期刊
ISCIENCE
卷 25, 期 12, 页码 -出版社
CELL PRESS
DOI: 10.1016/j.isci.2022.105418
关键词
-
资金
- MIUR (Italian Minister for Education) [Law 232/2016]
- Department of Information Engineering of the University of Padova [TONI_BIRD2020_01]
The study shows that tetraplegic spinal-cord injury users can be trained to operate a non-invasive thought-controlled wheelchair for complex navigation tasks, but only those with increasing decoding performance and feature discriminancy achieved high navigation performance. Additionally, dexterous control of robots is possible through shared-control methodologies.
Mind-controlled wheelchairs are an intriguing assistive mobility solution applicable in complete paralysis. Despite progress in brain-machine interface (BMI) technology, its translation remains elusive. The primary objective of this study is to probe the hypothesis that BMI skill acquisition by end-users is fundamental to control a non-invasive brain-actuated intelligent wheelchair in real-world settings. We demonstrate that three tetraplegic spinal-cord injury users could be trained to operate a non-invasive, self-paced thought-controlled wheelchair and execute complex navigation tasks. However, only the two users exhibiting increasing decoding performance and feature discriminancy, significant neuro-plasticity changes and improved BMI command latency, achieved high navigation performance. In addition, we show that dexterous, continuous control of robots is possible through low-degree of freedom, discrete and uncertain control channels like a motor imagery BMI, by blending human and artificial intelligence through shared-control methodologies. We posit that subject learning and shared-control are the key components paving the way for translational non-invasive BMI.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据