本文關(guān)鍵詞： 血糖預(yù)測 小波去噪 ARIMA BP神經(jīng)網(wǎng)絡(luò) 組合預(yù)測　出處：《鄭州大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著糖尿病患者數(shù)量的不斷增多,糖尿病對人類健康的危害日趨增加,而穩(wěn)定血糖是糖尿病患者臨床治療的主要目的,如果能提前預(yù)測出患者的血糖濃度,那么醫(yī)生和患者就能在高血糖或者低血糖事件發(fā)生之前采取措施來穩(wěn)定血糖,這將極大減小糖尿病對患者造成的傷害。建立一個精確度比較高的血糖預(yù)測模型,為醫(yī)生和糖尿病患者提供指導(dǎo),具有很好的應(yīng)用價值。目前,關(guān)于人體血糖預(yù)測技術(shù)的研究大體有兩個方向:一個方向是只利用患者的歷史血糖值,不考慮影響患者血糖動態(tài)變化的外部因素(飲食、藥物注射、運動等),追求簡單和高效,但不夠精準(zhǔn);另外一個方向不僅利用糖尿病患者的歷史血糖值,而且結(jié)合人體的生理模型和大量的病理學(xué)、生理學(xué)的知識,追求準(zhǔn)確和精準(zhǔn),算法復(fù)雜,有一定延遲。本文深入研究了影響人體血糖變化的關(guān)鍵因素和血糖預(yù)測所面臨的問題,在比較了現(xiàn)有的血糖預(yù)測技術(shù)的基礎(chǔ)上,探討基于ARIMA和BPNN的組合預(yù)測模型對患者血糖未來值分析和預(yù)測的可行性。采用ARIMA對糖尿病患者的歷史血糖值進(jìn)行分析,找出患者血糖變化的線性規(guī)律,利用BPNN捕獲外部因素對人體血糖的影響,并對輸入值、誤差項等進(jìn)行學(xué)習(xí)和擬合。最后將ARIMA計算出的預(yù)測值與BP算法得到的修正值進(jìn)行組合,得到準(zhǔn)確的結(jié)果。同時,針對飲食或藥物注射在短時間內(nèi)對人體血糖波動的突發(fā)影響,設(shè)定開始影響的點為奇異點,提出一種奇異點發(fā)現(xiàn)和處理算法,在人體血糖受外部干擾發(fā)生不規(guī)律變化時自動調(diào)整未來一段時間內(nèi)的預(yù)測值,保證組合預(yù)測模型的精度和準(zhǔn)確度。采用河南省人民醫(yī)院內(nèi)分泌科所提供的糖尿病患者血糖數(shù)據(jù)對所提出來的基于ARIMA和BPNN的組合預(yù)測模型及奇異點發(fā)現(xiàn)和處理算法進(jìn)行驗證。結(jié)果表明,相比ARIMA預(yù)測,所提出來的組合預(yù)測模型具有更好的預(yù)測效果,可以給醫(yī)生或者糖尿病患者提供臨床上的指導(dǎo);所提出的奇異點發(fā)現(xiàn)和處理算法,在人體血糖受外部干擾發(fā)生急劇變化時能自動調(diào)整未來一段時間內(nèi)的預(yù)測值,能保證組合預(yù)測模型的預(yù)測精度和準(zhǔn)確度。
[Abstract]:With the increasing number of patients with diabetes, diabetes is increasingly harmful to human health, and stable blood sugar is the main purpose of clinical treatment of patients with diabetes, if we can predict the concentration of blood sugar in advance. Then doctors and patients can take steps to stabilize blood sugar before hyperglycemia or hypoglycemia occurs, which will greatly reduce the damage caused by diabetes. To provide guidance for doctors and patients with diabetes, has a good application value. At present, there are two directions in the study of blood glucose prediction technology: one direction is to use only the patient's historical blood sugar value. Regardless of the external factors (diet, drug injection, exercise, etc.) that affect the dynamic changes of blood glucose, the pursuit of simplicity and efficiency, but not accurate; The other direction not only uses the historical blood sugar value of diabetic patients, but also combines the physiological model of the human body and a lot of pathology, physiological knowledge, the pursuit of accuracy and precision, complex algorithm. In this paper, the key factors affecting the changes of blood glucose and the problems of blood glucose prediction are studied in depth, based on the comparison of existing blood glucose prediction techniques. To explore the feasibility of the combination prediction model based on ARIMA and BPNN to analyze and predict the future value of blood glucose in patients with diabetes mellitus. ARIMA was used to analyze the historical blood glucose value of patients with diabetes mellitus. To find out the linear rule of blood glucose change, use BPNN to capture the influence of external factors on human blood sugar, and to input value. Finally, the predicted value of ARIMA is combined with the revised value of BP algorithm to get accurate results. Aiming at the sudden effect of diet or drug injection on blood glucose fluctuation in a short period of time, the singularity point is set as the starting point, and a singular point detection and processing algorithm is proposed. Automatically adjust the predicted value for a period of time when the body's blood sugar changes irregularly by external interference. To ensure the accuracy and accuracy of the combined prediction model. The combined prediction model based on ARIMA and BPNN was proposed by using the blood glucose data of diabetic patients provided by the Endocrinology Department of Henan Provincial people's Hospital. The algorithm of point discovery and processing is verified. The results show that. Compared with ARIMA prediction, the proposed combined prediction model has better predictive effect and can provide clinical guidance to doctors or patients with diabetes. The proposed singular point detection and processing algorithm can automatically adjust the prediction value in the future when the blood sugar changes sharply by external interference, which can ensure the prediction accuracy and accuracy of the combined prediction model.
【學(xué)位授予單位】：鄭州大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：R587.1;TP18

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本文編號：1476947