Abstract：In order to design a feedback channel conforming to the body's own control system and sensing ability, this paper applied tactile reproduction technology, took pinching force as the perception information and vibration stimulation as the feedback information of non-pattern matching, and finally built a force-haptic perception feedback system. On this basis, the ability to control the pinching force with feedback and without feedback was assessed in 16 healthy subjects. Meanwhile, the pinching force was detected and analyzed in sections through “steady force”, “boundary proximity ratio” and “upper/lower limit relative deviation” etc. The results of three force levels, 0~10 N, 10~20 N and 20~30 N, all showed that there were significant differences in “tachieve” between the tests with and without feedback (P<0.01), which demonstrated the effectiveness of the vibration feedback device. Additionally, the median value of “boundary proximity ratio” was always lower than 0.01, indicating that people were likely to complete the experiment requirement with less force. Through the analysis of stable period andadjustive period, a similar dependent mechanism was presented that the pinch relied on the human feedforward control at low force level, while the feedback control mainly played a regulatory role at high force level.
王子文, 李可. 基于振动反馈的手指捏力响应调控机制研究[J]. 中国生物医学工程学报, 2021, 40(5): 567-573.
Wang Ziwen, Li Ke. The Regulatory Mechanism of Pinching Force Based on Vibration Feedback. Chinese Journal of Biomedical Engineering, 2021, 40(5): 567-573.
[1] Alpenfels EJ. The anthropology and social significance of the human hand [J]. Artificial Limbs, 1955, 2(2): 4-21. [2] Schmitz A, Maggiali M, Natale L, et al. Touch sensors for humanoid hands [C] //The 19th International Symposium in Robot and Human Interactive Communication. Viareggio: IEEE, 2010:691-697. [3] Caroline B, Régine R, Jean PR, et al. Combined contribution of tactile and proprioceptive feedback to hand movement perception [J]. Brain Research, 2011,1382:219-229. [4] Johansson RS, Flanagan JR. Coding and use of tactile signals from the fingertips in object manipulation tasks [J]. Nature Reviews Neuroscience, 2009, 10(5):345-359. [5] Geier A, Tucker R, Somlor S, et al. End-to-end tactile feedback loop: From soft sensor skin over deep GRU-autoencoders to tactile stimulation [J]. IEEE Robotics and Automation Letters, 2020, 5:1-1. [6] Wang D, Ohnishi K, Xu W. Multimodal haptic display for virtual reality: A survey [J]. IEEE Transactions on Industrial Electronics, 2019, 67(1):610-623. [7] Biddiss EA, Chau TT. Upper limb prosthesis use and abandonment: A survey of the last 25 years [J]. Prosthetics and Orthotics International, 2007, 31(3):236-257. [8] Nghiem BT, Sando IC, Gillespie RB, et al. Providing a sense of touch to prosthetic hands [J]. Plastic & Reconstructive Surgery, 2015, 135(6):1652-1663. [9] Benjamin SF, Gursel A, Rahim M. A Review of non-invasive sensory feedback methods for transradial prosthetic hands [J]. IEEE Access, 2018, 6:6878-6899. [10] Antfolk C, Balkenius C, Rosén B, et al. SmartHand tactile display: A new concept for providing sensory feedback in hand prostheses [J]. Scandinavian Journal of Plastic & Reconstructive Surgery, 2010, 44(1):50-53. [11] Ninu A, Dosen S, Muceli S, et al. Closed-loop control of grasping with a myoelectric hand prosthesis: Which are the relevant feedback variables for force control? [J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2014, 22(5):1041-1052. [12] Markovic M, Schweisfurth MA, Engels LF, et al. The clinical relevance of advanced artificial feedback in the control of a multi-functional myoelectric prosthesis [J]. Journal of Neuroengineering & Rehabilitation, 2018, 15(1):28-42. [13] Clemente F, D'Alonzo M, Controzzi M, et al. Non-invasive, temporally discrete feedback of object contact and release improves grasp control of closed-loop myoelectric transradial prostheses [J]. IEEE Transactions on Neural Systems & Rehabilitation Engineering, 2016, 24(12):1314-1322. [14] 吴常铖. 仿生机械假手的肌电控制及其力触觉感知反馈方法研究[D]. 南京: 东南大学, 2016. [15] 吴常铖,熊鹏文,曾洪,等. 一种基于EEG和sEMG的假手控制策略 [J]. 自动化学报, 2018, 44(4): 676-684. [16] D′ Ausilio A. Arduino: A low-cost multipurpose lab equipment [J]. Behavior Research Methods, 2012, 44(2):305-313. [17] 毕胜,燕铁斌. 运动控制原理与实践[M]. 第3版. 北京: 人民卫生出版社, 2009.
