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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/102556

    Title: A step counting algorithm for smartphone users : design and implementation
    Other Titles: 適用於智慧型手機之步伐計算演算法之設計與實做
    Authors: 林學偉;Lin, Huseh-Wei
    Contributors: 淡江大學資訊工程學系碩士班
    Keywords: 加速度計;步態分析;智慧型手機;步數計算;Accelerometer;gaint analysis;Smartphone;step counting
    Date: 2014
    Issue Date: 2015-05-04 09:58:45 (UTC+8)
    Abstract: 近幾年來,智慧型手機已成為我們日常生活中的一環,其中,使用者的行走步數對於室內定位和健康照護等是一重要資訊,然而目前所提出的步伐計算大多需要限制使用者以固定放式持有手機,或是於行走中無法自然地使用手機,上述這些限制與一般使用者使用手機行為模式不符且於使用上非常不便。因此在本論文中,我們設計一新穎的步伐計算演算法,可以減輕上述之使用手機的限制且能準確地計算使用者行走步數。我們所提出的演算法可分成兩個部分,第一個部分透過手機中之加速度計蒐集線性加速度和重力加速度,接下來利用重力加速度及座標軸旋轉之概念來取得手機相對於水平面之傾斜角度,得到與水平面之角度後,藉由所計算之角度來推估所感測到之線性加速度數據映射於水平面之線性加速度數值。經由此模組之轉換後,所感測到之線性加速度感測數值將皆以水平方向為基準,接下來偵測使用者可能開始移動的起始點。第二個階段透過相關係數的概念去辨識前述所得之線性加速度資料中是否有相似的趨勢,藉此計算腳步。我們的實做結果顯示,我們所設計之方法可以區分不同的步態且精確地判斷出使用者行走之步數。
    In recent years, smartphones have become the most popular devices in our daily lives. The step count is an important information for developing services for smartphone users, e.g., indoor localization and health management. Most step counting solutions restrict that (i) the phone has to be fixed to the user and (ii) the user cannot use the phone naturally while walking. We can see that these restrictions are inconvenient for users. In this paper, we propose an adaptive step calculation algorithm, which can relieve the above restrictions and can count users'' steps precisely. The proposed algorithm is composed by two phases. The first phase collects linear acceleration and gravity values from the smartphone''s accelerometer. Then, this phase transforms the perceived linear acceleration values to parallel with horizontal plane and identifies possible start points of periodical regular fluctuations (of linear acceleration measurements). The second phase adopts the concept of correlation coefficients to identify whether the collected sensing measurements exhibit similar tendencies, and then calculates step counts. In this work, we implement the proposed method on the Android platform. The experiment results indicate that the proposed scheme can accurately divide gait changes and effectively identify steps.
    Appears in Collections:[資訊工程學系暨研究所] 學位論文

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