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Since computers have
become more fundamental in society, there has been an increase in demand for
Human Computer Interaction. Hence, there has been growing interest in the
development of new approaches in Human Computer Interaction. Gesture
recognition is an important part of Human Computer Interaction and has a wide
variety of applications like gaming and virtual reality. Previous work and
approaches use sensors that are worn by the user or cameras that require proper
light to identify gestures. In this paper, we introduce a finger gesture
recognition system by using a WiFi device without requiring any cameras or the user to wear any
sensors. Our system uses Channel State Information (CSI) from a WiFi device and identifies
small movements of finger gestures by analyzing the unique patterns of Channel
State Information. We also incorporate an environmental noise removal mechanism
to mitigate any noise cause due to environmental changes. Our experimental evaluation
shows that our system can achieve about 80% accuracy and is robust to
individual diversity. Moreover our results show that our system is immune to
NLOS scenarios.

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