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    题名: 應用智慧型手機三軸加速度計於動作識別
    其它题名: Activity recognition with smartphone tri-axial accelerometer
    作者: 朱晉廷;Chu, Chin-Ting
    贡献者: 淡江大學資訊工程學系碩士班
    許輝煌
    关键词: 加速度感測器;陀螺儀;支持向量機;動作識別;Accelerometer;Gyroscope;Support Vector Machine;Activity recognition
    日期: 2015
    上传时间: 2016-01-22 15:03:34 (UTC+8)
    摘要: 人的動作識別一直以來都是一個重要的研究課題,方法也很多,例如在人體身上裝載著穿戴式的感測器進行動作識別,也有利用影像處理的方式進行動作識別,影像處理的辨識方式主要是固定在一個位置上進行識別,並不適用在針對個人的情形,在身上裝載穿戴式的感測器的方式,在行動上會有所不便,因此不適合用在對人進行長時間的偵測上。隨著智慧型手機的發展,以及其便利性,目前可以說是每個人都擁有一支智慧型手機,加上手機內搭載著多種感測器,以及處理運算能力,這使得智慧型手機很適合用來取代穿戴式的感測器來進行長時間的動作識別,相關的研究及應用也越來越多。但是在這些研究中,很多都存在著一些限制,例如需要固定手機在身上的某個位置,可能是褲子前口袋或上衣口袋…等,或需要固定手機的方向不能旋轉,這些限制在日常生活的應用上會很不方便,因此在本篇論文中,我們提出了一個基於手機位置的動作識別的系統,首先我們會利用陀螺儀將手機位置分成三類,根據手機位置不同會使用不同的分類模型,用這個方法解決限制手機位置的問題,之後再利用手機內的三軸加速度計抓取加速度值,並將收集來的三軸加速度作平方和取得整體的加速度值,以此用來消除限制手機方向的問題,最後會利用支持向量機進行動作識別,識別的動作分別為走路、跑步、上樓梯、下樓梯和站/坐,並將動作及持續時間輸出在畫面上。根據實驗結果表明使用手機位置辨識的方法可以提升辨識準確率,且不管手機方向的影響,因此我們認為根據我們的方法所提出的動作識別系統可以解決手機位置和方向限制的問題。
    Human activity recognition is an important research topic, there are many solution such as using wearable sensor to human activity recognition, but also using image processing to human activity recognition. Image processing solution is in a fixed location to human activity recognition, does not apply to personal case. The solution of using wearable sensor to human activity recognition is inconvenient in action, therefore not suitable for use in long time detection. Along the development of smartphone, and its convenience. Currently it can be said that everyone has a smart phone, and the smartphone is equipped with a variety of sensors, and processing operations ability. This makes the smartphones very suitable replace wearable sensors for long time activity recognition, related research and application is also increasing. However, in these research, many of them have some restrictions, for example, the smartphone needs to be fixed at some location, like pants pocket or jacket pocket ... etc. or needs to be fixed direction. These restrictions apply in daily life will be very inconvenient, therefore, in this paper, we propose an activity recognition system based on phone’s position recognition method, first we use the gyroscope to distinguish position, according to the position use different classification models, this step can solve the problem of restricted smartphone position, and then using tri-axial accelerometer inside the phone to get the acceleration value, and calculates the sum of squares of the tri-axis acceleration value to obtain the whole acceleration, these new feature can solve the problem of restricted smartphone orientation, finally, we use support vector machine to activity recognition, the active are walk, run, up-stair, down-stair, stand/sit, and the result and the time displays on the screen. The experimental results show that we used phone’s position recognition method can upgrade accuracy, and we can ignore the impact of phone’s orientation. Therefore, we believe that using our proposed activity recognition system can solve the problem of the restricted smartphone location and restricted smartphone direction.
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