Abstract

Stroke has been considered the main cause of neuromuscular damages worldwide and one of the most common causes of walking disabilities, with approximately 60% of the individuals suffering from persistent problems in walking. These patients generally use technical aids for walking to achieve independent gait, however, when cognitive impairments are also present, conventional assistive devices such as walkers could be difficult to handle. By leveraging multimodal interfaces, smart walkers can offer natural and intuitive human-robot interaction. In this work, we present two multimodal interaction strategies for smart walkers focusing on guiding post-stroke patients through their environment. These strategies leverage different communication channels and provide distinct levels of guidance: one strategy uses haptic feedback and a visual interface to indicate the desired path to the user, while the other strategy uses haptic feedback and a virtual torque to maintain the user on path. We also present two case studies with post-stroke patients to preliminarily validate these interaction strategies with their target population and to collect valuable insight as to how multimodal strategies for smart walkers can be enhanced to deal with the characteristic asymmetries of post-stroke patients. Our results show that both strategies can guide the volunteers, however, the first one demands more effort from the volunteer and is more suited for patients with increased levels of independence. The second interaction strategy allows for higher linear velocity (Volunteer 1, \(\varvec{0.18}\) \(\varvec{\pm 0.026}\) \(\varvec{m/s}\) ; Volunteer 2, \(\varvec{0.22}\) \(\varvec{\pm 0.0283}\) \(\varvec{m/s}\) ) than the first one (Volunteer 1, \(\varvec{0.10}\) \(\varvec{\pm 0.031}\) \(\varvec{m/s}\) ; Volunteer 2, \(\varvec{0.20}\) \(\varvec{\pm 0.012}\) \(\varvec{m/s}\) ), suggesting improved guidance.

中文翻译：

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助行器辅助步态的多模式交互策略：中风后患者康复的案例研究

摘要

中风被认为是全世界神经肌肉损伤的主要原因，也是导致行走障碍的最常见原因之一，大约 60% 的人患有持续性行走问题。这些患者通常使用步行技术辅助设备来实现独立步态，然而，当还存在认知障碍时，传统的辅助设备（例如助行器）可能难以操作。通过利用多模式接口，智能步行器可以提供自然、直观的人机交互。在这项工作中，我们为智能步行者提出了两种多模式交互策略，重点是引导中风后患者穿过他们的环境。这些策略利用不同的通信渠道并提供不同级别的指导：一种策略使用触觉反馈和视觉界面来向用户指示所需的路径，而另一种策略使用触觉反馈和虚拟扭矩来使用户保持在路径上。我们还提出了两个针对中风后患者的案例研究，以初步验证这些与目标人群的互动策略，并收集关于如何增强智能步行者的多模式策略以处理中风后患者特征不对称的宝贵见解。我们的结果表明，这两种策略都可以指导志愿者，但是，第一种策略需要志愿者付出更多的努力，并且更适合独立程度较高的患者。第二种交互策略允许更高的线速度 (志愿者 1, \(\varvec{0.18}\) \(\varvec{\pm 0.026}\) \(\varvec{m/s}\) ; 志愿者 2, \( \varvec{0.22}\) \(\varvec{\pm 0.0283}\) \(\varvec{m/s}\) ) 比第一个（志愿者 1，\(\varvec{0.10}\) \(\ varvec{\pm 0.031}\) \(\varvec{m/s}\) ; 志愿者 2, \(\varvec{0.20}\) \(\varvec{\pm 0.012}\) \(\varvec{m/ s}\)），建议改进指导。