CN101524300B - Digital pillow type device for remedying head sleeping posture by identifying stertor signals - Google Patents
Digital pillow type device for remedying head sleeping posture by identifying stertor signals Download PDFInfo
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- CN101524300B CN101524300B CN200910029294XA CN200910029294A CN101524300B CN 101524300 B CN101524300 B CN 101524300B CN 200910029294X A CN200910029294X A CN 200910029294XA CN 200910029294 A CN200910029294 A CN 200910029294A CN 101524300 B CN101524300 B CN 101524300B
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Abstract
The invention discloses a digital pillow type device for remedying the head sleeping posture by identifying stertor signals, which comprises a pillow body, wherein four air sacs are arranged in the pillow body and respectively connected with a miniature inflator pump and an air pressure sensor; each air pressure sensor is respectively connected with an electric damping exhaust valve; a sound collector for collecting sound is arranged in the pillow body and connected with an amplifying and filter circuit for preprocessing sound signals; the amplifying and filter circuit is connected with a digital signal processing device; and the digital signal processing device is connected with each air pressure sensor and each electric damping exhaust valve. The pillow type device has reasonable structure, does not apply electric stimulus and mechanical stimulus or the limitation of an additional appliance, guarantees the natural sleeping posture and depth of a sleeper, and is more beneficial to the health sleeping.
Description
Technical field:
The present invention relates to a kind of device of snoring of preventing.
Background technology:
The present existing sleep-respiratory quality of improving, the product of alleviating the snoring symptom has: " the turning round and look at dust ground snore stopper " of calendar year 2001 Beijing Gu dust ground scientific & trading Co., Ltd. (www.gidkm.com) exploitation obtains national patent and medical device product registration certificate.Settle the soft support of silica gel in tooth portion before being employed in sleep, can when sleep, lower jaw stretched out forward, thereby preventing that the root of the tongue subordinate from hanging down removes nasal obstruction and reach the purpose of smooth and easy breathing, thereby eliminate effectively or alleviate snoring, improve sleep quality.
Zhejiang Yi Sheng electronics scientific technology co (www.nbesheng.com) has developed the health promoting product that the board snore of resting in peace must stop, and it is the device that utilizes a kind of little electric current intermittent stimulation formula of the theoretical exploitation of Chinese medicine meridian, also has certain effect.
The skill founding of the company of the great Rehabilitation in Taiwan has been produced intelligent snoring pillow in 2007 (www.hong-jian.com.tw).Automatically induce the sound of snoring, the move left and right medicated pillow promotes the adjustment cervical region gently then, the sleeper is broken away from the snoring number of times is reduced gradually, reaches and improves the purpose that breath rhythm promotes sleep quality.
Jiangsu lip cheek type snore stopper (utility model patent number: the ergonomics characteristic Design that ZL03220828.6) adopts physiology of oral cavity to dissect; Let user breathe through two passages in nostril and oral cavity; Cross vibrations, the eddy current that pharyngeal cavity and soft palate, uvula mucosa produce thereby alleviate air communication, and then the elimination sound of snoring.
But above-mentioned various device still has deficiency more at aspects such as performance, effects.
Summary of the invention:
The object of the present invention is to provide a kind of restriction that sleeper is not applied electricity, mechanical stimulus or additional utensil; Guaranteed sleeper's the natural sleep posture and the degree of depth, the head sleeping posture that more helps the digital sound of snoring signal identification of healthy sleep is corrected pillow type device.
Technical solution of the present invention is:
A kind of head sleeping posture of digital sound of snoring signal identification is corrected pillow type device; It is characterized in that: comprise the medicated pillow body; Adorn 4 air bags in the medicated pillow body; Each air bag is connected with a miniature inflator pump respectively, and each air bag is connected with a baroceptor respectively, and said each baroceptor is connected with an electric damper air bleeding valve respectively; The sound collector of gathering sound is set in the medicated pillow body; Sound collector with acoustical signal carried out pretreated amplification be connected with filter circuit; Amplification is connected with digital signal processing device with filter circuit, and digital signal processing device is connected with each baroceptor and each electric damper air bleeding valve.
Sound collector is condenser type MIC.
Digital signal processing device is the digital signal processing device that DSP forms.
The present invention is rational in infrastructure, the sleeper is not applied the restriction of electricity, mechanical stimulus or additional utensil, has guaranteed sleeper's the natural sleep posture and the degree of depth, more helps healthy sleep.
Description of drawings:
Below in conjunction with accompanying drawing and embodiment the present invention is described further.
Fig. 1 is the configuration diagram of one embodiment of the invention.
Fig. 2 is three layers of sensing network illustraton of model of DSP of digital signal processing device.
The specific embodiment:
A kind of head sleeping posture of digital sound of snoring signal identification is corrected pillow type device; Comprise the medicated pillow body; Adorn 4 air bags 1,2,3,4 in the medicated pillow body; Air bag 1,2,3,4 is connected with miniature inflator pump 5,6,7,8 respectively, and air bag 1,2,3,4 is connected with baroceptor 9,10,11,12 respectively, and baroceptor 9,10,11,12 is connected with electric damper air bleeding valve 13,14,15,16 respectively; The sound collector (condenser type MIC) 17 of gathering sound is set in the medicated pillow body; Sound collector with acoustical signal is carried out pretreated amplification and is connected with filter circuit 18; Amplification is connected with digital signal processing device 19 with filter circuit, and digital signal processing device is connected with each baroceptor and each electric damper air bleeding valve.Digital signal processing device is the digital signal processing device that DSP forms.
Operation principle of the present invention is: extract sleeper's acoustical signal by condenser type MIC (17), via amplify and filter circuit (18) to the acoustical signal pretreatment, pass to circuit (19) after reaching certain signal to noise ratio.The digital signal processing device that circuit (19) is made up of DSP, it is that digital signal is transferred to DSP inside then to the analog-signal transitions of circuit (18) output at first.DSP utilizes BP neutral net (being also referred to as the multilayer perception network) to handle the acoustical signal of input, and the sound of snoring characteristic according to learning in advance identifies the sound of snoring in the respiratory murmur.After the sound of snoring arrives certain number of times; Judge the gas pressure of the baroceptor (9,10,11,12) that communicates with air bag (1,2,3,4) earlier, according to pressure control micro air pump (5,6,7, the 8) inflation or the aerofluxus of control damping air bleeding valve (13,14,15,16) of each air bag.Because the change of pressure changes the volume of its inflation in the air bag, the posture that has changed sleeper's head reaches improves the purpose that breath rhythm promotes sleep quality.
The BP neutral net has three-decker promptly in DSP: input layer 20, hidden layer 21 (also claiming the intermediate layer) and output layer 22, and as shown in Figure 2.
Circle among the figure is represented neuron, and each neuron between the adjacent layer is realized full the connection, promptly descends each neuron of one deck all to realize being connected entirely with each neuron of last layer, does not connect but have between each neuron in every layer.
Utilize the multilayer perception network to carry out the process that pattern recognition must have " study ".Both at first each different sound of snoring pattern was set a desired output.Propagate to output layer through the intermediate layer then to network input model of memory, and by input layer, this process is called " pattern is saequential transmission broadcast ".Actual output is the study error with the difference of desired output.According to the rule of " least squares error ", successively revise the connection weights by output layer toward the intermediate layer, this process is called " error Back-Propagation ".Along with the alternate repetition of " pattern is saequential transmission broadcast " and " error Back-Propagation " process carries out.The actual output of network approaches to pairing desired output separately gradually, and network also constantly rises to the accuracy of the response of input pattern.Through this learning process, confirm with preserve each interlayer be connected weights after just can from acoustical signal, identify the sound of snoring.
The BP Learning Algorithms is the learning style of Minimum Mean Square Error.Hypothesis BP network has N processing unit for every layer earlier, and each processing unit is non-linear input/output relation, and the output function of employing is:
f(x)＝1/[1+exp(-x)] (1)
Training set comprises M sample mode to (X
k, Y
k) (k=1,2 ..., m), the input summation of P sample unit j is designated as net
Pj, the output note of unit i is made O
Pj, then:
net
pj＝∑W
jiO
pi (2)
O
pj＝1/[1+exp(-net
pj)] (3)
W wherein
JiBe neuron i, the weights of getting in touch between j.
If arbitrarily the network initial weight is set,, between the actual input of network and the desired output certain error is arranged, the define grid error so to each input pattern P:
E
p＝1/2∑(d
pj-O
pi)
2 (4)
E＝∑E
P (5)
D in the formula
PjRepresent P input pattern, the desired output of output unit j.
Based on this ultimate principle, sound of snoring identifying of the present invention mainly realizes by " learning training " and " identification " two stages,
1, " learning training process "
Input sample---pretreatment---feature extraction---BP network training
The input sample: the sound of snoring sample that at first will gather becomes digital signal input computer.
Pretreatment: then sample signal is carried out pretreatment such as denoising, amplitude adjustment, normalization.
Feature extraction: the eigenvalue sample that digital audio signal is taken out it is to (X
k, Y
k), as the input value of BP network.
The BP network training: BP network training process is divided into " pattern is saequential transmission broadcast " " error Back-Propagation ":
When the forward direction of " pattern is saequential transmission broadcast " training is started working, weighting parameters such as first initialization " input layer---hidden layer " and " hidden layer---output layer ".
Sample is scanned one by one, the sound in the sample is extracted characteristic vector, they are transported to input layer, according to the weights W that connects between neuron
JiCalculate net
Pj, O
Pj, obtain the ideal output of this layer; These data obtain the ideal output of hidden layer equally as the input of hidden layer; Pass to output layer from hidden layer again, obtain the result.
" error Back-Propagation " is that the result of output layer and desirable output are compared, and calculates the weights error on each node of output layer, conceals the error on each node of layer according to the Error Calculation on the output layer node; Calculate the error of hidden layer, input layer more respectively, to each interneuronal weights correction.
To add up error in the error Back-Propagation, calculate mean square error, if the mean square error value of meeting the expectation, and be no more than maximum cycle and then jump out circulation.If do not reach the error amount of expection, perhaps surpassed maximum cycle-index, need to change training parameter.Finish up to training.
After training finishes, can generate multi-group data: the both weights between weights, latent layer and the output layer between input layer and the latent layer and the number information of each layer node are stored in the identification use that supplies the back among the ROM of DSP respectively.
2, " identifying "
Step: sound to be identified---pretreatment---feature extraction---BP Network Recognition
Through the early stage pretreatment and sample training work, found proper weight equivalence after, just can discern.At first, system acquisition sleeper's respiratory murmur.(X when reading training
k, Y
k) be kept at the data among the ROM, then digital audio and video signals is scanned one by one.It is the same to shift to an earlier date method as characteristic in the above-mentioned learning training process, and constitutive characteristic value sample is right.Be transported to input layer to the characteristic vector of extracting, the forward direction input treatment channel according to weights information activation pattern is saequential transmission broadcast obtains differentiating the output result on the neuron output node.Promptly accomplished the identification of this respiratory murmur signal.
Concrete hands-on approach based on the pillow formula nip automatic regulating system of sound of snoring identification is:
(1) is placed on (particular location can be regulated according to individual's situation test and confirm) in sleeper's the medicated pillow to the each several part among Fig. 1 respectively.
(2) by condenser type MIC (17) collection sleeper's respiratory murmur, after circuit (18) pretreatment, be sent in the circuit (19).
(3) utilize DSP identification software of the present invention that the respiratory murmur signal that obtains is discerned processing.
(4) sound of snoring that identifies is carried out degree and judge, and, change its sleeping posture, reach the state that reduces or eliminate respiratory obstruction the airbag aeration or the venting of sleeper's incidence.
Claims (3)
1. the head sleeping posture of a digital sound of snoring signal identification is corrected pillow type device; It is characterized in that: comprise the medicated pillow body; Adorn 4 air bags in the medicated pillow body; Each air bag connects a miniature inflator pump respectively, and each air bag connects a baroceptor respectively, and said each baroceptor connects an electric damper air bleeding valve respectively; The sound collector of gathering sound is set in the medicated pillow body; Sound collector with acoustical signal carried out pretreated amplification be connected with filter circuit; Amplification is connected with digital signal processing device with filter circuit, and digital signal processing device is connected with each baroceptor and each electric damper air bleeding valve.
2. the head sleeping posture of digital sound of snoring signal identification according to claim 1 is corrected pillow type device, and it is characterized in that: sound collector is condenser type MIC.
3. the head sleeping posture of digital sound of snoring signal identification according to claim 1 is corrected pillow type device, it is characterized in that: digital signal processing device is the digital signal processing device that DSP forms.
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| CN200910029294XA CN101524300B (en) | 2009-04-08 | 2009-04-08 | Digital pillow type device for remedying head sleeping posture by identifying stertor signals |
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| CN200910029294XA CN101524300B (en) | 2009-04-08 | 2009-04-08 | Digital pillow type device for remedying head sleeping posture by identifying stertor signals |
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| CN101524300A CN101524300A (en) | 2009-09-09 |
| CN101524300B true CN101524300B (en) | 2012-01-25 |
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Families Citing this family (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102327177A (en) * | 2010-07-13 | 2012-01-25 | 詹瑞鹏 | Pneumatic device with sleeping effect |
| CN102247079B (en) * | 2011-04-13 | 2013-07-31 | 邱晨 | Fully-automatic shape maintaining snore treating pillow |
| CN105232208A (en) * | 2015-09-16 | 2016-01-13 | 朱王勇 | Smart snore-ceasing back mat based on postural therapy |
| CN106264839A (en) * | 2016-08-05 | 2017-01-04 | 南通海联助眠科技产品有限公司 | Intelligent snore stopping pillow |
| CN108697528B (en) * | 2017-06-19 | 2020-12-15 | 深圳和而泰智能控制股份有限公司 | Air bag control method and device |
| CN111770706B (en) * | 2017-12-28 | 2023-06-02 | 数眠公司 | Bed with snore detection feature |
| CN108714071B (en) * | 2018-06-29 | 2024-04-02 | 山东科亿宏智能科技有限公司 | Pillow for correcting apnea and working method thereof |
| WO2020122394A1 (en) * | 2018-12-13 | 2020-06-18 | 주식회사 텐마인즈 | External force detecting system and method for driving external force detecting system |
| CN111110189B (en) * | 2019-11-13 | 2021-11-09 | 吉林大学 | Anti-snoring device and method based on DSP sound and image recognition technology |
| CN111227791A (en) * | 2020-01-09 | 2020-06-05 | 珠海格力电器股份有限公司 | Sleep quality monitoring method and sleep monitoring device |
| CN111489824A (en) * | 2020-04-09 | 2020-08-04 | 杭州电子科技大学 | OSAHS prediction system based on Internet of things |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2535007Y (en) * | 2002-03-22 | 2003-02-12 | 刘宝社 | Snore-stopping gas-filled pillow |
| CN1557270A (en) * | 2004-02-04 | 2004-12-29 | 中国人民解放军空军第四研究所 | Pressure-controllable multiple balloon snoring apnea therapeutic pillow and device |
| CN200973569Y (en) * | 2006-11-30 | 2007-11-14 | 师海峰 | Intelligent sleep helping pillow |
-
2009
- 2009-04-08 CN CN200910029294XA patent/CN101524300B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2535007Y (en) * | 2002-03-22 | 2003-02-12 | 刘宝社 | Snore-stopping gas-filled pillow |
| CN1557270A (en) * | 2004-02-04 | 2004-12-29 | 中国人民解放军空军第四研究所 | Pressure-controllable multiple balloon snoring apnea therapeutic pillow and device |
| CN200973569Y (en) * | 2006-11-30 | 2007-11-14 | 师海峰 | Intelligent sleep helping pillow |
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Owner name: NANTONG HYLAN SLEEP-HELPFUL CO., LTD. Free format text: FORMER OWNER: NANTONG AILSIN HOUSEHOLD TEXTILE CO., LTD. Effective date: 20111109 |
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Effective date of registration: 20111109 Address after: 226014 Guanyin Mountain Science and Technology Pioneering Park, Nantong, Jiangsu Applicant after: Nantong Hailian Sleep Technology Products Co., Ltd. Address before: Eighteen 226014 Bay Industrial Park, Guanyin Mountain, Jiangsu, Nantong Applicant before: Nantong Ailsin Household Textile Co., Ltd. |
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Granted publication date: 20120125 Termination date: 20210408 |
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