Abstract

Human–Computer Interfaces (HCI) deals with the study of interface between humans and computers. The use of radar and other RF sensors to develop HCI based on Hand Gesture Recognition (HGR) has gained increasing attention over the past decade. Today, devices have built-in radars for recognizing and categorizing hand movements. In this article, we present the first ever review related to HGR using radar sensors. We review the available techniques for multi-domain hand gestures data representation for different signal processing and deep-learning-based HGR algorithms. We classify the radars used for HGR as pulsed and continuous-wave radars, and both the hardware and the algorithmic details of each category is presented in detail. Quantitative and qualitative analysis of ongoing trends related to radar-based HCI, and available radar hardware and algorithms is also presented. At the end, developed devices and applications based on gesture-recognition through radar are discussed. Limitations, future aspects and research directions related to this field are also discussed.

Highlights

  • In recent years, computing technology has become embedded in every aspect of our daily lives and man–machine interaction is becoming inevitable

  • Hand gesture recognition through radar technology found ical images application in the operating room to assist medical staff in processing and manipulating Based on the transmitted signal, short-range radar sensors used for Hand Gesture Recognition (HGR) can broadly medical images be categorized as pulsed radarsignal, and continuous-wave radar

  • It was observed that all the articles related to HGR using pulsed radar first performed clutter removal operation before further processing, and a loop-back filter is a common choice [11,12,50,77] as it exhibits a simple structure and the computational power is very minimal in comparison to other clutterreduction filters

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Summary

Introduction

In recent years, computing technology has become embedded in every aspect of our daily lives and man–machine interaction is becoming inevitable. Radar sensors have been deployed in a network-fashion for the detection and classification of complex hand gestures to develop applications such as the wireless keyboard [9]. Another study published by same authors presented a continuous alphabet writing based on the gestures drawn in front of two radars [20]. Hand gesture(DCNN)-based recognition through radar technology found appliConvolutional. Hand gesture recognition through radar technology found ical images [21]. Application in the operating room to assist medical staff in processing and manipulating Based on the transmitted signal, short-range radar sensors used for HGR can broadly medical images be categorized as pulsed radarsignal, and continuous-wave radar. Continuous Wave (FMCW) radar, transmits and receives a continuous wave Both these radars are widely used for HGR purposes

Understanding
Hand-Gesture Based HCI Design
Main Contribution and Scope of Article
Hand-Gesture Signal Acquisition through Radar
Pulsed Radars
CW Radars
Figure
Hand-Gesture Radar Signal Representation
HGR Algorithms
HGR Algorithms for Pulsed Radar
Participants and Samples Per
Participants and Total
HGR Algorithms for FMCW
10. Google’s
Quantitative Analysis
Nature
Real-Time HGR Examples
Security and Privay Analysis of Radar-Based HGR System
Commercially Available Radars for HGR
Ongoing Trends Limitations and Future Direction
Findings
Conclusions

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