Research Analyzer
← Back ICRA 2026

Estimation of Gait Phase of Human Stair Descent Walking Based on Phase Variable Approach

MyeongJu Cha, Pilwon Hur

PDF

AI summary

Key figure (auto-extracted from paper)
A novel blended phase variable method reliably estimates stair descent gait phase by combining hip position and thigh angle data, enabling smoother and more accurate prosthetic control.
gait phase estimation stair descent phase variable powered prostheses wearable robotics blending method

Problem

Existing phase estimation methods rely on thigh angles that follow a sinusoidal pattern during level walking, but this pattern breaks down during stair descent. This gap hinders the synchronization of powered lower-limb prostheses and exoskeletons.

Approach

The method splits the gait cycle into stance and swing phases, using hip position for stance and thigh angle for swing. These are unified into a single phase variable with a weighted blending technique to ensure smooth transitions at the phase transition point.

Key results

  • Novel phase variable formulation using hip position for stance and thigh angle for swing phases
  • Blending technique that eliminates non-smooth transitions at the phase transition point
  • Real-time feasible estimation using averaged parameters from previous gait cycles
  • Validated reliable phase estimation performance across 12 healthy subjects using motion capture and IMU data

Why it matters

Enables more synchronized and comfortable control for powered lower-limb prostheses and exoskeletons during complex stair descent tasks.

Abstract

Synchronization between a wearer and a lower limb powered prosthesis is important for effective control. Typically, phase variable-based phase estimation methods are employed. However, there is a noticeable lack of studies focusing on estimating the gait phase during stair descent, likely due to the difficulty in generating a reliable phase variable. In most studies, the thigh angle is used to generate phase variables for level walking because it follows a sinusoidal pattern. However, during stair descent, the thigh angle exhibits only a partially sinusoidal shape, making it challenging to apply the methods used for level walking. In this study, we propose a novel phase variable generation method to address the difficulty of using only the thigh angle for stair descent. To estimate the gait phase reliably, the phase variable is defined differently for the stance and swing phases: the hip position is used to generate the phase variable during the stance phase, and the thigh angle is used during the swing phase. These phase variables are then unified into a single phase variable (PV-ENT) for the entire gait cycle of stair descent. During this unification process, a non-smooth transition occurs around the phase transition point. To address this, a blending method is applied. The proposed method was validated using the data from 12 healthy subjects, collected through a motion capture system and IMU sensors. The results demonstrate a reliable phase estimation performance. Moreover, the blending method successfully improves the smoothness of the phase variable around the phase transition point without reducing the overall phase estimation performance.

Index terms

Wearable Robotics Prosthetics and Exoskeletons Intention Recognition

Related papers