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Tytuł artykułu

Bydgostian hand exoskeleton - own concept and the biomedical factors

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
An exoskeleton is defined as a distinctive kind of robot to be worn as an overall or frame, effectively supporting, or in some cases substituting for, the user’s own movements. In this paper a new three-dimensional (3D) printed bydgostian hand exoskeleton is introduced and biomedically characterized. The proposed concept is promising, and the described approach combining biomechanical factors and 3D modeling driven by detailed hand exoskeleton patterns may constitute a key future method of ergonomic hand exoskeleton design and validation prior to manufacturing. Despite the aforementioned approach, we should be aware that hand exoskeleton constitutes hand support and rehabilitation robot system developing with the user; thus, certain coordination and continuity of the “hardware” part of the whole system and the training paradigm are essential for therapy efficacy.
Rocznik
Strony
art. no. 20190003
Opis fizyczny
Bibliogr. 25 poz., rys.
Twórcy
  • Department of Psychology, Kazimierz Wielki University, Bydgoszcz, Poland
  • Institute of Mechanics and Applied Computer Sciences, Kazimierz Wielki University, Bydgoszcz, Poland
autor
  • Institute of Mechanics and Applied Computer Sciences, Kazimierz Wielki University, Bydgoszcz, Poland
  • Institute of Mechanics and Applied Computer Sciences, Kazimierz Wielki University, Bydgoszcz, Poland
Bibliografia
  • [1] Burns MK, Van Orden K, Patel V, Vinjamuri R. Towards a wearable hand exoskeleton with embedded synergies. Conf Proc IEEE Eng Med Biol Soc 2017;2017:213-6.
  • [2] Kim S, Lee J, Park W, Bae J. Quantitative evaluation of hand functions using a wearable hand exoskeleton system. IEEE Int Conf Rehabil Robot 2017;2017:1488-93.
  • [3] Zhang F, Fu Y, Zhang Q. Experiments and kinematics analysis of a hand rehabilitation exoskeleton with circuitous joints. Biomed Mater Eng 2015;26(Suppl 1):S665-72.
  • [4] Hansen C, Gosselin F, Ben Mansour K, Devos P, Marin F. Design-validation of a hand exoskeleton using musculoskeletal modeling. Appl Ergon 2018;68:283-8.
  • [5] Mikołajewska E. Terapia ręki. Diagnoza i terapia. Warszawa: Soyer, 2016.
  • [6] Mikołajewska E. Terapia ręki - warsztat. Biomechaniczna analiza zabaw. Bydgoszcz: FEM, 2017.
  • [7] Chow YK, Masiak J, Mikołajewska E, Mikołajewski D, Wójcik GM, Wallace B, et al. Limbic brain structures and burnout – a systematic review. Adv Med Sci 2018;63:192-8.
  • [8] Wójcik GM, Masiak J, Kawiak A, Kwaśniewicz L, Schneider P, Polak N, et al. Mapping the human brain in frequency band analysis of brain cortex electroencephalographic activity for selected psychiatric disorders. Front Neuroinform 2018;12:73.
  • [9] Wójcik GM, Masiak J, Kawiak A, Kwaśniewicz L, Schneider P, Polak N, et al. New Protocol for quantitative analysis of brain cortex electroencephalographic activity in patients with psychiatric disorders. Front Neuroinform 2018;12:27.
  • [10] Kopowski J, Rojek I, Mikołajewski D, Macko M. 3D printed hand exoskeleton - own concept. In: Trojanowska J, Ciszak O, Machado JM, Pavlenko I, editors. Advances in manufacturing II - vol. 1. - Solutions for industry 4.0. Series: Lecture Notes in Mechanical Engineering. Heidelberg, New York: Springer, 2019.
  • [11] Hill D, Holloway CS, Morgado Ramirez DZ, Smitham P, Pappas Y. What are user perspectives of exoskeleton technology? A literature review. Int J Technol Assess Health Care 2017;33:160-7.
  • [12] Wolff J, Parker C, Borisoff J, Mortenson WB, Mattie J. A survey of stakeholder perspectives on exoskeleton technology. J Neuroeng Rehabil 2014;11:169.
  • [13] Ngeo J, Tamei T, Shibata T, Orlando MF, Behera L, Saxena A, et al. Control of an optimal finger exoskeleton based on continuous joint angle estimation from EMG signals. Conf Proc IEEE Eng Med Biol Soc 2013;2013:338-41.
  • [14] Bos RA, Haarman CJ, Stortelder T, Nizamis K, Herder JL, Stienen AH, et al. A structured overview of trends and technologies used in dynamic hand orthoses. J Neuroeng Rehabil 2016;13:62.
  • [15] Yue Z, Zhang X, Wang J. Hand rehabilitation robotics on poststroke motor recovery. Behav Neurol 2017;2017:3908135.
  • [16] Rose CG, Kann CK, Deshpande AD, O’Malley MK. Estimating anatomical wrist joint motion with a robotic exoskeleton. IEEE Int Conf Rehabil Robot 2017;2017:1437-42.
  • [17] Proietti T, Guigon E, Roby-Brami A, Jarrassé N. Modifying upper-limb inter-joint coordination in healthy subjects by training with a robotic exoskeleton. J Neuroeng Rehabil 2017;14:55.
  • [18] Wu G, van der Helm FC, Veeger HE, Makhsous M, Van Roy P, Anglin C, et al. ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion - part II: shoulder, elbow, wrist and hand. J Biomech 2005;38:981-92.
  • [19] Chan SS, Moran DW. Computational model of a primate arm: from hand position to joint angles, joint torques and muscle forces. J Neural Eng 2006;3:327-37.
  • [20] Garner BA, Pandy MG. Musculoskeletal model of the upper limb based on the visible human male dataset. Comput Methods Biomech Biomed Engin 2001;4:93-126.
  • [21] Li J, Zheng R, Zhang Y, Yao J. iHandRehab: an interactive hand exoskeleton for active and passive rehabilitation. IEEE Int Conf Rehabil Robot 2011;2011:5975387.
  • [22] Wang J, Li J, Zhang Y, Wang S. Design of an exoskeleton for index finger rehabilitation. Conf Proc IEEE Eng Med Biol Soc 2009;2009:5957-60.
  • [23] Krüger M, Eggert T, Straube A. Joint angle variability in the time course of reaching movements. Clin Neurophysiol 2011;122:759-66.
  • [24] Kulig K, Andrews JG, Hay JG. Human strength curves. Exerc Sport Sci Rev 1984;12:417-66.
  • [25] Kapandji AI. The clinical evaluation of the upper limb joints’ function: back to Hippocrates. Hand Clin 2003;19:379-86.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3872249e-ea9c-4233-a449-5e3968de932a
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