Hand Gesture Recognition Based on Near-Infrared Sensing Wristband

Maereg, Anudalem and Lou, Yang and Secco, Emanuele Lindo and King, Raymond (2019) Hand Gesture Recognition Based on Near-Infrared Sensing Wristband. In: 4th international Conference on Human Computer Interaction Theory and Applications, 2020, Malta. (Accepted for Publication)

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Abstract

Wrist-worn gesture sensing systems can be used as a seamless interface for AR/VR interactions and control of various devices. In this paper, we present a low-cost gesture sensing system that utilizes near Infrared Emitters (600 - 1100 nm) and Photo-Receivers encompassing the wrist to infer hand gestures. The proposed system consists of a wristband comprising Infrared emitters and receivers, data acquisition hardware, data post-processing software, and gesture classification algorithms. During the data acquisition process, 24 near Infrared Emitters are sequentially switched on around the wrist, and twelve Photo-diodes measure the light reflected, refracted, and scattered by the tissues inside the wrist. The acquired data corresponding to different gestures are labeled and input into a machine learning algorithm for gesture classification. To demonstrated the accuracy and speed of the proposed system, real-time gesture sensing user studies were conducted. As a result of this comparison, we obtained an average accuracy of 98.06% with standard deviation of 1.82%. In addition, we
evaluated that the system can perform six-eight gestures per second in real time using a desktop computer operating with Core i7-7800X CPU at 3.5GHz and 32 GB RAM.

Item Type: Conference or Workshop Item (Paper)
Additional Information and Comments: This is the author's version of a paper that has been accepted for presentation at the 4th international Conference on Human Computer Interaction Theory and Applications.
Faculty / Department: Faculty of Human and Digital Sciences > Mathematics and Computer Science
Depositing User: Emanuele Secco
Date Deposited: 06 Dec 2019 14:16
Last Modified: 01 Mar 2020 01:15
URI: https://hira.hope.ac.uk/id/eprint/2979

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