The main objective of this research study is to enhance the functionality of an Android pattern lock application by determining whether the time elements of a touch operation, in particular time on dot (TOD) and time between dot (TBD), can be accurately used as a biometric identifier. The three hypotheses that were tested through this study were the following–H₁: there is a correlation between the number of touch stroke features used and the accuracy of the touch operation biometric system; H₂: there is a correlation between pattern complexity and accuracy of the touch operation biometric system; H₃: there is a correlation between user training and accuracy of the touch operation biometric system. Convenience sampling and a within-subjects design involving repeated measures were incorporated when testing an overall sample size of 12 subjects drawn from a university population who gave a total of 2,096 feature extracted data. Analysis was done using the Dynamic Time Warping (DTW) Algorithm. Through this study, it was shown that the extraction of one-touch stroke biometric feature coupled with user training was able to yield high average accuracy levels of up to 82%. This helps build a case for the introduction of biometrics into smart devices with average processing capabilities as they would be able to handle a biometric system without it compromising on the overall system performance. For future work, it is recommended that more work be done by applying other classification algorithms to the existing data set and comparing their results with those obtained with DTW.

中文翻译：

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增强触摸操作生物识别系统的准确性：以Android模式锁定方案为例

这项研究的主要目的是通过确定触摸操作的时间元素，特别是点上时间（TOD）和点间时间（TBD），是否可以准确地用作以下内容，来增强Android模式锁定应用程序的功能：生物识别符。通过本研究检验的三个假设为：H ₁：所使用的触摸笔触特征数量与触摸操作生物识别系统的准确性之间存在相关性；H ₂：图案复杂度与触摸操作生物识别系统的准确性之间存在相关性；高₃：用户培训与触摸操作生物识别系统的准确性之间存在关联。当测试从大学人口中抽取的12个受试者的总体样本量时，便进行了便利采样和涉及重复测量的受试者内部设计，这些受试者总共提供了2,096个特征提取数据。使用动态时间规整（DTW）算法进行了分析。通过这项研究，结果表明，一键式笔触生物特征的提取与用户培训相结合，能够产生高达82％的高平均准确度。这有助于将生物识别技术引入具有平均处理能力的智能设备中，因为它们将能够处理生物识别系统而不会损害整体系统性能。为了以后的工作，