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基于直腸感知功能重建的人工括約肌系統(tǒng)研究

發(fā)布時間:2018-12-15 02:20
【摘要】:大便失禁指肛門括約肌失去對糞便及氣體排出的控制能力,是臨床上常見的病癥。它容易造成多種并發(fā)癥,尤其在老年患者、危重患者及癱瘓臥床患者中發(fā)病率居高不下,不僅給患者帶來極大痛苦,而且也給護理工作帶來諸多困難。隨著人口老齡化趨勢的發(fā)展,大便失禁已成為醫(yī)療、護理亟需解決的問題,相關治療手段與科學技術的發(fā)展對提高患者生命質量和推動社會文明進步具有重要的現(xiàn)實意義。 治療大便失禁的傳統(tǒng)方法很多,但是都存在一定的缺陷,甚至可能產生嚴重的并發(fā)癥。隨著人們對健康和生命質量的要求不斷提高,傳統(tǒng)的治療方法已經(jīng)不能滿足患者的需求,人工肛門括約肌為大便失禁的治療開辟了一條新途徑;國內外學者已經(jīng)針對人工肛門括約肌的仿生結構、控制方式、能量供給等方面開展了大量研究工作。但是,當前人工肛門括約肌領域涉及的直腸感知功能重建的研究尚無顯著進展,因此圍繞目前人工肛門括約肌研究無法重建患者直腸感知功能這一關鍵問題,進行相關技術方法的深入探索和研究,并充分發(fā)揮現(xiàn)代信息處理技術、材料科學技術、生物醫(yī)學技術等多學科交叉優(yōu)勢,研究一種完全適合植入人體的人工肛門括約肌勢在必行。 本文基于國家自然科學基金科研項目的研究背景,以人工肛門括約肌為研究對象,著重進行直腸感知功能重建的理論方法及相關技術的研究,同時針對特征向量選取和模式識別算法優(yōu)化的相關方法進行積極探索,并在此基礎上構建人工肛門括約肌直腸感知功能重建的實驗平臺,以驗證相關方法技術的可行性和有效性;全文工作可以概括為人工肛門括約肌系統(tǒng)的開發(fā)和實現(xiàn)、直腸感知功能重建理論與方法、模擬腸道實驗平臺構建與驗證分析三大部分。所做主要研究工作與貢獻如下: (1)介紹人體排便的基本生理常識和人體肛門失禁的概況;闡述了肛門失禁治療方法和人工肛門括約肌方面的國內外研究現(xiàn)狀;分析了目前臨床醫(yī)學上針對肛門失禁的治療方法及其不足;根據(jù)人體生物肛門和結直腸的結構特點,提出基于生物反饋控制的人工肛門括約肌系統(tǒng)構思。 (2)人工肛門括約肌系統(tǒng)的仿生學實現(xiàn)。本論文在研究肛門括約肌肌群生理學的基礎上,探索運用工程技術重建肛門括約肌理論、方法和排便控制機理,模擬肛門括約肌各肌群的基本功能;提出系統(tǒng)技術方案,分析系統(tǒng)三大技術模塊:基于生物反饋控制的人工肛門執(zhí)行機構、無線通信模塊和經(jīng)皮供能模塊;按照模塊化和低功耗的要求研究人工肛門括約肌系統(tǒng)的實現(xiàn)結構。 (3)直腸壓力收縮信號的特征提取算法研究。本文在分析現(xiàn)有特征提取方法及存在的問題基礎上,針對直腸收縮信號的非線性、非平穩(wěn)性,提出了基于小波包分解子空間時域特征及子空間頻域特征的的直腸壓力特征提取方法。為從原始特征集中找到最有利于分類的最優(yōu)特征集,以提高分類器的精度和分類準確率,提出了基于Fisher距離的最優(yōu)小波包基直腸壓力特征選擇方法,以及基于DB(Davies-Bouldin,DB)指標優(yōu)化的最優(yōu)小波包基直腸壓力特征選擇方法,并基于概率神經(jīng)網(wǎng)絡(Probilistic Neural Network,PNN)模型驗證了提出方法的有效性。 (4)直腸壓力收縮信號的分類算法研究。本文將基于PNN的分類、基于支持向量機的分類應用于直腸收縮信號的分類預測;同時提出了基于粒子群優(yōu)化算法優(yōu)化支持向量機參數(shù)的直腸收縮信號特征向量分類方法,并在此基礎上對采集到的直腸壓力特征向量進行了分類預測,對比分析了三種分類預測方法的分類準確率,驗證了所提分類方法的有效性和優(yōu)越性。 (5)構建基于生物反饋式人工肛門括約肌實驗模型與實驗平臺,在上述理論與方法的指導下,通過模擬人體腸道環(huán)境,獲取大量實驗數(shù)據(jù),驗證人工肛門括約肌的基本功能、直腸感知功能重建模型的有效性,,根據(jù)評估結果改進和完善人工肛門括約肌系統(tǒng),為大便失禁患者人工器官的最終臨床應用提供理論方法依據(jù)與技術基礎支持。
[Abstract]:The incontinent of the anus refers to the loss of control ability of the anal sphincter to the discharge of the faecal matter and the gas, which is a common condition in the clinic. It is easy to cause a number of complications, especially in the elderly, critically ill patients and in patients with paralysis, not only to the patient, but also to the care work. With the development of the trend of the aging of the population, the fecal incontinence has become a problem for medical care and nursing, and the related treatment means and the development of science and technology are of great practical significance for improving the quality of life of patients and promoting the progress of the social civilization. Traditional methods for the treatment of fecal incontinence are many, but there are some defects and may even lead to serious complications With the increasing demand of people for health and quality of life, the traditional method of treatment has not met the needs of the patient, and the artificial anal sphincter opens a new way for the treatment of fecal incontinence; and the domestic and foreign scholars have been aiming at the bionic structure of the artificial anal sphincter, and the control prescription A large number of studies have been carried out in terms of formula, energy supply, etc. However, there is no significant progress in the research of the reconstruction of the rectal sensing function involved in the field of artificial anal sphincter. Therefore, the key problem in the study of the rectum-sensing function of the patient can not be reconstructed around the present artificial anal sphincter. To study and give full play to the cross-cutting advantage of modern information processing technology, material science and technology, and biomedical technology, a kind of artificial anal sphincter which is completely suitable for human body is studied. In this paper, based on the research background of the National Natural Science Fund (NSFC) research project, the artificial anal sphincter is used as the research object, and the theoretical method and related techniques for the reconstruction of the rectal sensing function are emphasized. At the same time, the research on the optimization of the feature vector selection and the pattern recognition algorithm is explored, and the experimental platform for the reconstruction of the artificial anal sphincter and the rectal sensing function is constructed, so as to verify the feasibility of the related methods and techniques. Effectiveness: The full-text work can be summarized as the development and realization of the artificial anal sphincter system, the theory and method of the reconstruction of the rectal perception function, the construction and verification of the experimental platform of the simulated intestinal tract. Most of them. The main research work and the tribute The following are the following: (1) introduction of the basic physiological knowledge of the defecation of the human body and the general situation of the anal incontinence of the human body; and the domestic situation of the anal incontinence treatment method and the artificial anal sphincter. The present situation of external research is analyzed. The treatment of anal incontinence in the present clinical medicine and its deficiency are analyzed. According to the characteristics of the biological anus and the structure of the colorectal, the artificial anal is proposed based on biofeedback control. muscular system conception. (2) Artificial anal sphincter system This paper, based on the study of the physiology of the sphincter of the anal sphincter, explored the theory, method and the mechanism of defecation control for the reconstruction of the anal sphincter, and the basic function of the muscle group of the anal sphincter. The system technical scheme and the analysis system were put forward. The three major technical modules of the system: the artificial anal actuator, the wireless communication module and the skin energy supply module based on the biofeedback control; and the artificial anal sphincter is researched according to the requirements of the modularization and the low power consumption. System realization structure. (3) Rectal pressure contraction signal In this paper, based on the analysis of the existing feature extraction methods and the existing problems, the paper presents a method based on the wavelet packet decomposition sub-space time domain and the frequency-domain characteristics of the sub-space for the non-linear and non-stationarity of the rectal contraction signal. In order to improve the accuracy and classification accuracy of the classifier, the optimal wavelet packet-based rectal pressure feature selection method based on Fisher's distance is proposed. The optimal wavelet packet-based rectal pressure feature selection method for s-Bouldin (DB) index optimization and verification based on the probabilistic neural network (PNN) model The effectiveness of the proposed method is presented. (4) Rectal pressure The classification algorithm of the contraction signal is based on the classification of PNN, which is applied to the classification and prediction of the rectal contraction signal based on the classification of the support vector machine, and the rectal charge of the parameter of the support vector machine is optimized based on the particle swarm optimization algorithm. The classification method of the characteristic vector of the contraction signal is carried out on the basis of the classification and prediction of the feature vector of the collected rectal pressure. The classification accuracy of the three classification methods is compared and analyzed, and the extracted score is verified. and (5) constructing a biological feedback type artificial anal sphincter experimental model and an experimental platform, and under the guidance of the theory and the method, a large amount of experimental data is obtained through the simulation of the human intestinal environment, The basic function of the artificial anal sphincter and the effectiveness of the reconstruction model of the rectal sensing function are improved and the artificial anal sphincter system is improved and improved according to the results of the evaluation.
【學位授予單位】:上海大學
【學位級別】:博士
【學位授予年份】:2013
【分類號】:R318.14

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