@inbook{f248c5440d2b4192bab011cff3029ee9,
title = "Wi-Fi-based sensing for gesture control applications",
abstract = "This chapter introduces a Wi-Fi-based sensing technology that is able to detect and recognize hand gestures with Wi-Fi signals. It covers the underlying theory and state-of-the-art sensor systems. It also demonstrates several gesture control applications with the additional use of machine learning and sensor fusion techniques.",
keywords = "Gesture recognition, Hand gesture control applications, Hand gesture detection, Hand gesture recognition, Learning (artificial intelligence), Machine learning, Sensor fusion, Sensor fusion technique, Telecommunication control, Wi-fi signals, Wi-fi-based sensing systems, Wireless LAN, Wireless sensor networks",
author = "Tang, \{Mu Cyan\} and Lai, \{Yi Chen\} and Lin, \{Min Hui\} and Chen, \{Chien Lun\} and Chou, \{Chuan Chi\} and Wang, \{Fu Kang\} and Yeh, \{Chia Hung\} and Li, \{Chien Jung\} and Horng, \{Tzyy Sheng Jason\}",
note = "Publisher Copyright: {\textcopyright} The Institution of Engineering and Technology 2019.",
year = "2019",
month = jan,
day = "1",
doi = "10.1049/PBCE125E\_ch3",
language = "English",
pages = "45--88",
booktitle = "Short-Range Micro-Motion Sensing with Radar Technology",
publisher = "Institution of Engineering and Technology",
address = "United Kingdom",
}