Most commercially available haptic gloves compromise the accuracy of hand-posture measurements in favor of a simpler design with fewer sensors. While inaccurate posture data is often sufficient for the task at hand in biomedical settings such as VR-therapy-aided rehabilitation, measurements should be as precise as possible to digitally recreate hand postures as accurately as possible. With these applications in mind, we have added extra sensors to the commercially available Dexmo haptic glove by Dexta Robotics and applied kinematic models of the haptic glove and the user's hand to improve the accuracy of hand-posture measurements. In this work, we describe the augmentations and the kinematic modeling approach. Additionally, we present and discuss an evaluation of hand posture measurements as a proof of concept.

翻译：当前市售触觉手套大多采用传感器精简设计，导致手部姿态测量精度受限。尽管在虚拟现实辅助康复等生物医学场景中，不精确的姿态数据通常足以满足即时任务需求，但为实现手部姿态的高保真数字重建，测量精度应尽可能提升。基于此应用需求，我们在Dexta Robotics公司生产的商用Dexmo触觉手套基础上增设了额外传感器，并应用触觉手套与用户手部的运动学模型以提高手部姿态测量精度。本文详细阐述了硬件增强方案与运动学建模方法，同时作为概念验证，展示并讨论了手部姿态测量的评估结果。