研究生: |
莊立筠 Li-Yun Chuang |
---|---|
論文名稱: |
基於虛擬實境的穿戴式復健動作監控系統於中風病患之應用與評估 The Virtual Reality-based Clinical Application of Wearable Rehabilitation System for Stroke Patients |
指導教授: |
林淵翔
Yuan-Hsiang Lin |
口試委員: |
許維君
Wei-Chun Hsu 林立 Li-Feng Lin |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電子工程系 Department of Electronic and Computer Engineering |
論文出版年: | 2016 |
畢業學年度: | 104 |
語文別: | 中文 |
論文頁數: | 87 |
中文關鍵詞: | 動作監控系統 、慣性感測器 、穿戴式感測器 、居家復健 |
外文關鍵詞: | Rehabilitation monitoring system, Inertial sensor, Wearable device, Home-based rehabilitation |
相關次數: | 點閱:347 下載:3 |
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有動作障礙的患者大多需要每週2次以上的復健,而因為中風造成動作障礙的患者數隨著人口的老年化上升,為了顧全患者的復健品質,卻造成更多的醫療人力資源消耗。因此,居家復健的發展也是現在需要重視的領域。
本研究的目的在於開發一套適合患者自行使用的復健動作監控系統,讓患者在沒有治療師在旁指導輔助的情況下,依然可以透過系統的虛擬實境畫面與動作判斷的語音回饋來引導修正錯誤的動作方向,提高主要動作的關節活動角度並降低偏移角度。藉由網路架設資料庫來連接病患與醫院端資料雙向傳輸,讓治療師可以遠端監控患者復健情況,維持患者的復健品質也節省治療師人力。
此基於虛擬實境的穿戴式復健動作監控系統與馬達驗證比對後,在X、Y和Z軸的平均誤差為1.01°、0.5°及1.1°。此外,在臨床實驗驗證上,兩位使用本系統的患者經過10次復健系統訓練後,在偏移程度減少的軸向相較未使用本系統執行復健訓練患者多,顯示本系統在中風患者的復健上有給予實際復健成效。
Most of the patients with movement disorders need rehabilitation twice a week for recovering, and the population of stroke patients with movement disorders is raising, which is caused by aging of the population. It makes the demand for therapists is increasing for keeping high qualities of rehabilitation. Therefore, home-based rehabilitation is out of the solution to solve these problems.
The purpose of this study is developing a self-use rehabilitation movement monitoring system for patients. The system provides virtual reality and voice feedback to guide the patients to decrease wrong orientation of movement angle and enhance correct orientation angle without therapists’ supervision. The angular position of limbs during rehabilitation process will be recorded and uploaded to the database. Then, the therapist is able to download the data to analyze the result and adjust the data description via internet. Through the wireless communication is able to save manpower of therapist and maintain rehabilitation quality.
The system has been verified with single axis motor. The average error is 1.01, 0.5 and1.1 degree, respectively, for X, Y, Z axis. Based on the experiment results obtained from stroke patients, through involving 10 times clinical training for each participant, the proposed system is certified as an efficient platform for helping the participants to improve their upper limb movement.
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