本文選題：生物雷達(dá) + LMS算法��； 參考：《第四軍醫(yī)大學(xué)》2012年碩士論文

【摘要】：呼吸和心跳等生命體征反映人體的健康狀況，是臨床診斷和疾病預(yù)防的重要依據(jù)。常規(guī)的檢測方法有接觸式和非接觸式兩種：接觸式需要依靠電極或傳感器等采集信號，對人體產(chǎn)生約束，在一些非常規(guī)的應(yīng)用場景（如燒傷、傳染等）不宜使用。常用的非接觸式檢測方法如紅外、激光等受到溫度和環(huán)境障礙物的影響，應(yīng)用范圍受到限制。雷達(dá)式生命體征檢測技術(shù)通過雷達(dá)發(fā)射電磁波照射人體，接收的回波經(jīng)過信號處理分離出呼吸、心跳生命信息。鑒于該技術(shù)可以非接觸、遠(yuǎn)距離、穿透障礙物，隨著雷達(dá)技術(shù)、微電子技術(shù)的發(fā)展，在生命體征檢測領(lǐng)域受到越來越多的關(guān)注。 現(xiàn)階段雷達(dá)式生命體征檢測技術(shù)研究主要集中在對呼吸和心跳信號的檢測上，，在以下方面還存在一定的技術(shù)難題： 首先，由于呼吸、心跳等生命信息具有微弱、低頻、易受干擾、非平穩(wěn)的特點，雷達(dá)系統(tǒng)的系統(tǒng)噪聲會影響回波信號的質(zhì)量，所以如何提高雷達(dá)系統(tǒng)的穩(wěn)定性、抗干擾能力成為該檢測技術(shù)的難題之一。 其次，呼吸運(yùn)動引起的胸廓微動遠(yuǎn)大于心跳信號，且呼吸信號的諧波成分與心跳信號的頻譜有重疊，所以選擇怎樣的信號分離方法從回波信號中分離出能量較小的心跳信號成為難題之一。 針對以上問題，本文在課題組前期研究的基礎(chǔ)上，重點研究呼吸和心跳的分離方法，主要完成以下工作： 1、分析了呼吸、心跳生理特點，研究其與體表胸廓微動的對應(yīng)關(guān)系，明確了雷達(dá)檢測胸廓的微動信息從中提取呼吸、心跳特征參數(shù)的生理學(xué)依據(jù)。 2、結(jié)合本研究呼吸、心跳的特點，以及自適應(yīng)對消算法的原理，提出了基于LMS自適應(yīng)諧波抵消的算法，通過仿真構(gòu)建信號模型，用Matlab實現(xiàn)算法，從體動、呼吸信號中分離出心跳信號，輸出結(jié)果顯示仿真效果良好。 3、設(shè)計完成了相關(guān)實驗，建立了接觸式同步檢測心電信號的對比分析實驗系統(tǒng)，驗證了算法的可行性。實驗包括：實驗一，模擬臨床監(jiān)護(hù)的人體平躺實驗；實驗二：模擬家庭監(jiān)護(hù)的人體坐姿實驗（分為深呼吸和自由呼吸兩種模式）。通過采集不同實驗條件下的呼吸和體動信號，并進(jìn)行自適應(yīng)諧波抵消處理及濾波后的輸出信號與同步檢測的心電信號進(jìn)行對比分析。結(jié)果表明兩者的頻率有很強(qiáng)的相關(guān)性，證實了本算法可以分離出心跳信號。 本課題的創(chuàng)新點： 1、分析了呼吸和心跳與體表胸廓微動的對應(yīng)關(guān)系，明確了雷達(dá)檢測呼吸心跳信號的生理學(xué)依據(jù)。 2、提出了將呼吸信號的諧波組合作為自適應(yīng)濾波器的參考信號輸入的基于LMS自適應(yīng)諧波抵消算法，該改進(jìn)算法對呼吸和心跳的分離具有較好的效果。
[Abstract]:Vital signs such as respiration and heartbeat reflect the health status of human body and are the important basis for clinical diagnosis and disease prevention. The conventional detection methods are contact-type and non-contact-type: the contact-type needs to rely on electrodes or sensors to collect signals, which has constraints on human body, and should not be used in some unconventional application scenarios (such as burn, infection, etc.). Common non-contact detection methods such as infrared laser and so on are affected by temperature and environmental obstacles and their application scope is limited. Radar vital sign detection technology irradiates the human body through radar electromagnetic wave, and the received echo signal is processed to separate the vital information of breath and heartbeat. With the development of radar technology and microelectronics technology, more and more attention has been paid in the field of vital sign detection. At present, the research of radar vital sign detection is mainly focused on the detection of respiratory and heartbeat signals, and there are still some technical problems in the following aspects: First of all, because the vital information such as breathing and heartbeat are weak, low frequency, easy to be interfered and non-stationary, the system noise of radar system will affect the quality of echo signal, so how to improve the stability of radar system, The ability of anti-jamming has become one of the difficult problems of the detection technology. Secondly, the chest fretting caused by respiratory movement is much larger than the heartbeat signal, and the harmonic components of the respiratory signal overlap with the spectrum of the heartbeat signal. So it is a difficult problem to select the signal separation method to separate the low energy heartbeat signal from the echo signal. In view of the above problems, this paper focuses on the separation method of respiration and heartbeat based on the previous study of the research group, mainly accomplishing the following work: 1. The physiological characteristics of respiration and heartbeat were analyzed, the corresponding relationship between them and the fretting of chest was studied, and the physiological basis for extracting the parameters of respiration and heartbeat from the fretting information of radar detection was established. 2. According to the characteristics of breathing and heartbeat, and the principle of adaptive cancellation algorithm, an adaptive harmonic cancellation algorithm based on LMS is proposed. The signal model is constructed by simulation, and the algorithm is realized by Matlab. The heartbeat signal is separated from the respiratory signal, and the output results show that the simulation results are good. 3. The relative experiment is completed, and the experiment system of contact-synchronous ECG signal analysis is established, which verifies the feasibility of the algorithm. The experiment includes: experiment 1, the human body lying flat experiment which simulates clinical monitoring; experiment 2: the human sitting posture experiment which simulates family monitoring (divided into two modes: deep breathing and free breathing). The respiratory and body motion signals under different experimental conditions were collected, and the output signals after adaptive harmonic cancellation and filtering were compared with those of synchronous ECG signals. The results show that there is a strong correlation between the two frequencies, and it is proved that the proposed algorithm can separate the heartbeat signal. The innovation of this topic: 1. The relationship between respiration and heartbeat and body surface chest fretting is analyzed, and the physiological basis for radar detection of respiratory heartbeat signal is clarified. 2. An adaptive harmonic cancellation algorithm based on LMS is proposed, which takes the harmonic combination of respiratory signal as the reference signal input of adaptive filter. The improved algorithm has a good effect on the separation of breath and heartbeat.
【學(xué)位授予單位】：第四軍醫(yī)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：R318.0

【參考文獻(xiàn)】

相關(guān)期刊論文 前6條

1 路國華,王健琪,楊國勝,王海濱,荊西京,邱力軍,楊波;一種人體生命體征檢測的新方法[J];北京生物醫(yī)學(xué)工程;2001年04期

2 楊冬,王健琪,荊西京,焦騰,路國華,葉勇;雷達(dá)式非接觸生命參數(shù)檢測系統(tǒng)中心跳信號提取方法研究[J];醫(yī)療衛(wèi)生裝備;2005年08期

3 張華;路國華;荊西京;王華;呂昊;焦騰;張揚(yáng);于霄;張驍;張鵬飛;薛慧君;王健琪;;非接觸生物雷達(dá)基于自適應(yīng)濾波的心跳信號檢測[J];醫(yī)療衛(wèi)生裝備;2012年01期

4 李斌;傅唯威;王勇;;基于周期抽樣的超寬帶生命探測雷達(dá)信號處理方法[J];儀器儀表學(xué)報;2010年09期

5 王健琪,王海濱,荊西京,楊國勝,楊波,董秀珍,邱力軍;呼吸、心率的雷達(dá)式非接觸檢測系統(tǒng)設(shè)計與研究[J];中國醫(yī)療器械雜志;2001年03期

6 王海濱,倪安勝,王健琪,楊國勝,路國華,荊西京,朱新亞;LMS算法在非接觸生命參數(shù)信號檢測中的消噪應(yīng)用[J];中國醫(yī)療器械雜志;2003年01期

相關(guān)碩士學(xué)位論文 前2條

1 楊冬;基于非接觸生命參數(shù)檢測系統(tǒng)的信號處理技術(shù)研究[D];第四軍醫(yī)大學(xué);2005年

2 王元東;基于超寬譜生物雷達(dá)的非接觸式生命特征信息提取技術(shù)研究[D];第四軍醫(yī)大學(xué);2009年

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