Gantenbein Jessica, Dittli Jan, Meyer Jan Thomas, Gassert Roger, Lambercy Olivier
Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Future Health Technologies, Singapore-ETH Centre, Campus for Research Excellence and Technological Enterprise (CREATE), Singapore, Singapore.
Front Neurorobot. 2022 Feb 21;16:815693. doi: 10.3389/fnbot.2022.815693. eCollection 2022.
Wearable robotic upper limb orthoses (ULO) are promising tools to assist or enhance the upper-limb function of their users. While the functionality of these devices has continuously increased, the robust and reliable detection of the user's intention to control the available degrees of freedom remains a major challenge and a barrier for acceptance. As the information interface between device and user, the intention detection strategy (IDS) has a crucial impact on the usability of the overall device. Yet, this aspect and the impact it has on the device usability is only rarely evaluated with respect to the context of use of ULO. A scoping literature review was conducted to identify non-invasive IDS applied to ULO that have been evaluated with human participants, with a specific focus on evaluation methods and findings related to functionality and usability and their appropriateness for specific contexts of use in daily life. A total of 93 studies were identified, describing 29 different IDS that are summarized and classified according to a four-level classification scheme. The predominant user input signal associated with the described IDS was electromyography (35.6%), followed by manual triggers such as buttons, touchscreens or joysticks (16.7%), as well as isometric force generated by residual movement in upper-limb segments (15.1%). We identify and discuss the strengths and weaknesses of IDS with respect to specific contexts of use and highlight a trade-off between performance and complexity in selecting an optimal IDS. Investigating evaluation practices to study the usability of IDS, the included studies revealed that, primarily, objective and quantitative usability attributes related to effectiveness or efficiency were assessed. Further, it underlined the lack of a systematic way to determine whether the usability of an IDS is sufficiently high to be appropriate for use in daily life applications. This work highlights the importance of a user- and application-specific selection and evaluation of non-invasive IDS for ULO. For technology developers in the field, it further provides recommendations on the selection process of IDS as well as to the design of corresponding evaluation protocols.
可穿戴式机器人上肢矫形器（ULO）是协助或增强使用者上肢功能的有前景的工具。虽然这些设备的功能不断增强，但对用户控制可用自由度意图的稳健可靠检测仍然是一个重大挑战，也是阻碍其被接受的一个障碍。作为设备与用户之间的信息接口，意图检测策略（IDS）对整个设备的可用性有着至关重要的影响。然而，这一方面及其对设备可用性的影响在ULO的使用背景下很少被评估。进行了一项范围界定文献综述，以识别应用于ULO且已在人体参与者中进行评估的非侵入性IDS，特别关注与功能和可用性相关的评估方法及结果，以及它们在日常生活特定使用背景下的适用性。共识别出93项研究，描述了29种不同的IDS，并根据四级分类方案进行了总结和分类。与所描述的IDS相关的主要用户输入信号是肌电图（35.6%），其次是手动触发装置，如按钮、触摸屏或操纵杆（16.7%），以及上肢节段残余运动产生的等长力（15.1%）。我们针对特定使用背景识别并讨论了IDS的优缺点，并强调了在选择最佳IDS时性能与复杂性之间的权衡。通过研究评估实践来考察IDS的可用性，纳入的研究表明，主要评估的是与有效性或效率相关的客观和定量可用性属性。此外，这凸显了缺乏一种系统方法来确定IDS的可用性是否足够高以适用于日常生活应用。这项工作强调了针对ULO的非侵入性IDS进行用户和应用特定选择及评估的重要性。对于该领域的技术开发者，它还提供了关于IDS选择过程以及相应评估协议设计的建议。
