PDF(Pubmed)
Abstract：
We propose a compact wearable glove capable of estimating both the finger bone lengths and the joint angles of the wearer with a simple stretch-based sensing mechanism. The soft sensing glove is designed to easily stretch and to be one-size-fits-all, both measuring the size of the hand and estimating the finger joint motions of the thumb, index, and middle fingers. The system was calibrated and evaluated using comprehensive hand motion data that reflect the extensive range of natural human hand motions and various anatomical structures. The data were collected with a custom motion-capture setup and transformed into the joint angles through our post-processing method. The glove system is capable of reconstructing arbitrary and even unconventional hand poses with accuracy and robustness, confirmed by evaluations on the estimation of bone lengths (mean error: 2.1 mm), joint angles (mean error: 4.16°), and fingertip positions (mean 3D error: 4.02 mm), and on overall hand pose reconstructions in various applications. The proposed glove allows us to take advantage of the dexterity of the human hand with potential applications, including but not limited to teleoperation of anthropomorphic robot hands or surgical robots, virtual and augmented reality, and collection of human motion data.
摘要：
我们提出了一种紧凑的可穿戴手套，能够通过简单的基于拉伸的感测机制来估计穿戴者的指骨长度和关节角度。软感应手套的设计可以轻松拉伸，并且可以一刀切，测量手的大小和估计拇指的指关节运动，索引,中指。使用全面的手部运动数据对系统进行了校准和评估，这些数据反映了自然手部运动和各种解剖结构的广泛范围。使用自定义运动捕获设置收集数据，并通过我们的后处理方法将其转换为关节角度。手套系统能够重建任意和甚至非常规的手的姿势与准确性和鲁棒性，通过对骨骼长度估计的评估证实（平均误差：2.1mm），关节角度（平均误差：4.16°），和指尖位置（平均3D误差：4.02毫米），和在各种应用中的整体手姿势重建。所提出的手套使我们能够利用人手的灵巧与潜在的应用，包括但不限于人工机器人手或手术机器人的远程操作，虚拟和增强现实，和人体运动数据的收集。
