[[alternative]]Applying G-sensor to detect the human upper limb movement

[[abstract]]人體感測網路是一種新興的技術，於人機介面的狀態下，可以蒐集到更多的資訊。同時也帶來了新的挑戰，要如何利用這些感應器，用於人體資訊。本論文研究目的有二：一是設計出結合加速度感測器(G-sensor)的系統，配合著3D 模擬軟體在螢幕中呈現3D 的人體模擬圖。二是將所蒐集到的資料，判斷人體上肢往上、往下、內縮、外擴以及畫圓圈的姿勢。設計和實作無線感應器節點的加速度運動捕捉系統，由一個三軸加速度感應元件(包括微控制器和無線收發器)，我們特別針對人體上肢的反應放置了三個節點(肩關節、肘關節、手腕關節)。將蒐集的資料加以處理，利用最長共同子字串演算法 ( Longest CommonSubsequence)來估算出上肢姿勢狀態。透過這次的實驗顯出加速度感測器放置在人體上的可行性以及是適合與人機介面的應用。[[abstract]]The Body Area Sensor Network is a new technology to collect more vital sign information. Research on this paper has two purposes: First, this thesis implements a 3D body simulation video combined with the G-sensors system to demonstrate the hand motion. Second, this thesis also recognizes the actions about hand motion by analyzing the G-sensor data. These recognized actions include human upper limb up, down, internal shrinkage, enlargement and drawing circular. The thesis employs three zigbee-based G-sensor modules placed at a person’s shoulder, elbow, and wrist joint to capture hand motions. We also apply the LCS (longest Common Subsequence) toanalyze those captured motion data from the G-sensor modules. Through this experiment shows that the acceleration sensor placed on the viability of the human body is suitable for applications with Human Computer Interfaces