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研究生: 曾澤恩
Chien, Ze-En
論文名稱: 應用擴增實境改善年長者視覺空間關注能力訓練遊戲之開發
Augmented Reality Based Visual Spatial Attention Modification Training Game for Elderly
指導教授: 陳建旭
Chen, Chien-Hsu
學位類別: 碩士
Master
系所名稱: 規劃與設計學院 - 工業設計學系
Department of Industrial Design
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 108
中文關鍵詞: 高齡者視覺空間關注波斯納任務擴真實境關注網絡訓練
外文關鍵詞: Elderly, Visual spatial attention, Posner’s task, Augmented Reality, Attention Network training
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  • 高齡化社會將連帶的對社會和國家帶來許多的問題,例如醫療費用開銷,獨居和疾病擴大之問題。因此,在未來社會,如何改善老年人之相關議題將成為焦點。在高齡化社會中,跌倒成為了一個對老年人傷害主要的威脅。跌倒可以導致身體創傷,不僅如此也會影響老年人對跌倒的恐懼而自信心受創,不敢再嘗試一些運動,這將加劇老年人退化。
    在之前,大部分研究主要都以針對肌肉骨骼方面去探討跌倒的危險因子,近期發現認知功能衰退也是導致跌倒的其中原因之一。據研究,在認知功能衰退的過程中,視覺空間關注能力在眾多非記憶認知功能中屬最先衰退的一塊。視覺空間關注能力主要協助老人在肢體運動時,執行引導步伐,動態平衡和距離判斷之作用。因此,視覺空間關注能力下降是導致跌倒的其中原因之一,一些研究也以老年人視覺空間關注能力來判斷其是否是跌倒高風險群。
    老年人視覺空間關注的能力能夠透過掛關注網絡訓練的方式來改善與加強。其方式主要原因注意涉及許多不同的功能神經網絡,受試者可通過不斷重複、複習波斯納任務等,認知任務的方式改進這些一個或多個功能來提高神經網絡的效率。雖然重複做波斯納任務等認知任務可以改善視覺空間關注能力,但現有的認知任務都缺乏趣味性與互動方式,大部分的年長者都不會將其納入日常練習行程。
    本研究由設計方法歸納出設計準則,並結合之擴真實境之技術與現有的認知任務結合,推出一套遊戲練習系統,協助高齡者鍛煉認知功能,改善視覺關注衰退之問題,從而減少跌倒之風險和提升高齡者生活品質。

    The aging society will cause problems to the public and the country, such as extra medical expenses, solitariness and expanding diseases. Therefore, in the future society, how to improve the issues related to the elderly will become the main focus. In aging society, fall has become a major threat to the elderly which causes injury both physically and psychologically, making them not confidant and fear to fall again. This will exacerbate the degradation of the elderly.
    In the past, most of the studies focused on the risk factors of falls in the musculoskeletal area. It is recently discovered that cognitive decline is also one of the causes of falls. According to research, visual-spatial attention ability is firstly affected in the process of cognitive decline among the other non-memory cognitive functions. The ability mainly assists the elderly in the exercise of stepping, performing the role of guiding pace, dynamic balance and distance judgment. Therefore, one of the reasons that cause fall is the decrease in visual-spatial attention ability. Some studies have also used the visual-spatial attention ability of the elderly to judge whether they are a high-risk group to fall. The ability to visually focus on space can be improved and enhanced through network training. The main reason to use this training is that many different functional neural networks are involved, thus, by repeating and reviewing Posner’s task and cognitive tasks, subject can improve the efficiency of the neural network. Although repetition of cognitive tasks can improve visual spatial attention, the existing tasks, however, lack of interesting and interactive ways. As a result, most of the seniors do not include them in their daily practice.
    This study summarizes the design criteria by design methodology, and combines the technology of augmented reality with existing cognitive tasks to introduce a game practice system to help senior citizens exercise cognitive function and improve visual attention to recession, thus reducing the risk of falls, improving the life quality of the elderly.

    摘要 ii SUMMARY iii ACKNOWLEDGEMENTS iv TABLE OF CONTENTS v LIST OF TABLES viii LIST OF FIGURES ix CHAPTER 1 INTRODUCTION 2 1.1 Background 2 1.2 Motivation 2 1.2.1 Visual Spatial Attention Training via Brain Network Training 3 1.2.2 The Gamification of Attention Network Training 4 1.2.3 Augmented Reality Application and Visual Spatial Attention 4 1.3 Objective 5 1.4 Overview 6 CHAPTER 2 LITERATURE REVIEW 8 2.1 Attention Theory 8 2.1.1 Selective Attention 8 2.1.2 Type of Visual Attention 10 2.2 Introduction of Visual Spatial Attention 11 2.2.1 Posner’s Cueing Paradigm - The Measurement of Visual Spatial Attention 11 2.2.2 Posner’s Cueing Paradigm from PysToolkit. 14 2.2.3 Visual Spatial Attention Ability in Elderly 15 2.3 Current Training Ways of Visual Spatial Attention 18 2.3.1 Brain State Training – Open-skill Exercise 18 2.3.2 Attention Network Training 20 2.4 Application of Augmented Reality 22 2.4.1 Augmented Reality Object Presentation 24 CHAPTER 3 METHODOLOGY 26 3.1 The Design Criteria of Training Game 28 3.1.1 Posner’s Task - The Analysis and Conversion 28 3.1.2 Observational and Unstructured Interviews 31 3.2 Designing the Training Content 33 3.2.1 Co-design workshop - Idea Generation 34 CHAPTER 4 IMPLEMENTATION 42 4.1 Software 42 4.1.1 Game Design Engine 42 4.1.2 Creating Game Object and Character 43 4.1.3 Stimulus Interaction Design 49 4.1.4 Time Parameter Input and Interface Design 52 4.1.5 After Time Showing (Reaction Time) Function 54 4.2 Hardware 55 4.2.1 Presenting the Virtual Object of Training Game 57 4.2.2 Creating Mock-up for Display Device 58 4.2.3 Looking for Carpenters to Discuss Feasibility 60 4.2.4 Construct the Display Device 61 4.3 Integration of Hardware and Software 63 4.3.1 Hardware Assembly 63 4.3.2 Software Interface – Whack a Mole Apps 66 CHAPTER 5 EVALUATION 70 5.1 Experiment Design 70 5.1.1 Attendance 70 5.1.2 Material 70 5.1.3 Equipment 70 5.1.4 Procedure 73 5.1.5 Pretest Phase 73 5.1.6 Training Phase 75 5.1.7 Unstructured Interview 77 5.2 Result 78 5.2.1 Statistical analysis of Posner’s Task and Whack a Mole 79 5.2.2 Group Statistics – Independent Sample Test of seniors and Adults Participants 81 5.2.3 Whack a Mole in Button Mode 84 5.2.4 Statistical analysis of Posner’s Task and Whack a Mole Button Mode Mean 85 5.2.5 Questionnaire and Unstructured Interview Results 89 CHAPTER 6 DISCUSSION AND CONCLUSION 92 6.1 Implementation of AR based Whack a Mole Training Game 92 6.1.1 Software 92 6.2 Implication of Reaction Time and Error Rate. 93 6.2.1 Whack a Mole Training with Visual Spatial Attention 93 6.2.2 Error Rate of Whack a Mole 93 6.2.3 Reaction Time of Posner’s Task and Whack a Mole Task 94 6.2.4 Group Statistics Result 94 6.2.5 Questionnaire and Unstructured Interview Results 95 6.3 Conclusion 95 REFERENCES 97 Appendix A Questionnaire of posner’s task 104 Appendix B Questionnaire of whack a mole 106

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