Hyun Sub Park

About

Hyun Sub Park is a researcher in the field of assistive robotics and human motion analysis, with a focus on developing intelligent control systems for walking assistance devices. His work centers on exoskeleton robots for paraplegic patients, where he has made key contributions to intent detection and gait generation. In his most cited paper (2011, 13 citations), Park proposed an INS/EKF-based algorithm to estimate stride length, height, and direction from user intent, enabling online gait pattern generation for walking assistance robots. This work addresses a critical challenge in real-time, adaptive control of robotic orthoses. He further advanced the field by introducing a gait phase classifier using a Recurrent Neural Network (2015, 6 citations), recognizing that walking is a dynamic system better modeled by RNNs than feedforward networks. Park also explored crutch gait pattern generation through feature extraction (2011), demonstrating his versatility in addressing different aspects of assisted locomotion. His research bridges sensor fusion, machine learning, and biomechanics, with implications for improving mobility and quality of life for individuals with lower-limb disabilities.

Research Focus

Key Achievements

Top Papers

1. 1
   INS/EKF-based stride length, height and direction intent detection for walking assistance robots

   13 citations · 2011
2. 2
   A Gait Phase Classifier using a Recurrent Neural Network

   6 citations · 2015
3. 3
   Crutch gait pattern for robotic orthoses by the use of feature extraction

   2 citations · 2011

Key Collaborators

Contact & Links