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使用轮椅机器人克服建筑障碍的启发式方法。

A Heuristic Approach to Overcome Architectural Barriers Using a Robotic Wheelchair.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2019 Sep;27(9):1846-1854. doi: 10.1109/TNSRE.2019.2934387. Epub 2019 Aug 9.

Abstract

The Mobility Enhancement roBotic (MEBot) wheelchair was developed to improve the safety and accessibility of wheelchair users when facing architectural barriers. MEBot uses pneumatic actuators attached to its frame and six wheels to provide curb ascending/descending for heights up to 20.3 cm. To improve MEBot's application, this study used a heuristic approach with power wheelchair users to evaluate and improve the MEBot application at different curb heights. Wheelchair users were trained on MEBot's features to operate its curb ascending/descending application. Three trials were carried out with wheelchair users ascending and descending three curbs of different height. Quantitative variables were analyzed to improve the sequential steps to ascend/descend curbs. Additionally, the application's effectiveness and efficiency were measured by the number of completed tasks, change in seat angle, and task completion time. Results showed that participants completed each trial and applied alternative strategies to traverse different curb heights. Furthermore, results suggested the combination and/or re-arrangement of steps to reduce task completion time. MEBot demonstrated its effectiveness to ascend/descend different curb heights with a heterogeneous participant sample. Future work will incorporate participant's most efficient strategies to improve the ascending/ascending process and the efficiency of the MEBot application.

摘要

移动增强机器人(MEBot)轮椅旨在提高轮椅使用者在遇到建筑障碍时的安全性和可达性。MEBot 使用附在框架上的气动执行器和六个轮子为高达 20.3 厘米的高度提供路缘升降功能。为了提高 MEBot 的适用性,本研究使用启发式方法,让电动轮椅使用者评估和改进 MEBot 在不同路缘高度下的应用。轮椅使用者接受了 MEBot 功能的培训,以操作其路缘升降应用程序。轮椅使用者进行了三次试验,分别在三个不同高度的路缘上上升和下降。对定量变量进行了分析,以改进上升/下降路缘的顺序步骤。此外,通过完成任务的数量、座椅角度的变化和任务完成时间来衡量应用程序的有效性和效率。结果表明,参与者完成了每次试验,并应用了替代策略来穿越不同的路缘高度。此外,结果表明,通过组合和/或重新排列步骤,可以减少任务完成时间。MEBot 展示了其在具有异质参与者样本的情况下,在不同路缘高度上的有效性。未来的工作将结合参与者最有效的策略,以改进上升/下降过程和 MEBot 应用程序的效率。

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