研究生: |
張正昂 Chang, Cheng-Ang |
---|---|
論文名稱: |
觸控手機之操作手勢設計與評估 The Design and Evaluation of Gesture Input for Touch Mobile Phone |
指導教授: |
吳豐光
WU, Fong-Gong |
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: | 2011 |
畢業學年度: | 99 |
語文別: | 中文 |
論文頁數: | 115 |
中文關鍵詞: | 手機 、觸控面板 、操作手勢 、手勢符號 |
外文關鍵詞: | mobile phone, touch panel, gesture, sign |
相關次數: | 點閱:196 下載:2 |
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觸控面板的應用已越來越普及,但操作方式仍停留在取代按鍵的操作模式,未將觸控面板效能發揮到最佳,所以本研究主要研究在觸控手機視窗進行手勢符號的操控方式,也就是將觸控手機點選式的操作方式,轉換成書寫式的操作方式,以提供一套更人性化、更直覺的操作模式。
第一階段使用訪談法與觀察法找出手機常用功能指令,並利用KJ法將指令收斂成58個,然後從這58個指令中使用問卷調查,調查出最常用之15個功能指令,再將這些指令依文字與圖形等相關聯想,使每一個指令至少發展出6個平面操作的手勢符號,總共篩選出90個手勢進行下一階段實驗。第二階段再將這90個操作手勢進行實測調查,紀錄受測者實際操作後最喜愛之15個操作手勢,運用ANOVA檢定分析,檢定結果得知所有操作手勢p-value皆小於0.05,達到0.05 顯著水準,所以每個指令間的操作手勢皆有顯著差異性。
事後檢定使用Duncan Test分析,找出15個指令每個指令間,具同群組別之操作手勢,檢定完後增加15個具有同群組別之操作手勢(總共30個操作手勢)進行混淆度實驗。第一次混淆度實驗之15個指令共30個操作手勢,準確度最低的操作手勢準確率達85%,總體準確率為95.6%;第一次混淆度實驗另一個主要目的為,將每個指令間同組別之最佳操作手勢篩選出來進行第二次混淆度實驗測試。所以第二次混淆度實驗之15個指令已篩選為15個操作手勢,準確率最低的操作手勢已提高為95%,總體準確率更達到99%。進行卡方檢定後得知二次的混淆度測試p-value皆大於0.05,未達到0.05 顯著水準,表示這二次混淆度測試,每個操作手勢與前後次的操作手勢,在使用上會導致錯誤的情形,並沒有顯著的差異。
Although touch panel are being increasingly used, the design of the operational model is still based on the intention of replacing keypads. The potential of touch panels has not been put into full play. This study aims to explore the use of finger gestures/symbols on touch-screen mobile phones to activate certain functions, in other words, by handwriting instead of tapping, in order to develop a more user-friendly, instinctive design.
In the first stage, interview and observation methods were employed to determine the common function commands of mobile phones. The results were organized and grouped with the KJ method (totaling 58). Among which, 15 of the most commonly-used ones were selected via a questionnaire survey. From the vocabulary, symbols and images with which users can associate, 15 commands were adapted into six corresponding finger gestures to create 90 gestures. In the second stage, the 90 gestures were examined by research subjects; the 15 gesture types they deemed optimal were recorded and analyzed through analysis of variance (ANOVA). The p-value of each gesture is lower than 0.05, the level of significance, so the results indicate that there are significant differences between the gestures of the commands herein explored.
A post-hoc analysis was conducted with Duncan’s Test. One gesture was selected from each of the 15 commands. Then, another 15 gestures for each command (totaling 30) were added for an analysis of confusion these gestures may cause. In the first confusion analysis of the 30 gestures (15 commands each), the gestures correctly identified the least reached 85% of being successfully identified. The overall percentage of the gestures were identified was 95.6. Another objective of the first confusion analysis was to select the optimal gestures for each command in the second confusion analysis. Therefore, in the second confusion analysis, 15 gestures out of 15 commands each were obtained. The gesture correctly identified the least had reached 95% of being successfully identified and the overall percentage of the gestures were identified at a high of 99%. A Chi-square test was conducted and found that the p-value among the gestures in the two confusion analyses all exceeded 0.05, the level of significance, showing no significant difference in failing to identify the gestures.
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