CSR: Small: Wireless Systems as Gesture Sensors

CSR：小型：作为手势传感器的无线系统

• 批准号: 1420654
• 负责人: Shyamnath Gollakota
• 金额: $ 50万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1420654&HistoricalAwards=false
• 关键词: CSR; Small; Wireless; Systems; Gesture

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.

在过去的二十年中，支持移动的设备的无线信号（例如Wi-Fi和蜂窝）迅速增加。因此，无线信号在我们的环境中无处不在-在家里，在工作中，现在甚至在飞机上。该项目的目标是利用我们周围的这些信号来实现新的传感应用，例如手势识别。手势识别系统允许用户使用他们的手，手臂，腿等的运动来控制设备。这项研究的重点是使用无线信号来实现手势感应功能，目前是不可能的，特别是（1）手势识别在家里，而不需要特定的运动检测器（如相机或用户手持设备），（2）手势识别，可以在无电池的设备上运行。该项目将解决有关使用现有无线信号提取丰富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。这项工作有可能激发设计新的系统，可以打开新的研究问题，在多个领域，包括无处不在的计算，移动的系统，计算机网络和人机交互，建议跨学科的研究需要一种新的方法，利用现有的无线系统，使新的应用，如手势传感和识别。该项目将产生算法，电路，传感器，设计和系统实现，以实现这一目标。该项目还将开发无电池手势传感器，该传感器可以仅使用从电视和蜂窝传输等环境无线源收集的电力工作。此外，这些设计将与现有的移动的设备（如智能手机和平板电脑）集成，以展示这些功率受限设备上的始终在线感测。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，这项研究将为从针对高吞吐量优化的通信信号中提取信息奠定算法基础（例如，基于OFDM的Wi-Fi和蜂窝传输），以实现丰富的传感功能，如整个家庭手势识别和免电池手势识别。最后，该项目展示了两个主要应用：可靠的指向手势识别（其中用户沿着沿着不同的方向指向以激活设备）和通过口袋手势识别，其中用户可以在口袋中的手机上做手势，例如，改变音量或静音手机。