Angle-of-arrival-based gesture recognition using ultrasonic multi-frequency signals

Type
Conference Paper

Authors
Chen, Hui
Ballal, Tarig
Saad, Mohamed
Al-Naffouri, Tareq Y.

KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program

KAUST Grant Number
OSR-2015-Sensors-2700

Online Publication Date
2017-11-02

Print Publication Date
2017-08

Date
2017-11-02

Abstract
Hand gestures are tools for conveying information, expressing emotion, interacting with electronic devices or even serving disabled people as a second language. A gesture can be recognized by capturing the movement of the hand, in real time, and classifying the collected data. Several commercial products such as Microsoft Kinect, Leap Motion Sensor, Synertial Gloves and HTC Vive have been released and new solutions have been proposed by researchers to handle this task. These systems are mainly based on optical measurements, inertial measurements, ultrasound signals and radio signals. This paper proposes an ultrasonic-based gesture recognition system using AOA (Angle of Arrival) information of ultrasonic signals emitted from a wearable ultrasound transducer. The 2-D angles of the moving hand are estimated using multi-frequency signals captured by a fixed receiver array. A simple redundant dictionary matching classifier is designed to recognize gestures representing the numbers from 0' to 9' and compared with a neural network classifier. Average classification accuracies of 95.5% and 94.4% are obtained, respectively, using the two classification methods.

Citation
Chen H, Ballal T, Saad M, Al-Naffouri TY (2017) Angle-of-arrival-based gesture recognition using ultrasonic multi-frequency signals. 2017 25th European Signal Processing Conference (EUSIPCO). Available: http://dx.doi.org/10.23919/eusipco.2017.8081160.

Acknowledgements
This work is supported by the KAUST-MIT-TUD consortium under grant OSR-2015-Sensors-2700.

Publisher
IEEE

Journal
2017 25th European Signal Processing Conference (EUSIPCO)

DOI
10.23919/eusipco.2017.8081160

Additional Links
http://ieeexplore.ieee.org/document/8081160/https://zenodo.org/record/1160244/files/1570347782.pdf

Permanent link to this record