WiGest: A Ubiquitous WiFi-based Gesture Recognition System
Heba Abdelnasser, Moustafa Youssef, Khaled A. Harras

TL;DR
WiGest is a WiFi-based gesture recognition system that detects in-air hand gestures using standard WiFi equipment without modifications or training, achieving high accuracy in various environments.
Contribution
WiGest introduces a novel WiFi-based gesture recognition method that requires no hardware modifications or training, utilizing signal primitives to identify gestures.
Findings
Achieves 87.5% accuracy with a single AP in non-line-of-sight scenarios
Improves to 96% accuracy using three APs
Successfully classifies gestures in real-world multimedia applications
Abstract
We present WiGest: a system that leverages changes in WiFi signal strength to sense in-air hand gestures around the user's mobile device. Compared to related work, WiGest is unique in using standard WiFi equipment, with no modi-fications, and no training for gesture recognition. The system identifies different signal change primitives, from which we construct mutually independent gesture families. These families can be mapped to distinguishable application actions. We address various challenges including cleaning the noisy signals, gesture type and attributes detection, reducing false positives due to interfering humans, and adapting to changing signal polarity. We implement a proof-of-concept prototype using off-the-shelf laptops and extensively evaluate the system in both an office environment and a typical apartment with standard WiFi access points. Our results show that WiGest…
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Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Wireless Networks and Protocols · Speech and Audio Processing
