ADJUHand - A Passive Anthropomorphic Hand Model with Adjustable Finger Stiffness for Exoskeleton Evaluation

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Authors: Nico G. M. Weber, Sebastian Dietz, Jonas Wälter, Dominik I. Braun, Alessandro Del Vecchio, Jörg E. Franke
Cited by: 0
References: 8

Abstract

Each year, more than 12 million strokes and nearly one million spinal cord injuries occur worldwide. These conditions can cause severe hand impairments, leading to a significant loss of independence. Hand exoskeletons have emerged as a promising solution to support the restoration of grasping function in both rehabilitation settings and daily life. However, testing such devices remains a major challenge during the development phase. Existing hand models are either overly simplistic, lacking anatomical realism or articulation, or are complex active prosthetic systems that are costly, difficult to replicate, and not designed for passive actuation. Testing on healthy individuals introduces safety risks and bias, as their hands behave differently and may unconsciously assist movement. Moreover, direct patient testing is resource-intensive and limited. This paper presents the ADJUHand, a passive anthropomorphic hand model designed to facilitate testing of hand exoskeletons. The ADJUHand can be fabricated easily using a standard FDM 3D printer, a few screws and springs. Motion capture experiments demonstrate that the fingers follow anatomically accurate flexion trajectories with a total finger flexion angle of 249.9°. Furthermore, the stiffness of each finger can be adjusted to simulate varying levels of joint rigidity, as observed in individuals with spastic or stiff fingers. Additionally the ADJUHand enables finger abduction and thumb circumduction, facilitating diverse grasp configurations.

Fields of Study & Subjects

Prosthetics and Rehabilitation Robotics Stroke Rehabilitation and Recovery Soft Robotics and Applications

Publication details

Journal / source
IEEE/SICE International Symposium on System Integration (SII)
Pages
1061–1066
Publication date
11 January 2026
Language
EN