Human movement in simulated hypogravity-Bridging the gap between space research and terrestrial rehabilitation
Frontiers in neurology(2023)
摘要
Human movement is optimized to Earth's gravity and based on highly complex interactions between sensory and neuro-muscular systems. Yet, humans are able to adapt-at least partially-to extreme environments upon and beyond Earth's surface. With upcoming Lunar Gateway and Artemis missions, it is crucial to increase our understanding of the impact of hypogravity-i.e., reduced vertical loading-on physiological and sensory-motor performances to improve countermeasure programs, and define crewmember's readiness to perform mission critical tasks. Several methodologies designed to reduce vertical loading are used to simulate hypogravity on Earth, including body weight support (BWS) devices. Countering gravity and offloading the human body is also used in various rehabilitation scenarios to improve motor recovery in neurological and orthopedic impairments. Thus, BWS-devices have the potential of advancing theory and practice of both space exploration and terrestrial rehabilitation by improving our understanding of physiological and sensory-motor adaptations to reduced vertical loading and sensory input. However, lack of standardization of BWS-related research protocols and reporting hinders the exchange of key findings and new advancements in both areas. The aim of this introduction paper is to review the role of BWS in understanding human movement in simulated hypogravity and the use of BWS in terrestrial rehabilitation, and to identify relevant research areas contributing to the optimization of human spaceflight and terrestrial rehabilitation. One of the main aims of this research topic is to facilitate standardization of hypogravity-related research protocols and outcome reporting, aimed at optimizing knowledge transfer between space research and BWS-related rehabilitation sciences.
更多查看译文
关键词
hypogravity,body weight support,neurorehabilitation,orthopedic rehabilitation,spaceflight,exercise,reconditioning
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要