Wi-Fi Gesture Recognition on Existing Devices

TL;DR

This paper presents a novel Wi-Fi-based gesture recognition system that uses existing devices, achieving high accuracy without specialized hardware or per-user training, even in non-line-of-sight scenarios.

Contribution

It introduces algorithms for Wi-Fi gesture classification and demonstrates a practical prototype with high accuracy on off-the-shelf devices.

Findings

91% classification accuracy for four gestures

Works across six participants without per-user training

Effective in non-line-of-sight conditions

Abstract

This paper introduces the first wireless gesture recognition system that operates using existingWi-Fi signals and devices. To achieve this, we first identify limitations of existing wireless gesture recognition approaches that limit their applicability to Wi-Fi. We then introduce algorithms that can classify gestures using information that is readily available on Wi-Fi devices. We demonstrate the feasibility of our design using a prototype implementation on off-the-shelf Wi-Fi devices. Our results show that we can achieve a classification accuracy of 91% while classifying four gestures across six participants, without the need for per-participant training. Finally, we show the feasibility of gesture recognition in non-line-ofsight situations with the participants interacting with a Wi-Fi device placed in a backpack.