Design of Single Degree-of-Freedom Mechanisms for Hand Neurorehabilitation

TLDR: Three different kinematic mechanisms have been designed and analyzed to train four different functions: wrist flexion/extension, wrist ulnar and radial deviation, forearm pronation/supination, and gross hand opening-closing.

Abstract: Hand rehabilitation requires intensive training of various gross and fine movements Robotic devices have been developed and tested for implementing intense training of different hand functions in the current literature Current hand rehabilitation robots can be broadly grouped into two categories: (a) simple robots with one or two degrees-of-freedom (DOF) that train only one or two hand functions; or (b) complex robots with several DOF capable of training a wide range of functions Thus, to train different hand functions, we either need a set of simple robots or one complex robot, both of which are not economically viable solutions A potential solution is to have a single DOF robot that can train a wide range of functions, ie a robot with a single actuator, along with a set of easily pluggable passive mechanisms for different hand functions In this paper, we present the design and analysis of various kinematic mechanisms for a single DOF hand rehabilitation robot plug and train hand rehabilitation robot (PLUTO) Three different kinematic mechanisms have been designed and analyzed to train four different functions: wrist flexion/extension, wrist ulnar and radial deviation, forearm pronation/supination, and gross hand opening-closing Proper alignment of the robot and human joints is essential for safe and appreciate interaction with a human Misalignment in the robot and human joints can cause undesired forces on the human joint, makes the interaction potentially unsafe The problem of misalignment was addressed in the proposed mechanisms through the use of appropriate passive DOFs between the robot and human joints This paper presents the design and analysis of the three mechanisms for the different hand functions The analysis of the mechanisms were carried out by considering variations in human hand anthropometry, and uncertainty in the robot-human axis alignments