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A 2-DoF Ankle Rehabilitation Platform Based on an Inclined Dual-Cylinder Mechanism

Donggeon Kim, Kira Kiefer, Luisa Veits, Laura Ulbl, Necolle Morgado-Vega, Tae-Hyoung Kim, Yeongmi Kim

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Key figure (auto-extracted from paper)
A compact two-motor ankle rehabilitation platform achieves clinically relevant 2-DoF motion with sub-degree tracking precision using a novel inclined dual-cylinder mechanism.
Ankle rehabilitation parallel mechanism dual-cylinder active control gamification robotic therapy

Problem

Existing parallel ankle rehabilitation robots rely on complex, multi-actuator structures that hinder clinical adoption, while conventional methods lack objective quantification and precise control.

Approach

Two stepper motors drive cylinders on a shared 9° inclined surface to geometrically couple and produce dorsiflexion/plantarflexion and inversion/eversion, controlled via a PSO-tuned PD controller and an FSR-based insole for active mode.

Key results

  • Achieves up to 18° tilt per axis for clinically relevant range
  • Maintains RMS tracking error below 0.35° across full motion
  • Enables CoP-based active control via FSR insole
  • Validates interactive training with IMU-integrated VR gamification

Why it matters

Simplifies robotic ankle rehabilitation hardware and control, making precise, interactive therapy more accessible for clinical and home-based use.

Abstract

This paper presents a novel ankle rehabilitation platform based on an inclined dual-cylinder mechanism that provides 2-DoF motion through geometric coupling, without complex multi-link structures. Two cylinders sharing a 9° inclined contact surface are driven by two stepper motors, enabling simultaneous dorsiflexion/plantarflexion and inver- sion/eversion of up to 18° in each axis. The platform provides both a passive mode, which follows predefined trajectories, and an active mode, which captures user intent through center-of- pressure estimation using a force-sensing resistor–based insole. A Particle Swarm Optimization–tuned PD controller is used in both modes, achieving an RMS tracking error below 0.35°in experimental validation. An IMU-integrated gamification envi- ronment further demonstrates the feasibility of the platform as an interactive active training system.

Index terms

Rehabilitation Robotics Mechanism Design Motion Control

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