Hand Gesture Recognition Using Ultrasonic Waves
classification
📡 eess.SP
keywords
handsignalgesturegesturessingleultrasonicaccuracyachieved
read the original abstract
This paper presents a new method for detecting and classifying a predefined set of hand gestures using a single transmitter and a single receiver utilizing a linearly frequency modulated ultrasonic signal. Gestures are identified based on estimated range and received signal strength (RSS) of reflected signal from the hand. Support Vector Machine (SVM) was used for gesture detection and classification. The system was tested using experimental setup and achieved an average accuracy of 88%.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.