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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/101656

    Title: 基於智慧型手機之跌倒偵測與三維計步器之設計與實現
    Other Titles: Design and implementation of fall detection and triaxial pedometer based on smartphone platform
    Authors: 陳建榮;Chen, Jian-Rong
    Contributors: 淡江大學資訊工程學系資訊網路與通訊碩士班
    Keywords: 跌倒偵測;三軸加速器;陀螺儀;計步器;智慧型手機;Fall detection;Three-axis Accelerometer;Gyroscope;Pedometer;Smart phone
    Date: 2014
    Issue Date: 2015-05-01 16:13:25 (UTC+8)
    Abstract: 本文利用智慧型手機內建之三軸加速感測器和地磁感測器來計算走路步數,最終目的為老年人之跌倒偵測。高齡族群使用智慧型手機接受度提高,使用智慧型手機內建之感測器進行偵測,可降低感測器大小及配戴多種感測器之不便,以手機內建的多種感測器得知使用者肢體動態計算步數與分析跌倒狀況是否發生,防止當跌倒發生時,無人在旁協助治療之情況。
    本文計步器演算法在分析三軸加速度量值於平地行走可達96%準確率,上樓梯可達90%準確率,下樓梯可達86%準確率,並可偵測使用者目前肢體動作以達更高之準確率,跌倒偵測改良Maarit Kangas等多位學者演算法,加入肢體動作分析,增加準確度避免因較激烈日常活動而產生跌倒誤判,增加使用者困擾。日常行走與起立坐下時不會有錯誤偵測跌倒警告,準確率達100%,整體跌倒偵測準確率可達88%。
    This thesis use two sensors tri-axial acceleration sensors and magnetic sensors in smartphone to calculate walking steps. The main purpose is for detecting of fall in the elderly. Due to the older adult’s acceptance attitude of using smartphone is improving, using sensor in smartphone to detect fall will reduce incommodiousness of carry, and the volume of sensor become smaller. With various sensors to detect fall, could know that the user''s calculating steps in dynamic and analyze the situation of fall will happen or not. In case the fall happened, no one help the elderly.
    The algorithm of pedometer analyzed the accuracy rate of three-axis acceleration, it may reach 96% in walking, 90% in going upstairs, and 86% in going downstairs, it also achieves a higher accuracy rate in the user''s physical action. The fall detection improved Maarit Kangas'' and other scholars'' algorithm. Adding the analysis of physical action raise the accuracy to avoid misjudgment of violent daily activities and use’s inconvenience. Daily walking, Standing up and sitting down will not warn the user of fall, the accuracy rate of whole fall detection may reach 88%.
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Thesis

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