70 citations · 76 across the 6 of their papers we have counts for
7 papers
Wearable-informed generative digital avatars predict task-conditioned post-stroke locomotion
Yanning Dai, Chenyu Tang, Ruizhi Zhang +16
Dynamic prediction of locomotor capacity after stroke could enable more individualized rehabilitation, yet current assessments largely provide static impairment scores and do not i…
Generalised Label-free Artefact Cleaning for Real-time Medical Pulsatile Time Series
Xuhang Chen, Ihsane Olakorede, Stefan Yu Bögli +8
Artefacts compromise clinical decision-making in the use of medical time series. Pulsatile waveforms offer probabilities for accurate artefact detection, yet most approaches rely o…
An AI-Driven Multimodal Smart Home Platform for Continuous Monitoring and Assistance in Post-Stroke Motor Impairment
Chenyu Tang, Ruizhi Zhang, Shuo Gao +21
At-home rehabilitation for post-stroke patients presents significant challenges, as continuous, personalized care is often limited outside clinical settings. Moreover, the lack of…
Neuromorphic spatiotemporal optical flow: Enabling ultrafast visual perception beyond human capabilities
Shengbo Wang, Jingwen Zhao, Tongming Pu +14
Optical flow, inspired by the mechanisms of biological visual systems, calculates spatial motion vectors within visual scenes that are necessary for enabling robotics to excel in c…
Diagnosis of Multiple Fundus Disorders Amidst a Scarcity of Medical Experts Via Self-supervised Machine Learning
Yong Liu, Mengtian Kang, Shuo Gao +12
Fundus diseases are major causes of visual impairment and blindness worldwide, especially in underdeveloped regions, where the shortage of ophthalmologists hinders timely diagnosis…
SSVT: Self-Supervised Vision Transformer For Eye Disease Diagnosis Based On Fundus Images
Jiaqi Wang, Mengtian Kang, Yong Liu +12
Machine learning-based fundus image diagnosis technologies trigger worldwide interest owing to their benefits such as reducing medical resource power and providing objective evalua…
Intelligent machines work in unstructured environments by differential neuromorphic computing
Shengbo Wang, Shuo Gao, Chenyu Tang +9
Efficient operation of intelligent machines in the real world requires methods that allow them to understand and predict the uncertainties presented by the unstructured environment…