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首页> 外文期刊>Journal of signal processing systems for signal, image, and video technology >TouchSpeaker, a Multi-sensor Context-Aware Application for Mobile Devices: from Application to Implementation
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TouchSpeaker, a Multi-sensor Context-Aware Application for Mobile Devices: from Application to Implementation

机译：TouchSpeaker，用于移动设备的多传感器上下文感知应用程序：从应用程序到实现

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Tapping with your finger on any place on your mobile device is a promising candidate for enhanced interaction between users and their mobile device. So far the touchscreen and the accelerometer are commonly used to infer finger tap events. However, the touchscreen consumes a significant amount of power and is not always accessible (i.e., when the device is used as a running assistant). The accelerometer can be power efficient but can’t differentiate well between a variety of contexts and positions. To address these limitations, we present TouchSpeaker, a novel technique for finger tap detection on mobile devices using the built-in speakers as primary sensors. We show that a combination of the speakers with other built-in sensors can distinguish between 9 different tap events with an accuracy of 98.3%, outperforming the state of the art. In addition, a robust version is implemented resulting in a false positive rate below 1%. For power constrained devices, we propose a configuration consisting of only the speakers and the accelerometer, achieving an accuracy of 95.2%.
机译：用手指轻触移动设备上的任何位置都是增强用户与其移动设备之间交互的有希望的选择。到目前为止，触摸屏和加速度计通常用于推断手指轻击事件。但是，触摸屏会消耗大量电量，并且无法始终访问（即，当设备用作运行助手时）。加速度计具有较高的能效，但无法很好地区分各种环境和位置。为了解决这些局限性，我们提出了TouchSpeaker，这是一种使用内置扬声器作为主要传感器的移动设备上的手指敲击检测的新技术。我们显示，扬声器与其他内置传感器的组合可以以98.3％的精度区分9个不同的轻拍事件，性能超过了现有技术。另外，实施了可靠的版本，导致误报率低于1％。对于功率受限的设备，我们提出一种仅由扬声器和加速度计组成的配置，可实现95.2％的精度。

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