Data_Sheet_1_Grasping Ability and Motion Synergies in Affordable Tendon-Driven Prosthetic Hands Controlled by Able-Bodied Subjects.ZIP (2.4 MB)
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Data_Sheet_1_Grasping Ability and Motion Synergies in Affordable Tendon-Driven Prosthetic Hands Controlled by Able-Bodied Subjects.ZIP

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posted on 26.08.2020, 13:34 by Immaculada Llop-Harillo, Antonio Pérez-González, Javier Andrés-Esperanza

Affordable 3D-printed tendon-driven prosthetic hands are a rising trend because of their availability and easy customization. Nevertheless, comparative studies about the functionality of this kind of prostheses are lacking. The tradeoff between the number of actuators and the grasping ability of prosthetic hands is a relevant issue in their design. The analysis of synergies among fingers is a common method used to reduce dimensionality without any significant loss of dexterity. Therefore, the purpose of this study is to assess the functionality and motion synergies of different tendon-driven hands using an able-bodied adaptor. The use of this adaptor to control the hands by means of the fingers of healthy subjects makes it possible to take advantage of the human brain control while obtaining the synergies directly from the artificial hand. Four artificial hands (IMMA, Limbitless, Dextrus v2.0, InMoov) were confronted with the Anthropomorphic Hand Assessment Protocol, quantifying functionality and human-like grasping. Three subjects performed the tests by means of a specially designed able-bodied adaptor that allows each tendon to be controlled by a different human finger. The tendon motions were registered, and correlation and principal component analyses were used to obtain the motion synergies. The grasping ability of the analyzed hands ranged between 48 and 57% with respect to that of the human hand, with the IMMA hand obtaining the highest score. The effect of the subject on the grasping ability score was found to be non-significant. For all the hands, the highest tendon-pair synergies were obtained for pairs of long fingers and were greater for adjacent fingers. The principal component analysis showed that, for all the hands, two principal components explained close to or more than 80% of the variance. Several factors, such as the friction coefficient of the hand contact surfaces, limitations on the underactuation, and impairments for a correct thumb opposition need to be improved in this type of prostheses to increase their grasping stability. The principal components obtained in this study provide useful information for the design of transmission or control systems to underactuate these hands.

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