以運動指標預測復健成效暨設計復健方針;Using Kinematic Features to Predict Rehabilitation Outcome and Guide Rehabilitation Strategy

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/71429

Title:	以運動指標預測復健成效暨設計復健方針;Using Kinematic Features to Predict Rehabilitation Outcome and Guide Rehabilitation Strategy
Authors:	廖翊涵;Liao,Yi-Han
Contributors:	生物醫學工程研究所
Keywords:	虛擬實境;運動指標;復健方針;Virtual Reality;Kinematic Features;Rehabilitation Strategy
Date:	2016-08-18
Issue Date:	2016-10-13 13:03:53 (UTC+8)
Publisher:	國立中央大學
Abstract:	復健療程一直是改善中風造成的運動失能的主要方式之一，雖然多數的復健運動都被證實具有復健效果，卻不是全部的病患復健後運動功能損傷都獲得顯著提升。許多的文獻也提到復健療程沒有普遍的適用性。本研究透過虛擬實境系統提供中風復健療程並計算運動學相關指標，討論不同復健情形的病患與運動功能改善相關的運動學指標，藉此提出個別化的復健療程的指導方針。本研究招募了21名受試者，依據復健前後Fugl-Meyer量表是否達到進步10%的臨床效益，將病患分為復原普通和復原良好兩種情形(復原良好11人，復原普通10人)，而兩組之間復健前臨床量表分數並無顯著差異。分析結果顯示，不同復原情形病患與改善其運動損傷相關的運動指標確實有所不同，運動效率、接近直線軌跡及速度穩定度的提升與復原良好的病患運動功能改善有關；而復原普通的病患運動速度及手部施壓能力的提升有助於運動功能提升。本研究也發現運動指標表現能夠精準預測病患的復健情形，顯示復健過程中運動指標的變化能當成設計復健療程的依據，而虛擬實境能夠幫助及時調整復健方針。總結來說，我們的研究結果說明個別化的復健療程將有機會為病患帶來更多的益處。未來我們希望能證實以運動指標及時評估與調整復健，能夠讓病患運動功能損傷獲得更多改善，使復健更有效率。 ;Rehabilitation is one of the most frequently used therapeutic approaches to restore movement impairment after stroke, but significant variability exists between patients regarding rehabilitation efficacy. Many studies suggested that there is no optimal rehabilitation treatment suit to all patients. This study aims to identify the motion kinetics extracted from the virtual reality based rehabilitation that are significantly correlated with the functional improvement. Twenty -one stroke patients were recruited and were labeled as either having favourable (n=11) or poor recovery (n=10) according to whether their postrehabilitation improvement of Fugl-Meyer assessment has reached the 10% level of clinical significance. The clinical scores before the intervention revealed no significant difference in the initial impairments between the favourable and poor recovery groups. However, we found that the changes of motor kinetics during VR rehab differs in patients with different improvement levels: For patients with good recovery, the increase of efficiency, speed stability and straightness of trajectory leads to better functional improvement; For patients with poor recovery, the increase of motion speed and palm strength promotes the recovery. In additional, these kinematic features can be used to accurately predict the recovery outcome and thus server as guidance when designing the rehab strategy. In conclusion, our findings provide evidence that individualized treatment could most benefit patients and facilitate effective rehabilitation. In a future work, we will test whether real-time adjustment of rehabilitation according to the kinematic features can further improve the functional impairments.
Appears in Collections:	[Institute of Biomedical Engineering] Electronic Thesis & Dissertation

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