CN201641998U - Gastric electrical slow-wave signal detection device based on RLS self-adapting filter - Google Patents
Gastric electrical slow-wave signal detection device based on RLS self-adapting filter Download PDFInfo
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- CN201641998U CN201641998U CN2009202882171U CN200920288217U CN201641998U CN 201641998 U CN201641998 U CN 201641998U CN 2009202882171 U CN2009202882171 U CN 2009202882171U CN 200920288217 U CN200920288217 U CN 200920288217U CN 201641998 U CN201641998 U CN 201641998U
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Abstract
The utility model discloses a gastric electrical slow-wave signal detection device based on an RLS (Recursive Least Square) self-adapting filter, comprising a hardware part and a software processing part, wherein the hardware part comprises a body surface measuring electrode, an analog signal amplifier, an A/D (Analog/Digital) conversion card and a digital operation device; and the software processing part comprises a digital preprocessing module, a noise estimation module, an RLS adaptive filtering module, a display device, a storage device, and the like. The utility model has the following beneficial effects and advantages that: firstly, the gastric electrical slow-wave signal detection device is designed aiming to the self-adapting processing filter of gastric electrical slow-wave signals, electrocardiosignals, respiration signals, shaking movement and the self noise of a signal amplifying device are used as the noise of the gastric electrical slow-wave signals and are designed by the self-adapting filter to reduce filter complexity; and secondly, measuring signals are multiply reproduced by the signals subjected to self-adapting filtration, and the precise multiple reproduction of the gastric electrical slow-wave signals can be completed.
Description
Technical field
This utility model relates to the device that a kind of electro-gastric signals is handled, and can carry out the device of the stomach electricity slow wave signal processing of medical diagnosis specifically for acquisition.
Background technology
Gastropathy is a kind of common, multiple, difficult radical-ability disease.Along with the progress of medical diagnostic techniqu, the gastropathy diagnosis has not been a difficult matter.Again to the diagnosis of C14 chromatograph, organic gastropathy is found easily to biopsy from barium meal, endoscope, gastric analysis.But for functional gastropathy, of no avail, said method can bring certain misery, damage to patient, and the danger of communicate illness is arranged.As the digestive tract power diagnostic method of a kind of, safety, noinvasive, no pain, promptly pasting measurement electrode by body surface is the noinvasive detection method of digestive tract physiological detection, diagnosis.
Electro-gastric signals is very faint, therefore change very slowly, the observation stomach electricity difficulty by external electrode is very big, has on the other hand, clinical meaning understanding to clectrogastrogram is not enough, is all needing very big raising aspect stomach electro-detection means, analytical method and the effectiveness at present.
Electro-gastric signals is a kind of typical small-signal, and the stomach electricity of body surface amplitude arrives several millivolts of magnitudes for the hundreds of microvolt, and normal person's electro-gastric signals slow wave composition frequency is extremely low, and bandwidth is 0.02-0.3Hz; The signal that body surface collects has comprised various interference again, and as electrocardio, breath signal, shake etc., the interferential amplitude of part also may be much larger than electro-gastric signals.Can introduce a large amount of strong background noises in the measuring process, wherein again with electrocardio, the most difficult removal of breathing artefact.
Sef-adapting filter can prior given signal and the auto-correlation function of noise, the filter parameter that it can utilize the acquired filter parameter of previous moment automatically to regulate now makes that the mean square error between wave filter output and the unknown input minimizes or (weighting) minimum mean-square error minimizes, thereby it can realize optimal filter.
The algorithm of sef-adapting filter has a lot, and RLS (recurrent least square method) and LMS (least mean square algorithm) etc. are arranged.
The utility model content
This utility model by adaptive signal processing method, is finished the observation to the slow wave signal at the slow wave signal in the stomach electricity.
The purpose of this utility model provides a kind of adaptive-filtering blood processor that can obtain signal to the body surface measurement electrode, removes the measurement influence that electrocardio, breath signal, shake etc. bring, and finishes the observation to stomach electricity slow wave signal.
For solving the problems of the technologies described above, this utility model discloses a kind of stomach electricity slow wave signal supervisory instrument based on recurrence least square RLS (Recursive least squares) sef-adapting filter, comprise hardware components 1 and software processing part 2, described hardware components 1 comprises body surface measurement electrode, analog signal amplifier 11, A/D transition card 12 and digital operation equipment 13; Described external electrode is used for signals collecting, and described external electrode links to each other with analog signal amplifier 11 by leading, and described analog signal amplifier 11 electro-gastric signals that body surface is faint amplifies; Described analog signal amplifier 11 links to each other with A/D transition card 12 by lead, and described A/D transition card 12 is a digital signal with analog signal conversion; Described A/D transition card 12 links to each other with digital operation equipment 13 by data wire, and described digital operation equipment 13 carries out signal processing with digital signal;
Described software section 2 comprises equipment such as digital pretreatment module 21, Noise Estimation module 22, RLS adaptive-filtering module 23 and demonstration, storage, and wherein said data preprocessing module 21 comprises data resampling module 211 and digital band pass/low-pass filtering module 212; Described Noise Estimation module 22 comprises that the data dominant frequency is searched module 221 and number tape hinders filtration module 222; Described data resampling module 211 and digital band pass/low-pass filtering module 212 carry out pretreatment with the digital signal of digital operation equipment 13 outputs; A described pretreatment part is as a result searched module 221 and number tape resistance filtration module 222 by the data dominant frequency successively, obtains Noise Estimation; Last described pretreatment result and described Noise Estimation input RLS adaptive-filtering module, by RLS adaptive-filtering module dateout to equipment such as demonstration, storages.
Described data resampling module 211 comprises data input pin, the resampling computing, and three parts of data output end, these three parts connect successively.Data input pin is input as the data of sample rate Fs, and through the resampling computing, data output end is output as the data of sample rate f s, the Fs＞fs that wherein has ready conditions, and fs is about 1-10Hz.
Described digital band pass/low-pass filtering module 212 comprises digital signal input end, digital filtering, and three parts of digital signal output end, these three parts connect successively.Digital signal input end input string number signal, through about 0.01-0.5Hz digital band pass of passband or the about 0.5Hz digital low-pass filtering of cut-off frequency, digital signal output end is output as filtered digital signal.
Described data dominant frequency is searched module 221 and is comprised digital signal input end, power spectrumanalysis, and peak position is searched, four parts of outfan, these four parts connect successively.Digital signal input end input string number signal is through power spectrumanalysis, after peak position is searched, from the corresponding dominant frequency value of outfan output main peak.
Described number tape resistance filtration module 222 comprises the dominant frequency input, digital signal input end, and the stopband setting, filter parameter dynamically generates, band elimination filter (dynamically generating), six parts of digital signal output end.Wherein dominant frequency input connection stopband is provided with part, stopband is provided with part and connects the dynamic generating portion of filter parameter, the dynamic generating portion connecting band resistance of filter parameter filter segment, digital signal input end and digital signal output end be connecting band resistance filter segment respectively.At first from dominant frequency input input dominant frequency numerical value, through stopband part is set and obtains filter stop bend, this filter stop bend obtains one group of filter parameter through the dynamic generating portion of filter parameter, utilize this group parameter dynamically to generate a band elimination filter, then, from the digital signal input end supplied with digital signal,, export filtered digital signal at the digital signal output end place through this band elimination filter.
The utlity model has following beneficial effect and advantage:
1. the self-adaptive processing wave filter towards stomach electricity slow wave signal designs, promptly electrocardio, breath signal, shake, and the noise of signal amplifying apparatus itself all as the noise of stomach electricity slow wave signal, and it is carried out the design of sef-adapting filter, to reduce the complexity of wave filter.
2. measuring-signal promptly can be finished the accurate reproduction to stomach electricity slow wave signal by the reproduction of the signal behind the adaptive-filtering.
Description of drawings
Fig. 1 is a structured flowchart of the present utility model;
Fig. 2 is a data resampling module diagram;
Fig. 3 is digital band pass/low-pass filtering module sketch map;
Fig. 4 searches module diagram for the data dominant frequency;
Fig. 5 is number tape resistance filtration module sketch map;
Fig. 6 is a stomach electricity slow wave signal reproduction sketch map.；
The specific embodiment
Describe structure of the present utility model and control procedure in detail below in conjunction with embodiment and accompanying drawing.
As shown in Figure 1, comprise hardware components 1 and software section 2, wherein hardware components 1 has analog signal amplifier 11, A/D transition card 12 and digital operation equipment 13 (present embodiment employing PC).External electrode links to each other with analog signal amplifier 11 by leading, and the electro-gastric signals that body surface is faint is delivered to this amplifier and amplified; The amplifying signal of described analog signal amplifier 11 outputs links to each other with A/D transition card 12 by lead, the analogue signal of 500 to 1000 times of amplitude amplifications is delivered to this transition card be converted to digital signal; Described A/D transition card 12 links to each other with digital operation equipment 13 by data wire, gives this digital operation equipment with digital signal and carries out signal processing.Software section 2 is present in the digital operation equipment 13, comprises data preprocessing module 21, Noise Estimation module 22 and RLS adaptive-filtering module 23.Wherein said data preprocessing module 21 has data resampling module 211 and digital band pass/low-pass filtering module 212, and it is that the 0.5Hz digital low-pass filtering is handled that the digital signal of importing is carried out resampling and 0.01-0.5Hz digital band pass or cut-off frequency successively; Described Noise Estimation module 22 has the data dominant frequency and searches module 221 and number tape resistance filtration module 222, the digital signal of input is searched module through this data dominant frequency and is obtained dominant frequency, this dominant frequency numerical value and this digital signal enter number tape resistance filtration module then, and the filtering result of output is an estimating noise.The digital signal that digital operation equipment 13 obtains by data resampling module 211 and digital band pass/low-pass filtering module 212, obtains the pretreatment result successively.A described pretreatment part is as a result searched module 221 and number tape resistance filtration module 222 by the data dominant frequency successively, obtains Noise Estimation.Last described pretreatment result and described Noise Estimation obtain the output of final result as two inputs of RLS adaptive-filtering module.This dateout can be done processing such as demonstration, storage on described digital operation equipment 13, treat that the doctor analyzes and diagnoses.
As shown in Figure 2, described data resampling module 211 comprises data input pin, the resampling computing, and three parts of data output end, these three parts connect successively.Data input pin is input as the data of sample rate Fs, and through the resampling computing, data output end is output as the data of sample rate f s, the Fs＞fs that wherein has ready conditions, and fs is about 1-10Hz.
As shown in Figure 3, described digital band pass/low-pass filtering module 212 comprises digital signal input end, digital filtering, and three parts of digital signal output end, these three parts connect successively.Digital signal input end input string number signal, through about 0.01-0.5Hz digital band pass of passband or the about 0.5Hz digital low-pass filtering of cut-off frequency, digital signal output end is output as filtered digital signal.
As shown in Figure 4, described data dominant frequency is searched module 221 and is comprised digital signal input end, power spectrumanalysis, and peak position is searched, four parts of outfan, these four parts connect successively.Digital signal input end input string number signal is through power spectrumanalysis, after peak position is searched, from the corresponding dominant frequency value of outfan output main peak.
As shown in Figure 5, described number tape resistance filtration module 222 comprises the dominant frequency input, digital signal input end, and the stopband setting, filter parameter dynamically generates, band elimination filter (dynamically generating), six parts of digital signal output end.Wherein dominant frequency input connection stopband is provided with part, stopband is provided with part and connects the dynamic generating portion of filter parameter, the dynamic generating portion connecting band resistance of filter parameter filter segment, digital signal input end and digital signal output end be connecting band resistance filter segment respectively.At first from dominant frequency input input dominant frequency numerical value, through stopband part is set and obtains filter stop bend, this filter stop bend obtains one group of filter parameter through the dynamic generating portion of filter parameter, utilize this group parameter dynamically to generate a band elimination filter, then, from the digital signal input end supplied with digital signal,, export filtered digital signal at the digital signal output end place through this band elimination filter.
Fig. 6 is a stomach electricity slow wave signal reproduction sketch map, this shows that this utility model can be finished the accurate reproduction to stomach electricity slow wave signal.
Be a typical embodiment of the present utility model as mentioned above,, can not enumerate one by one that other are any to make up, simplify, and substitutes etc., all should be within protection domain of the present utility model under general frame of the present utility model because embodiment is more.
Claims (3)
1. one kind based on the stomach of RLS sef-adapting filter electricity slow wave signal supervisory instrument, comprise hardware components (1) and software processing part (2), described hardware components (1) comprises body surface measurement electrode, analog signal amplifier (11), A/D transition card (12) and digital operation equipment (13); Described external electrode is used for signals collecting, and described external electrode links to each other with analog signal amplifier (11) by leading, and described analog signal amplifier (11) electro-gastric signals that body surface is faint amplifies; Described analog signal amplifier (11) links to each other with A/D transition card (12) by lead, and described A/D transition card (12) is a digital signal with analog signal conversion; Described A/D transition card (12) links to each other with digital operation equipment (13) by data wire, and described digital operation equipment (13) carries out signal processing with digital signal;
Described software processing part (2) comprises equipment such as digital pretreatment module (21), Noise Estimation module (22), RLS adaptive-filtering module (23) and demonstration, storage, and wherein said data preprocessing module (21) comprises data resampling module (211) and digital band pass/low-pass filtering module (212); Described Noise Estimation module (22) comprises that the data dominant frequency is searched module (221) and number tape hinders filtration module (222); Described data resampling module (211) and digital band pass/low-pass filtering module (212) carry out pretreatment with the digital signal of digital operation equipment (13) output; A described pretreatment part is as a result searched module (221) and number tape resistance filtration module (222) by the data dominant frequency successively, obtains Noise Estimation; Last described pretreatment result and described Noise Estimation input RLS adaptive-filtering module, by RLS adaptive-filtering module dateout to equipment such as demonstration, storages.
2. stomach electricity slow wave signal supervisory instrument according to claim 1, it is characterized in that: described data resampling module (211) comprises data input pin, the resampling computing, three parts of data output end, these three parts connect successively; Described digital band pass/low-pass filtering module (212) comprises digital signal input end, digital filtering, and three parts of digital signal output end, these three parts connect successively.
3. stomach electricity slow wave signal supervisory instrument according to claim 1, it is characterized in that: described data dominant frequency is searched module (221) and is comprised digital signal input end, power spectrumanalysis, peak position is searched, four parts of outfan, these four parts connect successively; Digital signal input end input string number signal is through power spectrumanalysis, after peak position is searched, from the corresponding dominant frequency value of outfan output main peak;
Described number tape resistance filtration module (222) comprises the dominant frequency input, digital signal input end, and the stopband setting, filter parameter dynamically generates, band elimination filter, six parts of digital signal output end; Wherein dominant frequency input connection stopband is provided with part, stopband is provided with part and connects the dynamic generating portion of filter parameter, the dynamic generating portion connecting band resistance of filter parameter filter segment, digital signal input end and digital signal output end be connecting band resistance filter segment respectively; At first from dominant frequency input input dominant frequency numerical value, through stopband part is set and obtains filter stop bend, this filter stop bend obtains one group of filter parameter through the dynamic generating portion of filter parameter, utilize this group parameter dynamically to generate a band elimination filter, then, from the digital signal input end supplied with digital signal,, export filtered digital signal at the digital signal output end place through this band elimination filter.
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| CN2009202882171U CN201641998U (en) | 2009-12-18 | 2009-12-18 | Gastric electrical slow-wave signal detection device based on RLS self-adapting filter |
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| CN2009202882171U CN201641998U (en) | 2009-12-18 | 2009-12-18 | Gastric electrical slow-wave signal detection device based on RLS self-adapting filter |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104644143A (en) * | 2015-03-09 | 2015-05-27 | 耿希华 | Non-contact life sign monitoring system |
| CN108836321A (en) * | 2018-05-03 | 2018-11-20 | 江苏师范大学 | A kind of EEG signals preprocess method based on adaptive noise cancel- ation system |
-
2009
- 2009-12-18 CN CN2009202882171U patent/CN201641998U/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104644143A (en) * | 2015-03-09 | 2015-05-27 | 耿希华 | Non-contact life sign monitoring system |
| CN108836321A (en) * | 2018-05-03 | 2018-11-20 | 江苏师范大学 | A kind of EEG signals preprocess method based on adaptive noise cancel- ation system |
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| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20101124 Termination date: 20141218 |
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| EXPY | Termination of patent right or utility model |