environmental noise data to be strengthened;
Because the sound of people's ear to 1k ~ 2kHz is more responsive, the hear sounds being in below 1kHz is made to be not easy to hear, utilize contour of equal loudness can obtain the gain compensation value of corresponding a certain frequency, by gain compensation value, data are strengthened, the sound hearing low frequency can be conducive to;
S2, respectively to enhancing after signal bank of filters filtering, divide subband;
The bank of filters dividing subband can select the mode of evenly division, also can select the mode of uneven division, adopt the mode of uneven division subband in embodiment;
Basilar memebrane due to the cochlea of people's ear has the characteristic of similar spectrum analyzer, the sound of different frequency causes the vibration of basilar memebrane diverse location, and frequency along the position that basilar memebrane distributes be uneven, exponentially distribute, make people's ear different to the sound sensitive degree of different frequency.Using the bank of filters of uneven division subband, is the subband exponentially distributed by frequency band division, and the high frequency relative coarseness to the careful of low frequency division, can be conducive to differentiating low-frequency sound;
Fig. 4 is the filter result schematic diagram of one of them filter;
S3, to the data in each subband, carry out overlapping framing, obtain time frequency unit;
Overlapping framing makes to seamlessly transit between frame and frame, and time domain keeps continuity;
S4, calculate the energy of each time frequency unit, calculate the energy ratio of time frequency unit corresponding to the n-th subband t time frame of band noise cardiechema signals and ambient noise one by one, obtain characteristic value;
Fig. 5 is the characteristic value result of calculation schematic diagram of one of them subband;
S5, compared with masking threshold by characteristic value, determine masking value size, masking threshold is the piecewise function of subband, selects many-valued sheltering can obtain good de-noising effect;
S6, to the smoothing process of masking value.Because masking value is discrete value, adjacent time frame may the masking value of corresponding different size.After masking value weighting, the masking value of sudden change can make the data of adjacent time frame discontinuous, thus introduces high-frequency noise;
Smoothing processing improves the sudden change of masking value, improves temporal continuity, and Fig. 6 is the effect schematic diagram of the level and smooth front and back of masking value;
S7, the time frequency unit that band noise heart sound data is corresponding, through masking value weighting, the time frame of each subband carries out frame respectively and folds;
Owing to have employed overlapping framing mode, need when frame is folded first to use window function process to each frame data, then frame is carried out respectively to each subband fold, obtain the frame poststack data seamlessly transitted;
The frame poststack data of S8, each subband, through bank of filters filtering, obtain each subband data that time domain can directly superpose;
Owing to have employed the filter of uneven division subband when dividing subband, the delay on free between each subband data, shows as the difference of phase place in a frequency domain.The frame poststack data of each subband need device group filtering after filtering, eliminate the time delay between each subband, eliminate phase difference, obtain each subband data that time domain can directly superpose;
S9, each subband data temporally to be superposed, obtain de-noising result.
The present invention also provides a kind of dual microphone noise cancellation apparatus, comprises peripheral analysis, feature extraction, shelters separation and signal reconstruction four modules.
Wherein, described peripheral analysis module, obtain medical science acoustical signal data and the environmental noise data of band noise, process two groups of data respectively, acquired results is time frequency unit, for feature extraction and signal reconstruction;
Described characteristic extracting module, to described time frequency unit computation of characteristic values, for sheltering separation;
Describedly shelter separation module, according to the relation of described characteristic value and masking threshold, generate masking value, marking described time frequency unit traditional Chinese medicine acoustical signal number is main part, for signal reconstruction;
Described signal reconstruction module, the time frequency unit of masking value to the medical science acoustical signal data of described band noise according to generating is sheltered, and retaining medical science acoustical signal is main part, is reconstructed the data after sheltering, and obtains de-noising result.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the prerequisite not departing from the technology of the present invention principle; can also make some improvement and replacement, these improve and replace and also should be considered as protection scope of the present invention.
Claims (10)
1. a dual microphone noise-eliminating method for medical science acoustical signal, is characterized in that, comprising:
Obtain medical science acoustical signal data and the environmental noise data of band noise, described medical science acoustical signal data and described environmental noise data are processed respectively, obtains time frequency unit;
To described time frequency unit computation of characteristic values;
According to the relation of described characteristic value and masking threshold, generate masking value, marking described time frequency unit traditional Chinese medicine acoustical signal is main part;
The time frequency unit of masking value to the medical science acoustical signal data of described band noise according to generating is sheltered, and retaining medical science acoustical signal is main part, is reconstructed the data after sheltering, and obtains de-noising result.
2. the method for claim 1, is characterized in that, the medical science acoustical signal data of band noise are obtained by the acoustic sensor being in body surface placement.
3. method as claimed in claim 1 or 2, is characterized in that, described medical science acoustical signal data and described environmental noise data are divided subband, and temporally time division frame, obtain described time frequency unit.
4. method as claimed in claim 3, is characterized in that, also comprise:
According to auditory properties and the auscultation needs of people's ear, filtering is carried out to the dual microphone data obtained, the data in scheduled frequency range are strengthened.
5. method as claimed in claim 1 or 2, it is characterized in that, described computation of characteristic values is the energy Ratios of described dual microphone data time frequency unit.
6. method as claimed in claim 1 or 2, is characterized in that, also comprise:
To the smoothing process of described masking value, de-noising result is made to keep continuity in time domain.
7. method as claimed in claim 1 or 2, is characterized in that, the data after described sheltering temporally are superposed each time frame, superpose each subband, obtain de-noising result.
8. a dual microphone noise cancellation apparatus for medical science acoustical signal, is characterized in that, comprising:
Peripheral analysis module, for obtaining medical science acoustical signal data and the environmental noise data of band noise, processing respectively described medical science acoustical signal data and described environmental noise data, obtaining time frequency unit;
Characteristic extracting module, for described time frequency unit computation of characteristic values;
Shelter separation module, for the relation according to described characteristic value and masking threshold, generate masking value, marking acoustical signal in described time frequency unit is main part;
Signal reconstruction module, for sheltering according to the time frequency unit of masking value to the medical science acoustical signal data of described band noise generated, retaining medical science acoustical signal is main part, is reconstructed the data after sheltering, and obtains de-noising result.
9. device as claimed in claim 8, it is characterized in that, described peripheral analysis module also comprises signal and strengthens module, for according to the auditory properties of people's ear and auscultation needs, filtering is carried out to the dual microphone data obtained, the data in scheduled frequency range are strengthened.
10. as claimed in claim 8 or 9 device, is characterized in that, described in shelter separation module and also comprise Leveling Block, for the smoothing process of described masking value, make de-noising result keep continuity in time domain.
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| CN113763985A (en) * | 2021-10-15 | 2021-12-07 | 广州蓝仕威克医疗科技有限公司 | Device based on sound identification physiology phenomenon |
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