Clinical trials of GPE-based muscle support algorithm for robotic hip exoskeleton: a pilot study

Area of Science:

• Robotics
• Biomechanics
• Rehabilitation Engineering

Background:

• Aging populations face reduced physical activity and increased age-related diseases.
• Wearable robots, particularly exoskeleton robots, are crucial for gait improvement.
• Accurate gait cycle understanding is essential for effective exoskeleton control, but nonlinear trajectories pose challenges.

Purpose of the Study:

• To implement an enhanced gait phase estimation (GPE) algorithm integrated with a muscle support system using a robotic hip exoskeleton (RHE).
• To evaluate the effectiveness of gait rehabilitation training using the GPE-based muscle support algorithm.
• To assess the algorithm's applicability across different initial gait performance levels.

Main Methods:

• Utilized a robotic hip exoskeleton (RHE) to implement an enhanced gait phase estimation (GPE) algorithm.
• Integrated the GPE algorithm with a muscle support system.
• Divided participants into two groups (Group A and Group B) based on initial gait performance for comparative analysis.

Main Results:

• In the 10-meter walk test (10MWT), walking time decreased by ~5% (Group A) and ~27% (Group B).
• In the 6-minute walk test (6MinWT), walking distance increased by ~1% (Group A) and ~14% (Group B).
• Group B, with lower initial gait performance, demonstrated a greater improvement rate, confirming the algorithm's effectiveness.

Conclusions:

• The enhanced GPE algorithm integrated with a muscle support system shows significant applicability in gait rehabilitation.
• The algorithm provides greater benefits for individuals with lower initial gait performance.
• This approach holds promise for improving mobility and preventing age-related diseases through advanced wearable robotics.