Robotics (Jun 2023)

Finger Joint Stiffness Estimation with Joint Modular Soft Actuators for Hand Telerehabilitation

  • Fuko Matsunaga,
  • Shota Kokubu,
  • Pablo Enrique Tortos Vinocour,
  • Ming-Ta Ke,
  • Ya-Hsin Hsueh,
  • Shao Ying Huang,
  • Jose Gomez-Tames,
  • Wenwei Yu

DOI
https://doi.org/10.3390/robotics12030083
Journal volume & issue
Vol. 12, no. 3
p. 83

Abstract

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In a telerehabilitation environment, it is difficult for a therapist to understand the condition of a patient’s finger joints because of the lack of direct assessment. In particular, not enabling the provision of spasticity evaluation significantly reduces the optimal performance of telerehabilitation. In a previous study, it has been proposed that finger stiffness could be estimated using an analytical model of a whole-finger soft actuator. However, because the whole-finger soft actuators require high air pressure for high bending performance and are costly to customize for each patient, using joint modular soft actuators for telerehabilitation turns to be a necessity, though stiffness estimation with joint modular soft actuators has not been studied yet. Another problem is caused by using a marker-based joint angle measurement, which requires the markers to be attached to the exact positions, and limits its application in telerehabilitation. In this study, we proposed a procedure of finger joint stiffness estimation that combines information acquired from a joint modular soft actuator and a marker-less hand joint position acquisition device. Correction parameters were added to the previous analytical model for -the bending analysis of a joint assisted using a joint modular soft actuator. Moreover, a multi-variate regression model was implemented for correcting joint angles obtained from the hand joint position acquisition device. As a result, a reasonable accuracy of stiffness estimation was achieved for rehabilitation with the joint modular soft actuators, which suggests the possibility of using the proposed method to evaluate the finger spasticity in a telerehabilitation environment. This is a big step forward towards optimal hand telerehabilitation.

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