基於行動裝置的急性中風預後分析方法研究

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何心如(HSIN-JU HO) 查詢紙本館藏

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系統生物與生物資訊研究所

論文名稱

基於行動裝置的急性中風預後分析方法研究
(Development and Validation of Mobile-Based Prognostic Analysis Methodologies for Acute Stroke Outcomes)

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至系統瀏覽論文 (2026-12-11以後開放)

摘要(中)

中風是一場改變人生的事件，全球每年有數百萬人因此受影響，留下身體機能的種種限制，使患者難以恢復自主生活，給家庭和社區造成負擔。中風不僅伴隨高死亡率，對倖存患者而言，還意味必須面對漫長的復健之路。雖然復健已證明有助於恢復身體功能，但這段復健之路往往充滿挑戰。現代復健設備和技術不斷進步，但在可及性、經濟成本及療程強度仍是一大難題。為了解決這個問題，本研究利用行動裝置復健 (Wearable Device-Assisted Rehabilitation, WEAR) 平台配備了行動裝置感測器與智慧型手機應用程式，可透過該平台連接網絡伺服器提供的介面進行即時的動作追蹤和回饋，讓醫護人員能夠遠程監控，使患者在臨床與家庭環境中都能參與復健活動，以增強中風後復健康復效果，協助中風患者實現復健目標。我們的研究目標在於探索此行動裝置平台與傳統復健療法結合後，能否讓中風患者在復健過程中獲得更好的療效並提高其接受度，使高效的復健成為可能。我們邀請了127位急性中風患者參與一項為期90天的臨床研究，這些患者在發病12周內，隨機分成兩組，一組對照組，僅接受傳統式復健，另一組穿戴組，接受WEAR 平台結合傳統復健治療。我們測量每位患者主要的恢復成效，包含第90天的modified Rankin Scale (mRS) 分數變化，並加入巴氏量表，評估患者在日常生活活動、平衡和運動功能方面的細微進展。我們的研究結果顯示：兩組患者在第90天均顯示顯著的恢復，但穿戴組表現更為突出，其mRS得分顯著改善。這不僅僅是功能上的進步，更是賦權的過程。基於統一科技接受與使用理論 (Unified Theory of Acceptance and Use of Technology) 的問卷調查顯示，穿戴組患者在社會影響下更具動力，並逐漸接受使用科技進行復健。在研究期間發現，穿戴組在效能期望和努力期望上也有顯著提升，顯示該技術整合不僅可行且受到歡迎。對中風患者來說，復健是一條充滿挑戰和不確定性的旅程。本研究結果顯示，WEAR平台作為傳統療法的輔助，能夠提升復健體驗，提供更個人化且持續的復健方案，適應不同的環境與患者需求。此系統不僅支持功能性恢復，更提供了一個具成本效益的可持續照護模式，有助於縮小復健潛力與現實可及性之間的差距，為中風後復健邁向更具包容性的未來鋪路。

摘要(英)

Stroke represent a life-altering medical condition affecting millions annually, resulting in substantial physical limitations that compromise survivors’ independence. In the journey to regain functionality, rehabilitation emerges as a beacon of hope. Yet, access to quality rehabilitation is not always guaranteed, especially when obstacles like socioeconomic factors and limited medical resources stand in the way. This study introduces an innovative solution: a wearable device-assisted rehabilitation (WEAR) platform, designed to empower stroke survivors through a blend of advanced technology and conventional therapy. The investigation aimed to evaluate the effectiveness of incorporating this wearable platform into conventional rehabilitation protocols for enhancing recovery experience and outcomes among stroke survivors, making effective rehabilitation more accessible and accepted.
The WEAR platform facilitates real-time interaction between participants and rehabilitation protocols. Equipped with sensors and an application embedded in smartphones, this platform connects to a web server where medical staff can monitor and guide each step of a participant′s recovery journey. This randomized controlled trial enrolled 127 acute stroke survivors within 12 weeks post-onset for a 90-day intervention period. Participants were randomly assigned to either the wearable group (WG), combining WEAR with conventional rehabilitation, or the control group (CG), receiving only traditional rehabilitation. Primary recovery outcomes, including changes in modified Rankin Scale (mRS) scores at day 90 (D90), along with secondary measures such as the Barthel Index and Functional Independence Measure, capturing the nuanced shifts in balance and motor ability.
Our findings painted a hopeful picture: both groups showed significant recovery at D90, but the WG group surpassed expectations, demonstrating greater improvement in mRS scores. This wasn’t just a story of functional gains; it was about empowerment. Surveys using the Unified Theory of Acceptance and Use of Technology (UTAUT) revealed that participants in WG felt more motivated, supported by social influence, and increasingly open to using technology in their rehabilitation. At follow-up intervals (D30 and D90), the wearable group also saw notable gains in performance expectancy and effort expectancy, suggesting that this integration of technology was not only feasible but welcomed. The cross-sectional questionnaire survey revealed significant higher scores Social Influence (SI) and Behavior Intention scores in WG than CG. Follow-up survey in WG demonstrated significantly increasing Performance Expectancy, Effort Expectancy, and Facilitating Conditions scores and insignificantly increasing SI and BI scores at D30 and D90, respectively.
For stroke survivors, rehabilitation is a journey, often filled with challenges and uncertainties. This study suggests that the WEAR platform, as a companion to conventional therapy, could enhance the recovery experience, providing more personalized and continuous rehabilitation that adapts to various settings and participant needs. This platform not only supports functional recovery but offers a sustainable, cost-effective model of care that may help bridge the gap between rehabilitation potential and real-world accessibility, making strides toward a more inclusive approach to post-stroke recovery.

關鍵字(中)

★ 中風
★ 復健
★ 隨機臨床實驗
★ 客製化手機應用程式
★ 行動裝置輔助復健平台
★ 功能性恢復

關鍵字(英)

★ Stroke
★ Rehabilitation
★ Randomized Controlled Trial
★ Customized Application
★ Wearable Rehabilitation Platform
★ Functional Recovery

論文目次

Table of Contents
中文摘要 i
Abstract iii
致謝 v
Table of Contents vi
List of Figures ix
List of Tables x
Chapter 1 Introduction 1
1-1 Background of Stroke 1
1-2 The Use of Application in Clinical 2
1-3 Related Works 4
1-4 Research Goal 5
Chapter 2 Platform Architecture 7
2-1 Mobility Rehabilitation Platform 7
2-1-1 Rehabilitation APP on Smartphone 8
2-1-2 Rehabilitation APP on Smartwatch 12
2-2 Motion Capture and Assessment 12
2-3 Server for Record Tracking at Home 14
2-4 Summary 16
Chapter 3 Preparation for Implementation of Rehabilitation Assistance Platform 19
3-1 W-Stroke Care APP 19
3-1-1 Clinical Implement by Activities 20
3-1-2 Tracking Rehabilitation Activity Records 23
3-1-3 W-Stroke Care APP of e-Book 24
3-1-4 Risk Factors Assessment for Stroke 26
3-2 Clinical Procedure and Actigraphy 27
Chapter 4 Clinical Implementation of the Rehabilitation Assistance Platform 30
4-1 Clinical Trial Design 30
4-1-1 Ethical Statement 30
4-1-2 Participants Recruitment 31
4-1-3 Implement W-Stroke Care APP 32
4-1-4 Implementation of Rehabilitation Programs 34
4-1-5 Acceptance of WEAR Platform 36
4-2 Data Collection 36
4-2-1 Collection of Clinical Information 36
4-2-2 Retention of Data 37
4-2-3 Data Pre-processing and Preparation 37
4-3 Outcome Measures 37
4-3-1 Primary Outcome 38
4-3-2 Secondary Outcomes 38
4-4 Statistical Analyses 39
Chapter 5 Clinical Trial Results of the Rehabilitation Assistance Platform 42
5-1 Participants Characteristics 42
5-2 Primary Outcome 46
5-3 Secondary Outcomes 47
5-4 Results of Acceptance of WEAR Platform 47
5-5 Clinical Impacts Estimation 50
Chapter 6 Discussion and Conclusion 52
6-1 Discussion 52
6-2 Conclusion 57
Reference 58
Appendix 64

參考文獻

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指導教授

吳立青(Li-Ching Wu)

審核日期

2024-12-11

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