Study of Hand Joint Kinematics and Biomechanical of Grasping Contact Force
Liu Xiaojie1#, Zhang Xushu1#*, Guo Yuan1#, Wen Yunpeng2, Wang Ruixue1#, Zhang Ming3#
1(College of Biomedical Engineering, Taiyuan University of Technology, Jinzhong 030600, Shanxi, China) 2(Department of Rehabilitation Medicine, Shanxi Huajin Orthopedics Hospital, Taiyuan 030400, China) 3(Department of Biomedical Engineering, Hong Kong Polytechnic University, Hong Kong 999077, China)
Abstract:This work performed biomechanical analysis of finger joint kinematics and grip contact force, aiming to provide reference for design of the motion and force feedback control of prosthetic hands. This study recruited 50 college students and set up three working conditions: manual gripping of different mass weights, cups with different volumes of water, and spheres with different diameters. Hand kinematic data and grip contact force data were collected from the participants. In the hand kinematics experiment, the Vicon motion capture system was used to collect the kinematic data of each marked point affixed to the subject's hand, and the angles of finger joints were calculated according to the space vector angle formula. In the hand contact force acquisition experiment, a thin film pressure sensor was used to acquire contact force information of the hand. USB-210 eight-channel data acquisition card was used as a pressure acquisition device and INSTRON 5544 material testing machine was used to calibrate the sensor. The sensor calibration curve was fitted with an exponential function, and the R2 reached 0.995 9. The contact force of each collection area was calculated. According to the kinematic characteristics of human fingers in different working conditions, the contact force data were analyzed statistically, and the biomechanical characteristics were studied. The results showed that the movement of each finger and the distribution of contact force in hand movement were synergetic, and the thumb, middle finger and index finger had a greater impact on the grasping function of the opponent, contributing 31.59%, 22.2% and 15.88% of the contact force respectively. The three fingertips contact force had significant differences with the increase of weight mass (P<0.05). With the increase of the number of finger joints and the complexity of movement, the contact force between fingertip and palm area also showed significant differences (P<0.05). There was no significant interaction effect between the gender difference of the subjects and the differences between the working conditions (P>0.05). These results provided data and theoretical reference for the design of humanoid prosthetic hand.
作者简介: #中国生物医学工程学会会员(Member, Chinese Society of Biomedical Engineering)
引用本文:
刘晓杰, 张绪树, 郭媛, 文云鹏, 王瑞雪, 张明. 人手关节运动学与抓握接触力的生物力学研究分析[J]. 中国生物医学工程学报, 2025, 44(2): 193-202.
Liu Xiaojie, Zhang Xushu, Guo Yuan, Wen Yunpeng, Wang Ruixue, Zhang Ming. Study of Hand Joint Kinematics and Biomechanical of Grasping Contact Force. Chinese Journal of Biomedical Engineering, 2025, 44(2): 193-202.
[1] 赵梦文, 胡志刚, 王新征, 等. 基于AnyBody脑卒中患者手部抓握训练的肌肉力学特性分析[J]. 医用生物力学, 2021, 36(5): 698-704. [2] 戴景辉. 具有耦合自适应运动特性的欠驱动假肢手设计[D]. 哈尔滨: 哈尔滨工业大学, 2021. [3] 徐睿, 郑悦, 匡星, 等. 低成本自适应仿人假肢手设计[J]. 集成技术, 2016, 5(1): 17-23. [4] 罗椅民. 我国假肢与矫形器行业的历史、现状与展望[EB/OL].https://kffj.mca.gov.cn/article/fjzx/202012/20201200030929.shtml,2020-12-08/2023-02-20. [5] Anne E, Jill MC, Kathleen EY. Modified constraint-induced movement therapy for persons with unilateral upper extremity amputation: a case report[J]. Journal of Hand Therapy, 2020,33(41): 587-592. [6] 徐宏, 郝涛, 郝祥如. 我国老年残疾人口发展趋势预测及养老服务研究[J]. 海南大学学报(人文社会科学版), 2015, 33(5): 22-29. [7] 刘明进. 人手抓握运动规律及其在机器人仿人手设计中的应用[D]. 武汉: 华中科技大学, 2017. [8] 师昉, 张广为, 彭娜, 等. 北京市300例肢体残障者辅助器具适配情况研究[J]. 中国伤残医学, 2013, 21(6): 78-79. [9] Li Cong,Li Minglai. The policy information gap and resettlers’ well-being: Evidence from the anti-poverty relocation and resettlement program in China[J]. International Journal of Environmental Research and Public Health, 2020, 17(8): 1-20. [10] Mariana Z, Eva M, Miroslav J, et al. Influence of rehabilitation aid with biofeedback on the rehabilitation process during remote home-based rehabilitation[J]. International Journal of Environmental Research and Public Health, 2022, 19(15): 9069-9069. [11] 王伟. 具有力/位感知的仿人假手机构的研究[D]. 哈尔滨: 哈尔滨工业大学, 2009. [12] Gu Guoying, Zhang Ningbin, Xu Haipeng, et al. A soft neuroprosthetic hand providing simultaneous myoelectric control and tactile feedback[J]. Nature Biomedical Engineering,2021, 7(4): 589-598. [13] 刘正琼, 唐璇, 刘明周, 等. 高精度手部压力分布检测系统的设计及研究[J]. 合肥工业大学学报(自然科学版), 2017, 40(3): 316-320. [14] Vignais N, Marin F. Musculoskeletal model of the hand and forearm: From motion capture to biomechanical modeling[C]//EUROMECH Colloquium 511 on Biomechanics of Human Motion. Portugal: ResearchGate, 2011: 1-15. [15] 张乔飞. 人手运动特征分析与机械实现[D]. 武汉: 华中科技大学, 2015. [16] 樊瑜波. 康复工程研究与康复辅具创新[J]. 科技导报, 2019, 37(22): 6-7. [17] Tedesco TL, Mclening B, Hendrie W, et al. Is there a standard procedure for assessing and providing assistive devices for people with neuro-disabling conditions in United Kingdom? A nation-wide survey[J]. Disability and Health Journal, 2019, 12(1): 93-97. [18] Metcalf CD. Challenges in measuring small joint movements: hand biomechanics and health technology assessment[C]//IMechE Measurement and Sensing in Medicine and Health: Capturing Motion and Musculoskeletal Dynamics. London: Institute of Mechanical Engineers, 2009: 25-28. [19] 盛文倩. 个性化脊柱侧凸的有限元建模和分析[D]. 晋中: 太原理工大学, 2021. [20] 张绪树. 人体上肢肌骨系统生物力学分析及鼠标操作时腕部接触压力研究[D]. 晋中: 太原理工大学, 2017. [21] 虞沛芾, 李伟. 薄膜压力传感器的研究进展[J]. 有色金属材料与工程, 2020, 41(2): 47-54. [22] Tamez-Duque J, Cobian-Ugalde R, Kilicarslan A, et al. Real-time strap pressure sensor system for powered exoskeletons[J]. Sensors, 2015, 15(2): 4550-4563. [23] 李小彭, 郭军强, 孙万琪, 等. 混合工作模式欠驱动手设计及其接触力分析[J]. 机械工程学报, 2021, 57(1): 8-18. [24] 周丽哲, 郭媛, 张绪树, 等. 手、腕部运动姿势和角度的改变对腕管及正中神经影响的生物力学分析[J]. 医用生物力学, 2021, 36(S1): 140. [25] Chakraborty S, Nandy A, Yamaguchi T, et al. Accuracy of image data stream of a markerless motion capture system in determining the local dynamic stability and joint kinematics of human gait[J]. Journal of Biomechanics, 2020, 104: 109718. [26] Al-Jamal MF, Baniabedalruhman A, Alomari AK. Data smoothing with applications to edge detection[J]. Open Mathematics, 2022, 20(1): 492-504. [27] 申希平, 祁海萍, 刘小宁, 等. 两因素非参数方差分析在SPSS中的实现[J]. 中国卫生统计, 2013, 30(6): 913-914. [28] 钟海灵. 触屏手机屏幕尺寸对用户操作行为及舒适度影响的研究[D]. 杭州:浙江大学,2013. [29] 王瑞雪, 张绪树, 郭媛, 等. 单手操作手机时常见拇指动作关节角度与接触力测量和分析[J]. 医用生物力学, 2023, 38(4): 797-803. [30] Howard KJ, Galloy AE, Schmitz DG, et al. Ball-to-hand contact forces increase modeled shoulder torques during a volleyball spike[J]. Journal of Sports Science & Medicine, 2023, 22(3): 488-495. [31] Duncan SFM, Saracevic CE, Kakinoki R. Biomechanics of the hand[J]. Hand Clinics, 2013, 29(4): 483-492. [32] 范晓,罗伟. 浅议手部功能丧失的法医学人体损伤程度评定[C]//法医临床学专业理论与实践——中国法医学会·全国第二十届法医临床学学术研讨会论文集.乌鲁木齐: 黑龙江科学技术出版社, 2017: 121-122. [33] 陈番兴, 丁伯慧, 李铮, 等. 拇指弹琴触键动作测量与分析[J]. 电子测量与仪器学报, 2022, 36(8): 114-121. [34] 唐衡云, 王建生, 王宏民, 等. 基于手势动作传感控制机器人设计[J]. 自动化与仪器仪表, 2021(10): 190-193.