【摘要】：當(dāng)前,世界范圍內(nèi)中風(fēng)已經(jīng)與冠心病、癌癥一起被列為威脅人類(lèi)健康的三大疾病之一,國(guó)內(nèi)患中風(fēng)的人數(shù)逐年提升。受家庭經(jīng)濟(jì)承擔(dān)能力的限制,大多數(shù)中風(fēng)病人在醫(yī)院進(jìn)行初步的康復(fù)治療之后就回到家中進(jìn)行下一步的康復(fù)進(jìn)程。一般中風(fēng)病人在離開(kāi)醫(yī)院6至9個(gè)月就停止了康復(fù)治療,但是他們的運(yùn)動(dòng)功能要用幾年時(shí)間才能恢復(fù)。因此,進(jìn)行有效和低成本的家庭遠(yuǎn)程康復(fù)就變得十分重要。本文根據(jù)現(xiàn)有遠(yuǎn)程康復(fù)訓(xùn)練系統(tǒng)存在的中風(fēng)病人與醫(yī)生缺乏有效交互、康復(fù)訓(xùn)練枯燥無(wú)趣使病人無(wú)法堅(jiān)持康復(fù)訓(xùn)練和無(wú)法準(zhǔn)確評(píng)定康復(fù)效果等問(wèn)題,設(shè)計(jì)了新型的中風(fēng)病人康復(fù)訓(xùn)練系統(tǒng)。 系統(tǒng)使用可穿戴加速度傳感器設(shè)備采集康復(fù)訓(xùn)練數(shù)據(jù),通過(guò)ZIGBEE模塊將數(shù)據(jù)發(fā)送到計(jì)算機(jī)。系統(tǒng)提供了上肢康復(fù)動(dòng)作三維重建模塊,可以幫助醫(yī)生克服地域和工作時(shí)間的限制,及時(shí)準(zhǔn)確了解中風(fēng)病人當(dāng)前的康復(fù)進(jìn)展情況和動(dòng)作完成的準(zhǔn)確度。系統(tǒng)建立了利用BP神經(jīng)網(wǎng)絡(luò)評(píng)定上肢動(dòng)作強(qiáng)度模型,以期客觀地評(píng)定中風(fēng)病人當(dāng)前的上肢康復(fù)動(dòng)作強(qiáng)度,此強(qiáng)度參數(shù)可以對(duì)當(dāng)前訓(xùn)練進(jìn)程進(jìn)行科學(xué)評(píng)估。為增加使用本系統(tǒng)的娛樂(lè)性,本系統(tǒng)設(shè)計(jì)了上肢康復(fù)游戲模塊,中風(fēng)病人可以在相對(duì)輕松的環(huán)境下完成與標(biāo)準(zhǔn)上肢康復(fù)訓(xùn)練動(dòng)作相類(lèi)似的訓(xùn)練動(dòng)作。 通過(guò)本系統(tǒng)提供的基于Web的康復(fù)數(shù)據(jù)管理模塊,對(duì)中風(fēng)病人康復(fù)過(guò)程中產(chǎn)生的康復(fù)數(shù)據(jù)進(jìn)行有效管理,從而為醫(yī)生制定中風(fēng)病人下一階段的康復(fù)計(jì)劃提供依據(jù)。
[Abstract]:At present, stroke and coronary heart disease (CHD) and cancer have been listed as one of the three major diseases threatening human health, and the number of strokes in China has been increasing year by year. Limited by the family's financial capacity, most stroke patients return home for the next step after initial rehabilitation in the hospital. Stroke patients usually stop rehabilitation after six to nine months out of the hospital, but it takes years for their motor function to recover. Therefore, effective and low-cost home long-range rehabilitation becomes very important. According to the problems existing in the existing remote rehabilitation training system, such as the lack of effective interaction between stroke patients and doctors, the boring rehabilitation training, the inability of patients to insist on rehabilitation training and the inability to accurately evaluate the effects of rehabilitation, etc. A new rehabilitation training system for stroke patients was designed. The system uses wearable acceleration sensor equipment to collect rehabilitation training data and sends the data to computer through ZIGBEE module. The system provides a 3D reconstruction module of upper limb rehabilitation action, which can help doctors overcome the limitation of region and working time, and accurately understand the current rehabilitation progress of stroke patients and the accuracy of movement completion. A model of upper limb movement intensity assessment using BP neural network was established in order to objectively evaluate the current upper limb rehabilitation action intensity of stroke patients. This strength parameter can be used to evaluate the current training process scientifically. In order to increase the entertainment of using this system, this system designed the upper limb rehabilitation game module, the stroke patient can complete the training movement similar to the standard upper limb rehabilitation training movement in the relatively relaxed environment. The rehabilitation data management module based on Web provided by this system can effectively manage the rehabilitation data generated during the rehabilitation of stroke patients, so as to provide the basis for doctors to formulate rehabilitation plans for stroke patients in the next stage.
【學(xué)位授予單位】：青島大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TP311.52;R743.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 蘇淵;劉峗;;基于BP人工神經(jīng)網(wǎng)絡(luò)改進(jìn)算法的絕緣子污穢預(yù)測(cè)[J];重慶電力高等專(zhuān)科學(xué)校學(xué)報(bào);2013年03期

2 劉艷春;洪曉慧;;Struts2框架核心配置文件的研究與應(yīng)用[J];計(jì)算機(jī)技術(shù)與發(fā)展;2013年02期

3 錢(qián)海軍;;基于Flex的服務(wù)器通信技術(shù)[J];廣東交通職業(yè)技術(shù)學(xué)院學(xué)報(bào);2012年04期

4 丁振凡;;基于注解方式的Spring面向切面編程研究[J];計(jì)算機(jī)時(shí)代;2012年07期

5 陳正舉;;基于HIBERNATE的數(shù)據(jù)庫(kù)訪問(wèn)優(yōu)化[J];計(jì)算機(jī)應(yīng)用與軟件;2012年07期

6 寧齊元;劉祖德;游曦鳴;趙云勝;;基于BP神經(jīng)網(wǎng)絡(luò)煤與瓦斯突出強(qiáng)度預(yù)測(cè)模型[J];煤礦開(kāi)采;2011年06期

7 ;Application of quantum neural networks in localization of acoustic emission[J];Journal of Systems Engineering and Electronics;2011年03期

8 周軍;;基于FLEX和J2EE多層架構(gòu)的Web開(kāi)發(fā)框架研究[J];廣西民族師范學(xué)院學(xué)報(bào);2010年05期

9 呂海東;陸永林;;基于Flex和BlazeDS推技術(shù)實(shí)現(xiàn)WEB方式實(shí)時(shí)監(jiān)控系統(tǒng)[J];自動(dòng)化技術(shù)與應(yīng)用;2010年01期

10 董燕;王彤;胡曉華;;可獨(dú)立步行的腦卒中患者運(yùn)動(dòng)強(qiáng)度指標(biāo)選擇的初步研究[J];中華物理醫(yī)學(xué)與康復(fù)雜志;2009年01期

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