Human-Centered Evaluation of EMG-Based Upper-Limb Prosthetic Control Modes

IF 3.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Human-Machine Systems Pub Date : 2024-04-11 DOI:10.1109/THMS.2024.3381094
Yunmei Liu;Joseph Berman;Albert Dodson;Junho Park;Maryam Zahabi;He Huang;Jaime Ruiz;David B. Kaber
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Abstract

The aim of this study was to experimentally test the effects of different electromyographic-based prosthetic control modes on user task performance, cognitive workload, and perceived usability to inform further human-centered design and application of these prosthetic control interfaces. We recruited 30 able-bodied participants for a between-subjects comparison of three control modes: direct control (DC), pattern recognition (PR), and continuous control (CC). Multiple human-centered evaluations were used, including task performance, cognitive workload, and usability assessments. To ensure that the results were not task-dependent, this study used two different test tasks, including the clothespin relocation task and Southampton hand assessment procedure-door handle task. Results revealed performance with each control mode to vary among tasks. When the task had high-angle adjustment accuracy requirements, the PR control outperformed DC. For cognitive workload, the CC mode was superior to DC in reducing user load across tasks. Both CC and PR control appear to be effective alternatives to DC in terms of task performance and cognitive load. Furthermore, we observed that, when comparing control modes, multitask testing and multifaceted evaluations are critical to avoid task-induced or method-induced evaluation bias. Hence, future studies with larger samples and different designs will be needed to expand the understanding of prosthetic device features and workload relationships.
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以人为本的 EMG 上肢假肢控制模式评估
本研究旨在通过实验测试基于肌电图的不同假肢控制模式对用户任务表现、认知工作量和感知可用性的影响,为这些假肢控制界面的进一步以人为本的设计和应用提供参考。我们招募了 30 名健全参与者,对直接控制 (DC)、模式识别 (PR) 和连续控制 (CC) 三种控制模式进行了主体间比较。我们采用了多种以人为本的评估方法,包括任务表现、认知工作量和可用性评估。为确保结果不依赖于任务,本研究使用了两种不同的测试任务,包括衣夹重新定位任务和南安普顿手部评估程序--门把手任务。结果显示,每种控制模式在不同任务中的表现各不相同。当任务对角度调整精度要求较高时,PR 控制模式的表现优于 DC 控制模式。在认知工作量方面,CC 模式在减少用户任务负荷方面优于 DC。就任务性能和认知负荷而言,CC 和 PR 控制似乎都是 DC 的有效替代方案。此外,我们还发现,在比较控制模式时,多任务测试和多方面评估对于避免任务或方法引起的评估偏差至关重要。因此,未来的研究需要更多的样本和不同的设计,以扩大对假肢装置特征和工作量关系的理解。
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来源期刊
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Human-Machine Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
7.10
自引率
11.10%
发文量
136
期刊介绍: The scope of the IEEE Transactions on Human-Machine Systems includes the fields of human machine systems. It covers human systems and human organizational interactions including cognitive ergonomics, system test and evaluation, and human information processing concerns in systems and organizations.
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Table of Contents Present a World of Opportunity IEEE Systems, Man, and Cybernetics Society Information IEEE Transactions on Human-Machine Systems Information for Authors TechRxiv: Share Your Preprint Research with the World!
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