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Activity Recognition using wearable computing

机译:使用可穿戴计算的活动识别

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摘要

A secure, user-convenient approach to authenticate users on their mobile devices is required as current approaches (e.g., PIN or Password) suffer from security and usability issues. Transparent Authentication Systems (TAS) have been introduced to improve the level of security as well as offer continuous and unobtrusive authentication (i.e., user friendly) by using various behavioural biometric techniques. This paper presents the usefulness of using smartwatch motion sensors (i.e., accelerometer and gyroscope) to perform Activity Recognition for the use within a TAS. Whilst previous research in TAS has focused upon its application in computers and mobile devices, little attention is given to the use of wearable devices - which tend to be sensor-rich highly personal technologies. This paper presents a thorough analysis of the current state of the art in transparent and continuous authentication using acceleration and gyroscope sensors and a technology evaluation to determine the basis for such an approach. The best results are average Euclidean distance scores of 5.5 and 11.9 for users' intra acceleration and gyroscope signals respectively and 24.27 and 101.18 for users' inter acceleration and gyroscope activities accordingly. The findings demonstrate that the technology is sufficiently capable and the nature of the signals captured sufficiently discriminative to be useful in performing Activity Recognition.
机译:由于当前的方法(例如PIN或密码)存在安全性和可用性问题,因此需要一种安全,方便用户的方法来在其移动设备上对用户进行身份验证。已引入透明认证系统(TAS),以通过使用各种行为生物识别技术来提高安全级别,并提供连续和不干扰的认证(即用户友好)。本文介绍了使用智能手表运动传感器(即加速度计和陀螺仪)执行活动识别以供在TAS中使用的有用性。尽管先前在TAS上的研究集中于其在计算机和移动设备中的应用,但对可穿戴设备的使用却很少关注-可穿戴设备往往是富含传感器的高度个人化技术。本文使用加速和陀螺仪传感器对透明和连续身份验证中的现有技术进行了全面的分析,并进行了技术评估以确定这种方法的基础。最好的结果是用户的内部加速度和陀螺仪信号的平均欧几里德距离得分分别为5.5和11.9,用户的内部加速度和陀螺仪活动的平均欧几里德距离得分分别为24.27和101.18。研究结果表明,该技术具有足够的能力,并且所捕获的信号的性质具有足够的判别力,可用于执行活动识别。

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