A gesture database of B-mode ultrasound-based human-machine interface

Ultrasound imaging, as a non-invasive method which can recognize morphological changes of forearm muscles, has been gradually applied in the field of gesture recognition. In this paper, we proposed a B-mode ultrasound-based gesture database to provide a standard platform for the evaluation of different gesture recognition algorithms. The ultrasonic signals of the forearm according to the preset paradigm, and the classification results of a variety of features and classifiers were presented. Our results showed that the vast majority of feature algorithms and classifiers could achieve a satisfying recognition accuracy (about 90%). The analysis and results described herein are intended to provide a strong benchmark for the database and pave the way for subsequent researches.