Department of Computer Science and Information Engineering, National Taipei University, New Taipei City 23741, Taiwan.
College of Electrical Engineering and Computer Science, National Taipei University, New Taipei City 23741, Taiwan.
Sensors (Basel). 2018 May 13;18(5):1545. doi: 10.3390/s18051545.
Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.
捕获手部动作对于手部功能评估在医学领域至关重要。已经开发出各种数据手套,用于康复和手灵巧性评估。本研究提出了一种具有 9 轴惯性测量单元(IMU)的模块化数据手套,可在手部功能评估期间获取静态和动态参数。使用传感器融合算法来计算关节的运动范围。数据手套的设计具有低成本、易于穿戴和高可靠性的特点。由于采用模块化设计,IMU 板独立且可扩展,可与各种微控制器一起使用,以实现更多的医疗应用。这种设计极大地提高了手套的稳定性和可维护性。