本研究針對不需透過其他控制媒介的「手勢輸入」技術為基礎，並藉由現有最具未來家庭影音多媒體趨勢的微軟MCE(Media Center Edition媒體中心)作業系統來作為測試的平台。透過使用者實際使用，去獲知操作鍵在使用者心中的相關語彙與評估，接著透過文獻整理、MCE介面操控與功能分析，在設計階段裡把所有資料整合起來，讓設計人員(人因專家、符號圖形相關設計人員)以手語分類中的自然手語(「形」類)和文法手語(「音」類)分類的方法和邏輯，創造出每類各三個共有150個針對指令的新式手勢輸入符號，在經過60份有效問卷篩選出各一套50個最符合使用者心目中的手勢來讓受測者進行學習和測驗。

在實驗階段裡，挑選二十位受測者(男女各半)進行三次學習訓練，過程中透過測驗去獲知受測者對於指令手勢的辨識度、操作效能、反應時間和喜好度的數據，加以分析評估後得知：經過一次學習後，文法手語類(「音」類)全數的手勢指令都達到國際標準組織ISO建議的公共標誌設計67％以上的正確識認率標準，且本研究發展出的50個手勢，有48個達到此水準，在第二次測驗裡，全數指令手勢皆達到標準，且辨識率高達98.5%。檢視成績曲線圖可知代表著按照文字構造和符號組成的「音」類文法手語手勢有著較以姿勢、模仿動作組合而來的「形」類自然手語手勢有著比較好的辨識率，本研究發現到如要減少混淆，則「形」類的手勢應避免同樣位置的手勢，和語意不清的情況發生，另外「音」類手勢應避免重複出現相同的文字或符號。另外在操作性上，自然手語的發展邏輯讓受測者較容易接受，但是文法手語的發展邏輯給受測者較好的辨識效果，但在執行上比自然手語類型稍具難度。在反應時間總平均上，「形」類手勢為3.09秒略快於「音」類手勢的3.34秒，對照辨識率，發現到容易混淆的手勢會造成較長的反應時間。「形」類手勢當中混淆度與喜好度的關連性不大，但在「音」類的手勢當中，混淆度高的手勢會較不被受測者喜愛。在功能分組的分析裡「形」類快捷功能指令的反應時間明顯較「音」類快捷功能指令反應時間快；而「音」類影音控制指令的反應時間明顯較「形」類影音控制指令反應時間快，另外發現到「音」類指令手勢的「影音操作功能」和「文字/頻道輸入功能」的反應時間都較快於「快捷功能」。在功能分組的分析裡，「形」類快捷功能指令的喜好度明顯較「音」類快捷功能指令高；「音」類文字輸入指令的喜好度明顯較「形」類文字輸入指令高，另外發現到受測者對於「音」類手勢裡的「基本操作功能」和「影音操作功能」的喜好度都較優於「快捷功能」。最後評估辨識度、功能分組間的反應時間、喜好度等校標，選出最適於MCE作業系統的手勢為「形」類的快捷功能手勢和「音」類的基本操作功能、影音操作功能和文字/頻道輸入功能的組合最為理想。

Nowadays, home multimedia application is highly developed and the development of human-centered interface is getting important. This study focused on the technology of gestural input recognition and adopted Microsoft XP Media Center Edition Operating System(MCE) as an experimental environment. This study collected users’ extended language and evaluation of MCE functional commands by surveys and interviews, and then combined the results with references to design new gestural input symbols. The symbols were designed by several experts including ergonomic specialists and graphic designers. According to the principles of sign language (the language for silent people), they created 150 symbols which have two assorted types (grammatical gestures and natural gestures). After that, there were 50 best symbols (25 for each type) selected by 60 people.

In the process of learning new gestural symbols, the data of recognition, operation, reaction time and mental chart was recorded and evaluated by staffs. In the first test, the results revealed that all grammatical gestures passed the standard of ISO which means the criteria (67% recognition rate from participants) as public symbols. In the second test, all symbols passed this standard. After analyzing the results, we found that the recognition of grammatical gestures can be promoted if they have different position factors, and the natural gestures can be promoted if they have different character or icon factors. During the actual operation, the performances of natural gestures are better then grammatical gestures. About the reacting time, natural types (mean: 3.09sec) are faster then grammatical types (mean: 3.34sec). About the influences among different function groups, in quick function group, the reaction time of natural gestures are faster then grammatical gestures, in AV (audio-video) function group, grammatical gestures are faster then natural gestures. To discuss grammatical gestures independently, AV function group and key-in function group are both faster then quick function group. Discussion about the preference of symbols, participants prefer the quick function group of natural gestures and the key-in function group of grammatical gestures. Also, in grammatical gestures, participants more like basic function group and AV function group than quick function group. In the end, according to the evaluation of recognition, reaction time and preference, this study chose the best suite of symbols for MCE. They are quick function symbols of natural gestures and the other functions including basic, AV and key-in functions of grammatical gestures.

Barber ,C., Wankling, J., An Experimental Comparison of Text and Symbols for In-Car
Reconfigurable Displays, Applied Ergonomics23(4), pp255-262, 1992

Cassinelli, A., Perrin, S., Ishikawa, M., Smart Laser-Scanner for 3D Human-Machine Interface, ACM SIGCHI 2005 (CHI '05) International Conference on Human Factors in Computing Systems, Portland, OR, USA April 02 - 07, pp1138 - 1139, 2005

Chen, Y. T., Dengchuan, C., Huang, H. F., Jane, K., An Evaluation Model for Graphic
Design Works, Department of Industrial Design, National Yunlin University of Science
and Technology, Doului, Yunlin, Taiwan 640, R.O.C, 2002.

Drefus, W. (ed.), The Measure of Man: Human Factors in Design, Second Edition, Whitney Library of Design, New York, 1967

Fisher, J., Testing the Effect of Road , Traffic sing Information Value on Driver Behavior, Human Factors34, pp231-237, 1992

Foley, J. D., Wallace, V. L., Chan, P., The Human Factors of Computer Graphics Interaction Technique, IEEE Computer Graphic and Application, pp13-48, 1984

Frantz,J. P., Miller, J. M., Lehto, M. R., Must the Context Be Considered When Applying Generic Safety Symbols :A Case Study in Flammable Contact Adhesives ,Journal of Safety Research22, pp147-161, 1991

Gittins, D., 1986, Icon-based Human-Computer Interaction , International Journal of man-Machine Studies,Vol.24, pp.519-543.

Goldman, A. E. MacDonald, S. S., The Group Depth Interview: Principles and practices, Prentice Hall, Englewood Cliffs, NJ., 1987

Greenbaum, T. L., The Handbook for Focus Group Research. Lexington Books, NY., 1993

Hunt, J. M., The Rehabilitation of the hand, 3rd. ed, St Louis Mosby, ISBN080162472X, 1990

Kroemer, G., The pro-oncogene Bcl-2 and and its role in regulating apoptosis. Nature Medicine 3: pp614-620, 1997.

Kroemer, G., Mitochondrial control of apoptosis: an overview. In: Brown GC, et al(eds), Mitochondria and cell death. Cambridge University Press, Cambridge, pp1-16, 1999

Lam, W. C., Zou, F. and Komura, T., Motion Editing with Data Glove, ACM SIGCHI ACE2004 conference, Singapore, June, 2004

Neilson, J., Top Ten Mistakes in Web Design, Sunsoft Distinguished Engineer, 1996.
Caplan, S., Using focus groups methodology for ergonomic design, Ergonomic, Vol.33 No.5, pp527-533, 1990

Neilson, J., Usability Engineering. California: AP PROFESSIONAL Press., pp97-155, 1993.

Neilson, J., Usability Engineering. United Kingdom edition publish by Academic press-LTD, pp224, 1993

Nespoulous, J. L., Perron, P., Lecours, A. R., The Biological Foundations of Gestures: Motor and Semiotic Aspects, Lawrence Erlbaum Associates, Hillsdale, MJ, 1986.

Nordin, A. (ed.), Taxonomy and phylogeny of Buellia species with pluriseptate spores (Lecanorales, Ascomycotina),- Symb. Bot. Ups. 33(1): pp1-117, 2000

Norman, D. A., The Psychology of Everyday Things, New York: Basic Book Inc.

O’Donnell, P. J., Scobie, G. & Baxter I., The use of focus groups as an evaluation technique in HCI, People and Computers VI, Cambridge University Press, U.K.,pp211-214, 1991.

Oka K. and Sato Y., Real-Time Fingertip Tracking and Gesture Recognition
University of Tokyo Hideki Koike University of Electro-Communications, Tokyo, 2002

Pheasant, S. (ed.), Bodyspace: Anthropometry, Ergonomics and the Design of the Work, Second Edition, Taylor & Francis, London, UK, 1996

Piaget, J., Construction of reality in the child, London: Routledge & Kegan Paul, 1954

Plamondon, R., Srihari, S. N., On-Line and Off-Line Handwriting Recognition : a Compre-hensive Survey. IEEE Trans. On Pattern Analysis and Machine Intelligence. 22(1) pp63-84, 2000

Ritu, A., Jayesh, P., Michael, C. Z.,Training experience and usage intentions: a field study of a graphical user interface, Int. J. Hum.-Comput. Stud. 45(2), pp215-241, 1996.

Sanders, M. S., McCormick, E. J., Human factors in engineering and design, ISBN9579937249, 1996.
Schlenzig, J., Hunter, E., Jain, R., Vision based gesture interpretation using recursive estimation. In Asilomar Conference on Signals, Systems and Computers, 1994

Starner, T., “Visual Recognition of American Sign Language Using Hidden Markov Model”, Master’s Thesis, MIT Media Laboratory, February 1995

Sylvie C.W. Ong, Surendra Ranganath, Y.V. Venkatesh, Understanding gestures with systematic variations in movement dynamics, Pattern Recognition 39 pp1633–1648, 2006

Turing, M., Hannemann, J. , Haake, J. M., Hypermedia and Cognition: Design for Comprehension. Communications of the ACM38, pp57-66, 1995

Wallschlaeger, C., Basic Visual Concepts and Principles for Artists,
Architects and Designers, Times Mirror Pte Ltd,1996

Ware, C. (ed.), Information Visualization: Perception for Design, Second Edition, Morgan Kaufmann Publishers, San Francisco, 2004

Weimer, D., Ganapathy, S. K., Interaction techniques using hand tracking and speech recognition, Multimedia interface design, pp109-126, 1992

Wilson, A., and A. F. Bobick “Learning Visual Behavior for Gesture Analysis”, In Proceedings of the IEEE Symposium on Computer Vision, Coral Gables, Florida, November pp20-22, 1995

Whitaker,L. A., Sommer, R., Perception of Traffic Guidance sing Containing
Conflicting Symbol and Direction Information, Ergonomics29(5), pp699-711,
1986.
Zwaga, H. J., Boersema, T., Evaluation of a set of Graphic Symbols, Applied
Ergonomics14(1), pp43-54, 1983
Donald A. Norman，情感設計，田園城市文化事業有限公司，2005

史文漢，丁立芬，中華民國聾人協會手語叢書第一冊，民國八十六年一月第
十一版，中華民國聾人協會，台北市，1997.

李佳勳，「互動式媒體」-以感官多模式探討數位設計環境中人機互動介面設計與應用實例，成大建築所碩士論文，2002

林靜，家庭多媒體影音系統操作之手勢符號認知設計，成大工業設計研究所碩士論文，2006

姜明宏，人臉辨識系統之設計研究，國立中山大學碩士論文，2002
陳永祚，虛擬環境下即時三維手勢之介面系統，清華大學資訊工程所論文，2004

張春興編譯，教育心理學: 三化取向的理論與實踐，東華書局，pp85-97，1996

鄭璟鴻，網頁瀏覽指令圖示結合手勢輸入在認知上的設計與使用性評估，成大工業設計研究所碩士論文，2006

網站

http://www.k2.t.u-tokyo.ac.jp/

http://www.vkb-tech.com/

http://taiwan.cnet.com

http://www.intel.com