CSR: Small: Wireless Systems as Gesture Sensors

在过去的二十年里，支持移动设备的无线信号迅速激增，例如Wi-Fi和蜂窝。因此，无线信号在我们的环境中变得无处不在--在家里、在工作中，现在甚至在飞机上。这个项目的目标是利用我们周围的这些信号来实现新颖的传感应用，例如手势识别。手势识别系统允许用户通过手、手臂、腿等的动作来控制设备。这项研究专注于使用无线信号来实现目前无法实现的手势感知功能，特别是(1)在家庭中不需要特定运动检测器(如摄像头或用户手持设备)的手势识别，以及(2)可以在无电池设备上操作的手势识别。该项目将解决有关利用现有无线信号提取丰富的传感信息的可行性和局限性的基本问题，并将探索与通信和雷达理论的深层联系。这项工作有可能启发新系统的设计，这些系统可以在多个领域开辟新的研究问题，包括泛在计算、移动系统、计算机网络和人机交互。提出的跨学科研究采用了一种新的方法，利用现有的无线系统来实现新的应用，如手势感知和识别。该项目将产生算法、电路、传感器、设计和系统实现来实现这一目标。该项目还将开发无电池的手势传感器，仅使用从电视和蜂窝传输等周围无线来源收集的电力就可以工作。此外，这些设计将与智能手机和平板电脑等现有移动设备集成，以演示在这些功率受限的设备上始终在线感知。该项目还将开发分类算法，这些算法可以完全在低功耗微控制器上运行，而不会消耗大量电力。此外，这项研究将为从通信信号中提取信息奠定算法基础，这些通信信号针对高吞吐量(例如，基于ofdm的Wi-Fi和蜂窝传输)进行了优化，以实现全家手势识别和无电池手势识别等丰富的传感功能。最后，该项目演示了两个主要应用：可靠的指点手势识别(用户沿不同方向指点以激活设备)和穿透口袋手势识别，用户可以在口袋中对着手机手势，例如改变音量或将手机静音。

Over the past two decades there has been a rapid proliferation of wireless signals, such as Wi-Fi and cellular, that support mobile devices. As a result, wireless signals have become ubiquitous in our environment -- at home, at work, and now even on airplanes. The goal of this project is to leverage these signals around us to enable novel sensing applications, such as gesture recognition. A gesture recognition system allows users to control devices using movements of their hands, arms, legs, etc. This research focuses on using wireless signals to achieve gesture-sensing capabilities that are currently impossible, particularly (1) gesture recognition in the home without the need for specific movement detectors (such as cameras or user-held devices), and (2) gesture recognition that can operate on battery-free devices. The project will address fundamental questions about the feasibility and limits of using existing wireless signals for extracting rich sensing information, and will explore deep connections to both communication and radar theory. This work has the potential to inspire the design of novel systems that can open up new research questions in multiple domains, including ubiquitous computing, mobile systems, computer networking, and human-computer interaction.The proposed inter-disciplinary research takes a novel approach of leveraging existing wireless systems to enable novel applications such as gesture sensing and recognition. The project will produce algorithms, circuits, sensors, designs, and system implementations to achieve this goal. The project will also be developing battery-free gesture sensors that can work using only harvested power from ambient wireless sources like TV and cellular transmissions. Further, these designs will be integrated with existing mobile devices such as smartphones and tablets to demonstrate always-on sensing on these power-constrained devices. The project will also develop classification algorithms that can run entirely on low-power micro-controllers without consuming significant amounts of power. Further, this research will lay the algorithmic foundations for extracting information from communication signals optimized for high-throughput (e.g., OFDM-based Wi-Fi and cellular transmissions) to enable rich sensing capabilities like whole-home gesture recognition and battery-free gesture recognition. Finally, the project demonstrate two main applications: reliable pointing gesture recognition (where the user points along different directions to activate devices) and through-the-pocket gesture recognition where the user can gesture at the phone in a pocket, e.g., to change volume or mute the phone.