Xinjun Sheng

TL;DR: The design and validation of a real-time gesture recognition wristband based on surface electromyography and inertial measurement unit sensing fusion is presented, which can recognize 8 air gestures and 4 surface gestures with 2 distinct force levels.

TL;DR: The results indicate that the relative changes in EMG signal features over time become progressively smaller when the number of days during which the subjects perform the pre-defined motions are increased, resulting in more repeatable EMG patterns, even if the subjects do not have any external feedback on their performance.

TL;DR: It is found that the orientation of muscle activation pattern vector of the frequency band is similar for the same motion with different force levels and provided a potential way for simultaneous classification of hand motions and forces without training at all force levels.

TL;DR: A hybrid modality brain-computer interface (BCI) is proposed, which combines motor imagery with selective sensation to enhance the discrimination between left and right mental tasks, e.g., the classification between left/ right stimulation sensation and right/ left motor imagery.

TL;DR: In this article, the authors report the design, fabrication and performance of a soft, low-cost and lightweight (292 g) neuroprosthetic hand that provides simultaneous myoelectric control and tactile feedback.