Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/90439
DC FieldValueLanguage
dc.contributor陳焜燦zh_TW
dc.contributor.author賴辰哲zh_TW
dc.contributor.authorChen-Che Laien_US
dc.contributor.other應用數學系所zh_TW
dc.date2015zh_TW
dc.date.accessioned2015-12-09T06:30:07Z-
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dc.identifier.urihttp://hdl.handle.net/11455/90439-
dc.description.abstractObesity is one of the serious problem in the modern world, and pose a serious impact with human in the future. It can cause many deadly diseases, such as: heart disease, diabetes, etc. Physical activity is strongly important solution to reduce the threat of obesity. It is difficult to quantify the energy consumed of the activities, while the accelerometer is a kind of tool to tell the user the amount of energy consumed. Type of activity, intensity and duration can affect the body's energy consumption, so this research proposes an identification of distinguishing the gait of walking and up the stairs. All of the 20 young subjects that were age of 22.7 ± 2.1 years old, height 170.7 ± 6.5 centimeters and weight 67.9 ± 12.1 kilograms. They wear three-axis accelerometer on the left ankle, using the sampling frequency is 200Hz and the sensitivity is 68count/(m/s^2) to collect acceleration signal. We found out that the acceleration signal of subjects were quite different in walking and walking up the stairs. In this research, we used nine statistical parameters (maximum, minimum, mean, standard deviation, range, sum, median, skewness and kurtosis), the threshold, using the relationship between the parameters entering perceptron to calculate decision boundary , then do the gait recognition. The accuracy of the results were over 90%. Therefore, this research proposed a simple and effective method of gait recognition. Keywords:gait recognition、perceptron、decision boundaryen_US
dc.description.abstract肥胖為現代世界一項很嚴重的健康問題,並對未來人類的生活造成很嚴重的影響。肥胖會造成許多致命的疾病,例如:心臟病、糖尿病等,為了要減少肥胖對身體健康所造成的威脅,身體活動是一個非常重要的解決方法。但人們卻很難量化活動所消耗的能量,而加速度計是一個可提供使用者所消耗能量的工具。 活動的類型、強度與持續的時間會影響人體的能量消耗,故本研究提出一種分辨走路與上樓梯的步態辨識方法。以20名受測者平均年齡22.7±2.1歲,身高170.7±6.5公分,體重67.9±12.1公斤的年輕人為實驗對象,以三軸加速度計配戴於腳踝關節上進行實驗,採用取樣頻率200Hz,靈敏度68count/(m/s^2)的設定收集加速度訊號。 發現受測者在走路與上樓梯時的加速度訊號有著明顯的差異,本研究利用九項統計參數(最大值、最小值、平均數、標準差、值域、總和、中位數、偏度與峰度)與門檻值,以及利用參數間的關係輸入感知機(perceptron)計算出決策邊界(decision boundary),進而做到行走步態的辨識,其結果的準確率高達90%以上。故本研究提出一個簡單且有效的步態辨識方法。 關鍵字:步態辨識、感知機、決策邊界zh_TW
dc.description.tableofcontents誌謝辭 i 摘要 ii Abstract iii 目錄 iv 圖目錄 v 表目錄 vi 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 5 第三節 論文架構 6 第二章 文獻討論 7 第一節 身體活動量與加速度計之文獻探討 7 第二節 步態辨識之文獻探討 8 第三章 研究方法 12 第一節 研究對象 12 第二節 研究設備 13 第三節 實驗流程 16 第四節 活動型態辨識 17 第五節 統計分析 20 第四章 研究成果 21 第一節 人體物理參數 21 第二節 加速度訊號分析 22 第三節 步態辨識 24 第四節 數據驗證 29 第五章 討論 33 第一節 研究對象與加速度計配戴位置 33 第二節 參數選擇與文獻比較 35 第三節 辨識方法與文獻比較 36 第六章 結論與建議 38 第一節 結論 38 第二節 建議 38 參考文獻 39 附錄一 45zh_TW
dc.language.isozh_TWzh_TW
dc.rights同意授權瀏覽/列印電子全文服務,2018-07-17起公開。zh_TW
dc.subject步態辨識zh_TW
dc.subject感知機zh_TW
dc.subject決策邊界zh_TW
dc.subjectgait recognitionen_US
dc.subjectperceptronen_US
dc.subjectdecision boundaryen_US
dc.titleGait identification using cumulants of ankle accelerometeren_US
dc.title應用腳踝加速規之累積量於步態辨識zh_TW
dc.typeThesis and Dissertationen_US
dc.date.paperformatopenaccess2018-07-17zh_TW
dc.date.openaccess2018-07-17-
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