Spectrum-Based Hand Gesture Recognition Using Millimeter-Wave Radar Parameter Measurements

Changjiang Liu, Yuanhao Li, Dongyang Ao, Haiyan Tian

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
48 Downloads (Pure)

Abstract

Radar sensors offer several advantages over optical sensors in the gesture recognition for remote control of electronic devices. In this paper, we investigate the feasibility of human gesture recognition using the spectra of radar measurement parameters. With the combination of radar theory and classification methods, we found that the frequencies of different gestures' parameters could be utilized as features for gesture recognition. Six kinds of periodic dynamic gestures are designed to avoid the complexity of defining and extracting the start and end of the dynamic gesture. In addition to the frequency ratio, we also extracted some features related to motion range and detection coherence to eliminate the interferences brought by the unintended gestures. The decision tree classifier designed on the basis of experimental phenomena can guarantee effective classification between different gestures, and in general, the correct recognition rate of each gesture is higher than 90%. Finally, we collected the position and the Doppler velocity information of hand for classification by a W-band millimeter wave radar in the experiment and verified the usability of the proposed method.
Original languageEnglish
Article number8736874
Pages (from-to)79147-79158
Number of pages13
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 2019

Keywords

  • decision tree
  • feature extraction
  • Gesture recognition
  • millimeter-wave

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