连续信号模式分类中的范式转换：两轮移动机器人的移动乘骑辅助系统
Paradigm Shift in Continuous Signal Pattern Classification: Mobile Ride Assistance System for two-wheeled Mobility Robots
摘要：
在这项研究中，我们描述了可以在广泛的智能手机和平板电脑上实现的乘坐辅助应用程序的开发。行驶辅助应用程序具有信号处理和模式分类模块，可为实时信号模式分类提供几乎100%的识别准确度。我们引入了一个新的框架来构建一个具有压倒性辨别能力的训练字典，它消除了人工干预在训练样本上发现模式的需要。我们通过提供另一项研究的结果来验证所提出的方法的识别准确性，在该研究中，手的姿势和手势被跟踪和识别用于操纵机器人轮椅。
英文摘要：
In this study we describe the development of a ride assistance application which can be implemented on the widespread smart phones and tablet. The ride assistance application has a signal processing and pattern classification module which yield almost 100% recognition accuracy for real-time signal pattern classification. We introduce a novel framework to build a training dictionary with an overwhelming discriminating capacity which eliminates the need of human intervention spotting the pattern on the training samples. We verify the recognition accuracy of the proposed methodologies by providing the results of another study in which the hand posture and gestures are tracked and recognized for steering a robotic wheelchair.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
