面向脑卒中康复的气袋式触觉反馈单元特性研究

张超宙; 李敏; 吴宗林; 何博; 谢俊; 徐光华

doi:10.7652/xjtuxb202306001

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面向脑卒中康复的气袋式触觉反馈单元特性研究

专题医工交叉与人机交互 | 更新时间：2025-05-08

- 面向脑卒中康复的气袋式触觉反馈单元特性研究
- Characteristics of Air Bag Haptic Feedback Unit for Stroke Rehabilitation
- 西安交通大学学报 2023年57卷第6期页码：1-9
- 作者机构：
  
  1. 西安交通大学机械工程学院,西安,710049
  2. 西安交通大学机械制造系统工程国家重点实验室,西安,710049
- 作者简介：
  
  : 2022-12-26。作者简介: 张超宙(1997—),男,博士生
  李敏(通信作者),女,副教授,博士生导师。基金项目: 国家自然科学基金资助项目(51975451)。
- 基金信息：
  
  : 2022-12-26。作者简介: 张超宙(1997—),男,博士生;李敏(通信作者),女,副教授,博士生导师。基金项目: 国家自然科学基金资助项目(51975451)。
- DOI：10.7652/xjtuxb202306001
  中图分类号： TP203
- 网络首发：2023-06-10，
  
  纸质出版：2023
- 稿件说明：
移动端阅览
张超宙, 李敏, 吴宗林, 等. 面向脑卒中康复的气袋式触觉反馈单元特性研究[J]. 西安交通大学学报, 2023,57(6):1-9.

ZHANG Chaozhou, LI Min, WU Zonglin, et al. Characteristics of Air Bag Haptic Feedback Unit for Stroke Rehabilitation[J]. 2023, 57(6): 1-9.
张超宙, 李敏, 吴宗林, 等. 面向脑卒中康复的气袋式触觉反馈单元特性研究[J]. 西安交通大学学报, 2023,57(6):1-9. DOI： 10.7652/xjtuxb202306001.

ZHANG Chaozhou, LI Min, WU Zonglin, et al. Characteristics of Air Bag Haptic Feedback Unit for Stroke Rehabilitation[J]. 2023, 57(6): 1-9. DOI： 10.7652/xjtuxb202306001.

摘要

针对现阶段气袋式触觉反馈装置难以准确呈现交互效果及同时表征触觉力和触觉面积的问题

开展了气动触觉单元的静态特征和动态特征研究。依据气动触觉单元的几何约束条件建立了静态压力分布模型

类比电路电容放电模型构建了动态压力响应模型。制作了3种规格的气袋触觉单元并进行了特征实验测试

结果表明

静态压力分布模型的拟合触觉面积误差为6.94%

中型气袋(14.4 cm×9.4 cm)及以下规格的气动单元响应时间在0.5 s以内。采用中型气袋搭建了躯干触觉反馈系统

并进行了触觉感知实验

通过调节充气限制高度以表征不同的触觉面积

通过改变气袋气压大小以表征不同的触觉力。实验结果表明

被试者对其产生的触觉面积和触觉力感知识别率分别为87.25%和89.67%。气袋式触觉反馈单元特性研究为触觉反馈装置的设计参数选择提供了依据

可以使脑卒中患者在康复训练中快速感受到触觉面积和触觉力

从而提高患者的康复训练体验。

Abstract

Considering that existing air bag haptic feedback devices cannot accurately present the interaction effect and represent the haptic force and haptic area at the same time

the static characteristics and dynamic characteristics of the pneumatic haptic unit were studied. The static pressure distribution model was established based on the geometric constraints of the pneumatic haptic unit

and the dynamic pressure response model was developed by analogy with the circuit capacitive discharge model. Three types of air bag haptic units were produced

and the characteristics tests were carried out. The results showed that the fitted haptic area error of the static pressure distribution model was 6.94%

and the response time of pneumatic units of medium-sized air bag(14.4 cm×9.4 cm)and below was within 0.5 s. A torso haptic feedback system was developed using the medium-sized air bag

and haptic perception experiments were carried out as well. Different haptic areas were represented by adjusting the height of the inflation limit

and different haptic forces were represented by changing the air pressure of the air bag. The results showed that the recognition rates of haptic area and haptic force were 87.25% and 89.67%

respectively. The study on characteristics of air bag haptic feedback unit for stroke rehabilitation provides a basis for the selection of design parameters of the haptic feedback device which can enable stroke patients to quickly perceive the haptic area and haptic force during rehabilitation training to improve the rehabilitation training experience of patients.

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references

YEKUTIEL M. Sensory re-education of the hand after stroke [M]. Hoboken, NJ, USA: Wiley, 2002.[2] GHEZ C, GORDON J, GHILARDI M F, et al. Roles of proprioceptive input in the programming of arm trajectories [J]. Cold Spring Harbor Symposia on Quantitative Biology, 1990, 55: 837-847.[3] COLLINS D F, CAMERON T, GILLARD D M, et al. Muscular sense is attenuated when humans move [J]. The Journal of Physiology, 1998, 508(2): 635-643.[4] SMITH P S, DINSE H R, KALISCH T, et al. Effects of repetitive electrical stimulation to treat sensory loss in persons poststroke [J]. Archives of Physical Medicine and Rehabilitation, 2009, 90(12): 2108-2111.[5] MINOGUE J, JONES M G. Haptics in education: exploring an untapped sensory modality [J]. Review of Educational Research, 2006, 76(3): 317-348.[6] 张海涛. 气动触觉感知再现装置的研究 [D]. 哈尔滨: 哈尔滨工业大学, 2007.[7] MINAMIZAWA K, FUKAMACHI S, KAJIMOTO H, et al. Wearable haptic display to present virtual mass sensation [C]//ACM SIGGRAPH 2007 sketches. New York, NY, USA: Association for Computing Machinery, 2007: 43.[8] 李莅圆, 吴涓, 宋爱国. 基于穿戴型振动触觉数据腰带的方位提示实验研究 [J]. 东南大学学报(自然科学版), 2009, 39(S2): 82-86.LI Liyuan, WU Juan, SONG Aiguo. Directional cueing experiments of wearable vibrotactile belt [J]. Journal of Southeast University(Natural Science Edition), 2009, 39(S2): 82-86.[9] 袁丽, 李航真, 胥泽华, 等. 触觉振动反馈训练对脑卒中后偏瘫患者平衡及行走功能的影响 [J]. 中华物理医学与康复杂志, 2022, 44(10): 888-893.YUAN Li, LI Hangzhen, XU Zehua, et al. Tactile vibration feedback training can improve the balance and walking of stroke survivors [J]. Chinese Journal of Physical Medicine and Rehabilitation,2022, 44(10): 888-893.[10] CASINI S, MORVIDONI M, BIANCHI M, et al. Design and realization of the CUFF: clenching upper-limb force feedback wearable device for distributed mechano-tactile stimulation of normal and tangential skin forces [C]//2015 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS). Piscataway, NJ, USA: IEEE, 2015: 1186-1193.[11] 胡建浩. 智能假肢手的多模态感知反馈及生机交互训练 [D]. 哈尔滨: 哈尔滨工业大学, 2019.[12] 贺凯, 于鹏, 赵亮, 等. 电触觉皮肤机理仿真与刺激模式量化评估 [J]. 仪器仪表学报, 2016, 37(4): 920-930.HE Kai, YU Peng, ZHAO Liang, et al. Quantitative evaluation of electrotactile feeling for the cutaneous nervous mechanism simulation and stimulation method [J]. Chinese Journal of Scientific Instrument, 2016, 37(4): 920-930.[13] GALOFARO E, D'ANTONIO E, LOTTI N, et al. Rendering immersive haptic force feedback via neuromuscular electrical stimulation [J]. Sensors, 2022, 22(14): 5069.[14] 颜泽荣. 基于气囊阵列的柔性机器人皮肤设计及触觉感知研究 [D]. 重庆: 重庆大学, 2020.[15] WANG Haoyu, CHENG Xiang, HUANG Pei, et al. A soft electro-hydraulic pneumatic actuator with self-sensing capability toward multi-modal haptic feedback [J]. Actuators, 2022, 11(3): 74.[16] DELAZIO A, NAKAGAKI K, KLATZKY R L, et al. Force jacket: pneumatically-actuated jacket for embodied haptic experiences [C]//Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery, 2018: 320.[17] ROGNON C, KOEHLER M, DURIEZ C, et al. Soft haptic device to render the sensation of flying like a drone [J]. IEEE Robotics and Automation Letters, 2019, 4(3): 2524-2531.[18] AMBROSI G, BICCHI A, DE ROSSI D, et al. The role of contact area spread rate in haptic discrimination of softness [C]//Proceedings of 1999 IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 1999: 305-310.[19] RIVA G. Virtual reality in neuro-psycho-physiology: cognitive, clinical and methodological issues in assessment and rehabilitation [M]. Amsterdam, Netherlands: IOS Press, 1997.[20] LI Min, WU Zonglin, ZHAO Chenguang, et al. Facial expressions-controlled flight game with haptic feedback for stroke rehabilitation: a proof-of-concept study [J]. IEEE Robotics and Automation Letters, 2022, 7(3): 6351-6358.[21] ROBIN A. Paper bag problem [J]. Mathematics Today-Bulletin of the Institute of Mathematics and Its Applications, 2004, 40(3): 104-107.[22] USEVITCH N S, STANLEY A A. Cutting the cord: soft haptic devices without a pressure source [C]//2019 2nd IEEE International Conference on Soft Robotics(RoboSoft). Piscataway, NJ, USA: IEEE, 2019: 49-55.[23] RENNELS D C, HUDSON H M. Pipe flow: a practical and comprehensive guide [M]. Hoboken, NJ, USA: John Wiley & Sons, 2012.[24] BROOKS T L. Telerobotic response requirements [C]//1990 IEEE International Conference on Systems, Man, and Cybernetics. Piscataway, NJ, USA: IEEE, 1990: 113-120.[25] JARRETT C, MCDAID A. Modeling and feasibility of an elastomer-based series elastic actuator as a haptic interaction sensor for exoskeleton robotics [J]. IEEE/ASME Transactions on Mechatronics, 2019, 24(3):1325-1333.

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