EmoSense：基于无线信道数据的计算智能驱动的情感感知
EmoSense: Computational Intelligence Driven Emotion Sensing via Wireless Channel Data
摘要：
情感是人类的一种标志，在我们的日常生活中起着至关重要的作用。现有的基于视觉或基于传感器的解决方案要么阻碍使用，要么依赖于专用硬件，阻碍了它们的适用性。本文介绍了一种由计算智能驱动的无线情感感知系统--基本方法是通过数据采掘从无线信道响应中探索情感的物理表达。该系统的设计和实现面临两大挑战：从无线信道数据中提取身体表情和从相应的身体表情中恢复情感。对于前者，我们提出了一个基于菲涅尔区的理论模型，描述了信道响应的物理表达式的指纹。对于后者，我们设计了一个有效的计算智能驱动的机制，从相应的指纹识别情感。我们在商品WiFi基础设施上原型化了WiFi Sense，并将其与现实世界场景中主流的基于传感器和基于视觉的方法进行了比较。对$3360$案例的数值研究证实，在不同的场景下，基于视觉和基于传感器的竞争对手，智能感知实现了相当的性能。智能感知只利用低成本和普遍的WiFi基础设施，因此构成了一个诱人的情感感知解决方案。
英文摘要：
Emotion is well-recognized as a distinguished symbol of human beings, and it plays a crucial role in our daily lives. Existing vision-based or sensor-based solutions are either obstructive to use or rely on specialized hardware, hindering their applicability. This paper introduces EmoSense, a first-of-its-kind wireless emotion sensing system driven by computational intelligence. The basic methodology is to explore the physical expression of emotions from wireless channel response via data mining. The design and implementation of EmoSense {face} two major challenges: extracting physical expression from wireless channel data and recovering emotion from the corresponding physical expression. For the former, we present a Fresnel zone based theoretical model depicting the fingerprint of the physical expression on channel response. For the latter, we design an efficient computational intelligence driven mechanism to recognize emotion from the corresponding fingerprints. We prototyped EmoSense on the commodity WiFi infrastructure and compared it with main-stream sensor-based and vision-based approaches in the real-world scenario. The numerical study over $3360$ cases confirms that EmoSense achieves a comparable performance to the vision-based and sensor-based rivals under different scenarios. EmoSense only leverages the low-cost and prevalent WiFi infrastructures and thus constitutes a tempting solution for emotion sensing.
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