Xu Qiujian, Yang Dan, Li Meihui, Ren Xiubo, Yuan Xinran, Tang Lijun, Wang Xiaoyu, Liu Siqi, Yang Miaomiao, Liu Yintong, Yang Mingyi
School of Arts and Design, Yanshan University, Qinhuangdao 066004, China.
YSU & DCU Joint Research Centre for the Arts, Music College, Daegu Catholic University, Daegu 38430, Republic of Korea.
Biomimetics (Basel). 2024 Jun 25;9(7):385. doi: 10.3390/biomimetics9070385.
Finger technique is a crucial aspect of piano learning, and hand exoskeleton mechanisms effectively assist novice piano players in maintaining correct finger technique consistently. Addressing current issues with exoskeleton robots, such as the inability to provide continuous correction of finger technique and their considerable weight, a novel hand exoskeleton robot has been developed to enhance finger technique through continuous correction and reduced weight. Initial data are gathered using finger joint angle sensors to analyze movements during piano playing, focusing on the trajectory and angular velocity of key strikes. This analysis informs the design of a 6-bar double-closed-loop mechanism with an end equivalent sliding pair, using analytical methods to establish the relationship between motor extension and input rod rotation. Simulation studies assess the exoskeleton's motion space and dynamics, confirming its capability to meet structural and functional demands for accurate key striking. Prototype testing validates the exoskeleton's ability to maintain correct finger positioning and mimic natural strike speeds, thus improving playing technique while ensuring comfort and safety.
手指技巧是钢琴学习的一个关键方面，手部外骨骼机制有效地帮助新手钢琴演奏者始终保持正确的手指技巧。针对外骨骼机器人目前存在的问题，如无法对手指技巧进行持续纠正以及重量较大等，已开发出一种新型手部外骨骼机器人，以通过持续纠正和减轻重量来提高手指技巧。使用手指关节角度传感器收集初始数据，以分析钢琴演奏过程中的动作，重点关注按键敲击的轨迹和角速度。该分析为具有端部等效滑动副的六杆双闭环机构的设计提供了依据，采用解析方法建立电机伸长与输入杆旋转之间的关系。仿真研究评估了外骨骼的运动空间和动力学性能，证实其能够满足准确按键敲击的结构和功能要求。原型测试验证了外骨骼保持正确手指定位和模仿自然敲击速度的能力，从而在确保舒适性和安全性的同时提高演奏技巧。
