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Article | Open Access

Enhancing Hand Rehabilitation Through Interactive Design

Xiaotian Sun1Sitong Lu1( )Jiaqi Fan1,2
School of Mechanical and Materials Engineering, North China University of Technology, Beijing 100144, China
School of Human Comprehensive Sciences, University of Tsukuba, Tsukuba 305-8577, Japan
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Abstract

The demand for hand rehabilitation services is increasing currently, and there are many choices of hand rehabilitation products available on the market. Here, we report a flexible curvature sensor-based data glove, equipped with a built-in light trigger system, which is expected to provide active signal feedback for better human machine interface experience. By analyzing user needs and leveraging advancements in human-computer interaction, this new design not only facilitates physical recovery but also fosters a sense of ownership and motivation among patients. The incorporation of real-time feedback mechanisms further amplifies the efficacy of the rehabilitation process, propelling patients toward greater independence and self-assurance. Specially from an emotional point of view, the elements, such as functionality, design, color, material, and human-computer interaction, based on user needs, would be analyzed to summarize some core requirements. Then the performance of hand movements is integrated into the rehabilitation process through visual feedback to address the problem of monotony during training. This design can leverage the feedback mechanism between visual cues and hand movements, enhancing the sensory interaction experience between individuals and the product. Finally, it is proved by experiment this proposed design is very potential to help improve patients’ motivation and self-efficacy in training, thereby enhancing the effectiveness of rehabilitation. By combining these elements, we believed that the design is expected to make up some emotional support for better human machine interface experience.

References

[1]

I. V. A. N. Grubišić, S. K. Hana, and G. Simeon, Novel approaches in hand rehabilitation, Period. Biologorum, vol. 117, no. 1, pp. 139–145, 2015.

[2]
H. S. Cao, Design and study of a wearable upper limb exoskeleton, PhD dissertation, Shanghai Jiao Tong University, China, 2017.
[3]
M. Y. Li, Research on stroke rehabilitation equipment based on healthy limb, master’s dissertation, Yanshan University, China, 2017.
[4]
X. C. Liu, Design research of product and treatment design to simulate stroke hemiplegic patients to use their more-involved limbs during daily lives, master’s dissertation, Zhejiang University, China, 2018.
[5]
Z. L. Wang, Design of hand rehabilitation aids for stroke patients based on cross-education effect, master’s dissertation, Shandong University, China, 2021.
[6]

L. Zhou, Intelligent music rehabilitation hand based on voice recognition, IOP Conf. Ser.: Mater. Sci. Eng., vol. 612, no. 4, p. 042080, 2019.

[7]

S. H. Yang, C. L. Koh, C. H. Hsu, P. C. Chen, J. W. Chen, Y. H. Lan, Y. Yang, Y. D. Lin, C. H. Wu, H. K. Liu, et al., An instrumented glove-controlled portable hand-exoskeleton for bilateral hand rehabilitation, Biosensors, vol. 11, no. 12, pp. 495, 2021.

[8]
The James Dyson Foundation, HOPES, https://www.jamesdysonaward.org/zh-CN/2021/project/hopes/, 2023.
[9]

S. Ueki, H. Kawasaki, S. Ito, Y. Nishimoto, M. Abe, T. Aoki, Y. Ishigure, T. Ojika, and T. Mouri, Development of a hand-assist robot with multi-degrees-of-freedom for rehabilitation therapy, IEEE/ASME Trans. Mechatron., vol. 17, no. 1, pp. 136–146, 2012.

[10]
A. R. Moital, S. Dogramadzi, and H. A. Ferreira, Development of an EMG controlled hand exoskeleton for post-stroke rehabilitation, in Proc. 3rd 2015 Workshop on ICTs for improving Patients Rehabilitation Research Techniques, Lisbon, Portugal, 2015, pp. 66–722.
[11]
M. Cempini, S. M. M. De Rossi, T. Lenzi, M. Cortese, F. Giovacchini, N. Vitiello, and M. C. Carrozza, Kinematics and design of a portable and wearable exoskeleton for hand rehabilitation, in Proc. IEEE 13th Int. Conf. Rehabilitation Robotics (ICORR), Seattle, WA, USA, 2013, pp. 1–6.
[12]

F. Pichiorri, G. Morone, M. Petti, J. Toppi, I. Pisotta, M. Molinari, S. Paolucci, M. Inghilleri, L. Astolfi, F. Cincotti, et al., Brain–computer interface boosts motor imagery practice during stroke recovery, Ann. Neurol., vol. 77, no. 5, pp. 851–865, 2015.

[13]

M. Pust, E. Ivanova, H. Schmidt, and J. Krüger, Design of a pressure sensitive matrix for analyzing direct haptic patient-therapist interaction in motor rehabilitation after stroke, Curr. Dir. Biomed. Eng., vol. 3, no. 1, pp. 57–61, 2017.

[14]

P. Heo, G. M. Gu, S. J. Lee, K. Rhee, and J. Kim, Current hand exoskeleton technologies for rehabilitation and assistive engineering, Int. J. Precis. Eng. Manuf., vol. 13, no. 5, pp. 807–824, 2012.

[15]

Z. Yue, X. Zhang, and J. Wang, Hand rehabilitation robotics on poststroke motor recovery, Behav. Neurol., vol. 2017, p. 3908135, 2017.

[16]

M. V. Arteaga, J. C. Castiblanco, I. F. Mondragon, J. D. Colorado, and C. Alvarado-Rojas, EMG-driven hand model based on the classification of individual finger movements, Biomed. Signal Process. Contr., vol. 58, pp. 101834, 2020.

[17]

Y. Liu, X. Li, A. Zhu, Z. Zheng, and H. Zhu, Design and evaluation of a surface electromyography-controlled lightweight upper arm exoskeleton rehabilitation robot, Int. J. Adv. Rob. Syst., vol. 18, no. 3, p. 172988142110034, 2021.

[18]

T. du Plessis, K. Djouani, and C. Oosthuizen, A review of active hand exoskeletons for rehabilitation and assistance, Robotics, vol. 10, no. 1, pp. 40, 2021.

[19]

P. Tran, S. Jeong, K. Herrin, and J. Desai, Review: Hand exoskeleton systems, clinical rehabilitation practices, and future prospects, IEEE Trans. Med. Robot. Bionics, vol. 3, no. 3, pp. 606–622, 2021.

[20]

C. Laschi, B. Mazzolai, and M. Cianchetti, Soft robotics: Technologies and systems pushing the boundaries of robot abilities, Sci. Robot., vol. 1, no. 1, p. eaah3690, 2016.

[21]

T. Shahid, D. Gouwanda, S. G. Nurzaman, and A. A. Gopalai, Moving toward soft robotics: A decade review of the design of hand exoskeletons, Biomimetics, vol. 3, no. 3, p. 17, 2018.

[22]
P. W. Ferguson, Y. Shen, and J. Rosen, Hand exoskeleton systems—Overview, in Wearable Robotics, J. Rosen and P. W. Ferguson Eds. Amsterdam, The Netherlands: Elsevier, 2020, pp. 149–175.
[23]

C. G. Rose and M. K. O’Malley, Hybrid rigid-soft hand exoskeleton to assist functional dexterity, IEEE Robot. Autom. Lett., vol. 4, no. 1, pp. 73–80, 2019.

[24]

M. Sarac, M. Solazzi, and A. Frisoli, Design requirements of generic hand exoskeletons and survey of hand exoskeletons for rehabilitation, assistive, or haptic use, IEEE Trans. Haptics, vol. 12, no. 4, pp. 400–413, 2019.

[25]

M. H. Abdelhafiz, L. N. S. Andreasen Struijk, S. Dosen, and E. G. Spaich, Biomimetic tendon-based mechanism for finger flexion and extension in a soft hand exoskeleton: Design and experimental assessment, Sensors, vol. 23, no. 4, p. 2272, 2023.

[26]

T. Bagneschi, D. Chiaradia, G. Righi, G. Del Popolo, A. Frisoli, and D. Leonardis, A soft hand exoskeleton with a novel tendon layout to improve stable wearing in grasping assistance, IEEE Trans. Haptics, vol. 16, no. 2, pp. 311–321, 2023.

[27]

R. C. Silva, B. G. Lourenço, P. H. F. Ulhoa, E. A. F. Dias, F. L. da Cunha, C. P. Tonetto, L. G. Villani, C. B. S. Vimieiro, G. A. Lepski, M. Monjardim, et al., Biomimetic design of a tendon-driven myoelectric soft hand exoskeleton for upper-limb rehabilitation, Biomimetics, vol. 8, no. 3, p. 317, 2023.

[28]

T. Bützer, O. Lambercy, J. Arata, and R. Gassert, Fully wearable actuated soft exoskeleton for grasping assistance in everyday activities, Soft Robot., vol. 8, no. 2, pp. 128–143, 2021.

CAAI Artificial Intelligence Research
Article number: 9150041
Cite this article:
Sun X, Lu S, Fan J. Enhancing Hand Rehabilitation Through Interactive Design. CAAI Artificial Intelligence Research, 2024, 3: 9150041. https://doi.org/10.26599/AIR.2024.9150041

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Received: 02 December 2023
Revised: 08 July 2024
Accepted: 23 July 2024
Published: 07 November 2024
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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