Fine-grained Finger Gesture Recognition Using WiFi Signals

TL;DR

This paper introduces a WiFi-based system for fine-grained finger gesture recognition that does not require sensors or cameras, achieving over 90% accuracy across various environments and users.

Contribution

The work presents a novel WiFi signal processing approach for gesture recognition, including noise removal and multi-link utilization, enabling accurate detection without dedicated sensors.

Findings

Achieves over 90% recognition accuracy in diverse environments.

Robust to environmental changes and individual differences.

Effective in multi-user scenarios using multiple WiFi links.

Abstract

Gesture recognition has become increasingly important in human-computer interaction and can support different applications such as smart home, VR, and gaming. Traditional approaches usually rely on dedicated sensors that are worn by the user or cameras that require line of sight. In this paper, we present fine-grained finger gesture recognition by using commodity WiFi without requiring user to wear any sensors. Our system takes advantages of the fine-grained Channel State Information available from commodity WiFi devices and the prevalence of WiFi network infrastructures. It senses and identifies subtle movements of finger gestures by examining the unique patterns exhibited in the detailed CSI. We devise environmental noise removal mechanism to mitigate the effect of signal dynamic due to the environment changes. Moreover, we propose to capture the intrinsic gesture behavior to deal with individual diversity and gesture inconsistency. Lastly, we utilize multiple WiFi links and larger bandwidth at 5GHz to achieve finger gesture recognition under multi-user scenario. Our experimental evaluation in different environments demonstrates that our system can achieve over 90% recognition accuracy and is robust to both environment changes and individual diversity. Results also show that our system can provide accurate gesture recognition under different scenarios.