Extra robotic arms (XRAs) are gaining interest in neuroscience and robotics, offering potential tools for daily activities. However, this compelling opportunity poses new challenges for sensorimotor control strategies and human-machine interfaces (HMIs). A key unsolved challenge is allowing users to proficiently control XRAs without hindering their existing functions. To address this, we propose a pipeline to identify suitable HMIs given a defined task to accomplish with the XRA. Following such a scheme, we assessed a multimodal motor HMI based on gaze detection and diaphragmatic respiration in a purposely designed modular neurorobotic platform integrating virtual reality and a bilateral upper limb exoskeleton. Our results show that the proposed HMI does not interfere with speaking or visual exploration and that it can be used to control an extra virtual arm independently from the biological ones or in coordination with them. Participants showed significant improvements in performance with daily training and retention of learning, with no further improvements when artificial haptic feedback was provided. As a final proof of concept, naïve and experienced participants used a simplified version of the HMI to control a wearable XRA. Our analysis indicates how the presented HMI can be effectively used to control XRAs. The observation that experienced users achieved a success rate 22.2% higher than that of naïve users, combined with the result that naïve users showed average success rates of 74% when they first engaged with the system, endorses the viability of both the virtual reality–based testing and training and the proposed pipeline.

中文翻译：

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使用额外的机械臂增强人体运动，不会产生功能干扰

额外机械臂 (XRA) 正在引起人们对神经科学和机器人技术的兴趣，为日常活动提供潜在的工具。然而，这个引人注目的机会给感觉运动控制策略和人机界面（HMI）带来了新的挑战。一个尚未解决的关键挑战是允许用户在不妨碍其现有功能的情况下熟练地控制 XRA。为了解决这个问题，我们提出了一个管道，用于根据 XRA 完成的定义任务来识别合适的 HMI。按照这样的方案，我们在一个专门设计的集成虚拟现实和双侧上肢外骨骼的模块化神经机器人平台中评估了基于凝视检测和膈肌呼吸的多模式运动人机界面。我们的结果表明，所提出的 HMI 不会干扰说话或视觉探索，并且它可以用来独立于生物手臂或与生物手臂协调控制额外的虚拟手臂。参与者在日常训练和学习保持中表现出显着的表现改善，但在提供人工触觉反馈时没有进一步改善。作为最终的概念证明，新手和经验丰富的参与者使用简化版本的 HMI 来控制可穿戴 XRA。我们的分析表明了如何有效地使用所提出的 HMI 来控制 XRA。经验丰富的用户的成功率比新手用户高 22.2%，再加上新手用户首次使用该系统时的平均成功率为 74%，这都证实了基于虚拟现实的系统的可行性。测试和培训以及拟议的管道。