The flexibility and range of motion in human hands play a crucial role in human interaction with the environment and have been studied across different fields. Researchers explored various technological solutions for gathering information from the hands. These solutions include tracking hand motion through cameras or wearable sensors and using wearable sensors to measure the position and pressure of contact points. Data gloves can collect both types of information by utilizing inertial measurement units, flex sensors, magnetic trackers for motion tracking, and force resistors or touch sensors for contact measurement. Although there are commercially available data gloves, researchers often create custom data gloves to achieve the desired flexibility and control over the hardware. However, the existing literature lacks standardization and the reuse of previously designed data gloves. As a result, many gloves with unclear characteristics exist, which makes replication challenging and negatively impacts the reproducibility of studies. This work proposes a modular, open hardware and software architecture for creating customized data gloves based on IMU technology. We also provide an architecture implementation along with an experimental protocol to evaluate device performance.

翻译：人类手部的灵活性和运动范围在人与环境互动中起着关键作用，并已在不同领域得到研究。研究者探索了多种从手部采集信息的技术方案，包括通过摄像头或可穿戴传感器追踪手部运动，以及使用可穿戴传感器测量接触点的位置与压力。数据手套能够利用惯性测量单元、弯曲传感器、磁力追踪器进行运动追踪，并通过力敏电阻或触觉传感器实现接触测量，从而同时采集这两类信息。尽管市面上已有商用数据手套，但研究者常自行定制开发，以获得所需的灵活性并实现对硬件的自主控制。然而，现有文献缺乏标准化流程及对已有数据手套设计的复用机制，导致大量特性不明确的手套存在，这不仅增加了复制难度，还严重影响了研究的可重复性。本文提出一种基于IMU技术的模块化开源软硬件架构，用于定制化数据手套的开发，并提供了该架构的实现方案及评估设备性能的实验协议。