跳到主要內容

臺灣博碩士論文加值系統

(44.201.99.222) 您好!臺灣時間:2022/12/04 00:15
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:翁國倍
研究生(外文):Woung, Kuo-Bei
論文名稱:中風病人運動控制能力評估及復健策略決策支援系統之建構
論文名稱(外文):Development of Motor Control Assessment and Rehabilitative Therapeutic Decision Support System for Stroke Patients
指導教授:黃漢邦, 李明義
指導教授(外文):Luh Yih-Ping
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:機械工程學系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:1997
畢業學年度:85
語文別:中文
論文頁數:200
中文關鍵詞:模糊邏輯類神經網路復健
外文關鍵詞:fuzzy logicneural networkrehabilitation
相關次數:
  • 被引用被引用:1
  • 點閱點閱:562
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:2
近年來,由於生活的富裕,飲食的過度,中風已成為社會上越來越嚴重的
疾病,而中風病患亦是社會的一大負擔。如何評估中風病患的情況並有效
的予以復健乃大家所關切的事情。在傳統的復健裡,復健師根據病人日常
所會用到的動作來訓練病人,但是對於實行何種的復健的動作則依據復健
師本身的經驗來決定,因此經驗的累積往往是一位傑出的復健師所必經的
路程。在本論文裡,一套復健動作決策系統將被建構出來幫助年輕的復健
師決定復健動作。FIM(Functional Independent Measurement)及
Brunnstrom Stage為兩種傳統臨床上用來評估中風病患情況的指標。在本
論文裡,中風病患的情況將根據他們的的運動控制能力(Motor Control
Ability)來作為評估,而運動控制能力則由病患本身的整體平衡控制能
力及對於患側部分肌肉控制能力來決定。為求得客觀的評估,此兩種能力
將由病人接受測試時的動力學訊號及神經生理訊號加以分析。病人的動力
學訊號被輸入一模糊診斷系統加以推論評估病人的整體平衡控制能力,並
且和FIM取得一相對的關係。而神經生理訊號則會經由一類神經網路系統
加以辨認以評估病人患側肌肉控制能力,並且和Brunnstrom Stage做一比
較。此外,對於每個復健動作對中風病患有何復健上的效用亦被收集來建
立一套專家知識庫。由於專家的意見對於系統而言只是些離散的資料點,
為求得一全域的復健效用,對於收集來的專家意見,將被輸入類神經網路
中予以學習,以建立一類神經網路專家知識庫系統(Neural Network
Knowledge Base System)。此一系統將用來提供後段所建立的復健策略
決策支援系統使用。最後復健策略決策支援系統將會整合評估病人的各項
能力,並且由類神經網路專家知識庫系統中求取出一最佳的復健策略以提
供給復健師參考。此一復健策略決策支援系統由電腦程式實現,並配合完
善的人機介面,以方便使用者操作。
In recent years, cerebrovascular accidents have become a very
serious disease in our society. How to assess the states of
cerebrovascular accident (CVA) patients and cure them is very
important. Traditionally, therapists train CVA patients
according to the functional activities they need in their daily
life. It is a direct and effective method. However, the
rehabilitative therapeutic activities are based on the
experiences of therapists. In the thesis, a rehabilitative
therapeutic decision support system will be constructed to help
young therapists.Functional Independent Measurement (FIM) scores
and Brunnstrom Stage are two kinds of clinical indices for
assessing the states of CVA patients in hospitals. In the
thesis, the CVA patients will be analyzed according to the motor
control abilities defined by kinetic signals and neuro-
physiological signals. The kinetic signals are fed into a fuzzy
diagnostic system to assess the global control ability and to
compare with the FIM score. The neuro-physiological signals are
transferred into a neural network system to evaluate the
muscular control ability of the affected side and to compare
with the Brunnstrom Stage.The benefits of each rehabilitative
therapeutic activity are also collected to construct the expert
knowledge base system. For the rehabilitative system, the
opinions of experts are some discrete points. In order to find
the global rehabilitative benefits, the opinions of experts will
be fed into the neural network. After that, a neural network
expert knowledge base system will be constructed to support the
rehabilitative therapeutic decision support system.The
rehabilitative therapeutic decision support system integrates
the abilities of CVA patients and finds the optimal
rehabilitative therapeutic activities for therapists to
practice. In order to facilitate the users, the rehabilitative
therapeutic decision support system is programmed on PC with
user-friendly interface.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊