Object properties perceived through the tactile sense, such as weight, friction, and slip, greatly influence motor control during manipulation tasks. However, the provision of tactile information during robotic training in neurorehabilitation has not been well explored. Therefore, we designed and evaluated a tactile interface based on a two-degrees-of-freedom moving platform mounted on a hand rehabilitation robot that provides skin stretch at four fingertips, from the index through the little finger. To accurately control the rendered forces, we included a custom magnetic-based force sensor to control the tactile interface in a closed loop. The technical evaluation showed that our custom force sensor achieved measurable shear forces of +-8N with accuracies of 95.2-98.4% influenced by hysteresis, viscoelastic creep, and torsional deformation. The tactile interface accurately rendered forces with a step response steady-state accuracy of 97.5-99.4% and a frequency response in the range of most activities of daily living. Our sensor showed the highest measurement-range-to-size ratio and comparable accuracy to sensors of its kind. These characteristics enabled the closed-loop force control of the tactile interface for precise rendering of multi-finger two-dimensional skin stretch. The proposed system is a first step towards more realistic and rich haptic feedback during robotic sensorimotor rehabilitation, potentially improving therapy outcomes.

翻译：通过触觉感知到的物体属性（如重量、摩擦和滑移）在操控任务中显著影响运动控制。然而，在神经康复的机器人训练过程中，触觉信息的提供尚未得到充分探索。为此，我们设计并评估了一种基于二自由度移动平台的触觉接口，该平台安装于手部康复机器人上，可为从食指到小指的四根指尖提供皮肤拉伸。为精确控制施加力，我们集成了定制磁力传感器，以闭环方式控制触觉接口。技术评估表明，定制力传感器在±8N范围内可测量剪切力，受滞后效应、粘弹性蠕变和扭转变形影响，测量精度为95.2-98.4%。该触觉接口能精确施加力，阶跃响应稳态精度达97.5-99.4%，频率响应覆盖大多数日常生活活动范围。本传感器在测量范围-尺寸比方面表现最优，且精度与同类传感器相当。这些特性使得触觉接口能通过闭环力控制精确呈现多指二维皮肤拉伸。所提出的系统是实现机器人感觉运动康复过程中更真实、丰富触觉反馈的第一步，有望改善治疗效果。