近年來智慧型手機愈來愈普及，不僅運算能力強，智慧型手機上也搭載了多樣化的感應器，讓使用者能得到更多環境中的資訊，其中，磁感應器已成為智慧型手機上的標準配備。
　　本論文藉由分析智慧型手機上磁感應器的角度資料，計算出手機轉動的角速度、角加速度，來達到類似陀螺儀感應器的功能；我們還利用磁感應器偵測到的角度變化，推算出手機沿著同一軸向上的移動位移；最後我們將手機轉動的角度、角速度與角加速等資訊結合拉邦動作分析理論，對使用者的動作進行判斷與分類，藉此了解使用者的動作特性。

In recent years, smart phones become increasingly popular. More than having strong computing ability, smart phones are equipped with a variety of sensors. Users can get even more information by the sensors. Among the sensors, magnetic sensor has become the standard equipment on smart phones.
　　In this thesis, we analyze the rotational angle of magnetic sensor on smart phones and calculate the angular velocity and angular acceleration of the smart phones to achieve the capability which is similar to gyro sensor. The magnetic sensor is used to detect the change of the angle and to predict the displacement of the phones moving along the same axis. Finally, the rotational angle, the angular velocity, the angular acceleration of the smart phones and the LMA theory are integrated to determine and classify the users’ motion. Through this determination and classification, the characteristics of user’s motion can be found out.

第一章　緒論 ......1
1.1　研究動機及研究目的 ......2
1.2　論文架構 ......3
第二章　相關研究 ......4
2.1　光感應器應用於人體動作感測 ......4
2.1.1　Kinect ......4
2.1.2　Wii ......6
2.2　其他人體動作感測相關研究 ......9
2.3　拉邦動作分析 ......12
第三章　研究內容與方法 ......14
3.1　磁感應器 ......14
3.2　系統架構 ......17
3.3　手機轉動角速度、角加速度計算 ......18
3.3.1　角速度計算 ......19
3.3.2　角加速度計算 ......19
3.4　手機移動位移推算 ......20
3.5　使用者動作分析 ......29
3.5.1　Space ......31
3.5.2　Weight ......35
3.5.3　Time ......35
第四章　模擬實作與結果討論 ......36
4.1　模擬實作說明 ......36
4.1.1　模擬實作目標 ......36
4.1.2　模擬實作環境 ......36
4.1.3　模擬實作介面 ......37
4.2　模擬結果與討論 ......39
4.2.1　手機移動位移測量 ......39
4.2.2　使用者動作分析 ......41
第五章　結論與未來相關研究 ......45
5.1　結論 ......45
5.2　未來相關研究 ......46
參考文獻 ......47
附錄–英文論文 ......49

圖目錄
圖2.1　Light Coding技術 (Source：[PSRD 2010]) ......5
圖2.2　紅外線感測結合骨架追蹤系統 (Source：[Suma 2011]) ......6
圖2.3　Wii Remote控制器 (Source：[蔡亮宙 2010]) ......7
圖2.4　裝設了紅外線發送器的護目鏡跟原字筆 (Source：[Bharath 2010]) ......8
圖2.5　3D立體場景的視角轉換 (Source：[Bharath 2010]) ......8
圖2.6　互動式數位白板 (Source：[Bharath 2010]) ......8
圖2.7　裝在人體上的10個慣性感測器 (Source：[Arvind 2009]) ......10
圖2.8　分析Tango舞者的動作 (Source：[Arvind 2009]) ......10
圖2.9　磁感應器與慣性感應器的整合系統 (Source：[Fourati 2011]) ......11
圖3.1　磁感應器偵測方位角度示意圖 ......15
圖3.2　磁感應器偵測手機旋轉角度示意圖 ......16
圖3.3　Pitch、Roll正向旋轉角度示意圖 ......16
圖3.4　系統架構圖 ......17
圖3.5　手機位移方向示意圖 ......20
圖3.6　手機位移測量前的角度定位 ......21
圖3.7　可測量沿手臂方向的移動位移 ......21
圖3.8　測量手機移動位移 ......22
圖3.9　角度值介於0度到90度之間 ......23
圖3.10　角度值介於90度到180度之間 ......24
圖3.11　角度值介於180度到270度之間 ......26
圖3.12　角度值介於270度到360度之間 ......27
圖3.13　TAS波形平滑 (Source：[李冠霖 2009]) ......30
圖4.1　手機端實作介面 ......38
圖4.2　電腦端實作介面 ......38
圖4.3　電腦端波形平滑實作介面 ......39
圖4.4　手機移動位移測量 ......40
圖4.5　Indirect動作的角度變化 ......42
圖4.6　Direct動作的角度變化 ......43
圖4.7　Light、Strong角速度波形 ......44
圖4.8　Sustain、Sudden角加速度波形 ......44

表目錄
表3.1　每個時間點所偵測到的角度 ......31
表3.2　角度變化ΔA的誤判情況 ......32
表3.3　求出角度變化ΔA ......33
表3.4　求出P值 ......33
表3.5　求出C值 ......34
表4.1　手機系統模擬環境 ......37
表4.2　電腦系統模擬環境 ......37
表4.3　Indirect動作的角度紀錄表 ......41
表4.4　Direct動作的角度紀錄表 ......43

中文部份：
[李冠霖 2009] 李冠霖 (2009)。以拉邦理論為基礎用速率分析人體動作行為 (碩士論文)。取自http://etds.lib.tku.edu.tw/etdservice/view_metadata?etdun=U0002-0307200915084800&query_field1=&&query_word1=%A7%F5%ABa%C0M&
[蔡亮宙 2010] 蔡亮宙、張克遠 (2010)。手勢動作之機器人控制研究與實現。「2010電腦與網路科技在教育上的應用研討會」發表之論文，新竹教育大學。

英文部分：
[Arvind 2009] Arvind, D. K., & Valtazanos, A. (2009). Speckled Tango Dancers: Real-time Motion Capture of Two-Body Interactions using on-body Wireless Sensor Networks. 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks, 312-317.
[Ballagas 2006] Ballagas, R., Borchers, J., Rohs, M., & Sheridan, J. G. (2006). The Smart Phone: A Ubiquitous Input Device. IEEE Pervasive Computing, 5(1), 70-77.
[Bharath 2010] Bharath, L., Shashank, S., Nageli, V. S., Shrivastava, S., & Rakshit, S. (2010). Tracking method for Human Computer Interaction using Wii Remote. 2010 International Conference on Emerging Trends in Robotics and Communication Technologies (INTERACT), 133-137.
[Caruso 1997] Caruso, M. J. (1997). Applications of Magnetoresistive Sensors in Navigation Systems. SAE Transaction, 106, 1092-1098.
[Chen 2010] Chen, J. -F., Lin, W. -C., Tsai, K. -H., Lin, Y. -T., & Dai, S. -Y. (2010). Body Motion Analysis for E-Learning Based on Laban Movement Analysis. 2010 International Conference on University Basic Computers Education and eLearning, Tamkang University, Taiwan.
[Fourati 2011] Fourati, H., Manamanni, N., Afilal, L., & Handrich, Y. (2011, January). A Nonlinear Filtering Approach for the Attitude and Dynamic Body Acceleration Estimation Based on Inertial and Magnetic Sensors: Bio-Logging Application. IEEE Sensors Journal, 11(1), 233-244.
[Hashim 2010] Hashim, W. N. W., Noor, N. L. M., & Adnan, W. A. W. (2010). A Framework for Graceful Interaction: Applying Laban Effort Theory to Define Graceful Movement Quality. 2010 International Conference on User Science and Engineering (i-USEr), 139-144.
[Khoshhal 2010] Khoshhal, K., Aliakbarpour, H., Quintas, J., Drews, P., & Dias, J. (2010). Probabilistic LMA-based Classification of Human Behaviour Understanding Using Power Spectrum Technique. 2010 13th Conference on Information Fusion (FUSION), 1-7.
[Leyvand 2011] Leyvand, T., Meekhof, C., Wei, Y. -C., Sun, J., & Guo, B. (2011). Kinect Identity: Technology and Experience. Computer, 44(4), 94-96.
[Lin 2010] Lin, Z., Zecca, M., Sessa, S., Bartolomeo, L., Ishii, H., Itoh, K., & Takanishi, A. (2010). Development of an Ultra-miniaturized Inertial Measurement Unit WB-3 for Human Body Motion Tracking. 2010 IEEE/SICE International Symposium on System Integration (SII), 414-419.
[PSRD 2010] PrimeSensor Reference Design (2010). Retrieved from http://www.primesense.com/?p=514
[Rett 2008] Rett, J., Santos, L., & Dias, J. (2008). Laban Movement Analysis for Multi-Ocular Systems. 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 761-766.
[Roetenberg 2007] Roetenberg, D., Slycke, P. J., & Veltink, P. H. (2007, May). Ambulatory Position and Orientation Tracking Fusing Magnetic and Inertial Sensing. IEEE Transactions on Biomedical Engineering, 54(5), 883-890. 
[Suma 2011] Suma, E. A., Lange, B., Rizzo, A., Krum, D. M., & Bolas, M. (2011). FAAST: The Flexible Action and Articulated Skeleton Toolkit. 2011 IEEE Virtual Reality Conference (VR), 247-248.
[Zheng 2006] Zheng, P., & Ni, L. M. (2006, March). Spotlight: the rise of the smart phone. IEEE Distributed Systems Online, 7(3). Retrieved from http://ieeexplore.ieee.org/servlet/opac?punumber=8968.