A groundbreaking non-hand-worn VR hand rehabilitation system has been developed, utilizing ionic hydrogel electrodes and deep learning for electromyography (EMG) gesture recognition. The system offers load-free rehabilitation without bulky mechanical components, providing a more accessible and flexible alternative to traditional rehabilitation methods. This VR-based solution enables immersive training and precise hand rehabilitation for stroke and joint disease patients in the comfort of their homes, without the constraints of time or location.

A self-supervised deep learning model has been developed to improve the quality of dynamic fluorescence images by leveraging temporal gradients. The method enables accurate denoising without ground truth data and facilitates clearer visualization of spatially and temporally dynamic biological signals in vivo.

Oregon State University scientists have improved artificial intelligence’s ability to identify wildlife species in photos taken by motion-activated cameras.