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Updated: Jun 11, 2026
08:12
Experimental Methods to Study Human Postural Control
Published on: September 11, 2019
Concerted control framework for human-exoskeleton co-adaptation using ground reaction forces
Vahid Firouzi1,2, Arjang Ahmadi1, Dennis Haufe1
1Lauflabor Locomotion Laboratory, Centre for Cognitive Science, Sport Science Institute, Technical University of Darmstadt, Darmstadt, Germany.
Wearable Technologies
|June 10, 2026
Summary
This study introduces a novel control strategy using ground reaction force (GRF) feedback to synchronize human movement with wearable assistive devices like the BATEX exosuit, improving walking performance and reducing energy cost.
Area of Science:
- Biomechanics
- Robotics
- Human-Machine Interaction
Background:
- Coordinating human neuromuscular systems with wearable assistive devices is crucial for effective gait enhancement.
- Existing control strategies often rely on centralized or distributed systems, presenting limitations.
Purpose of the Study:
- To develop and validate a concerted control strategy synchronizing biological and artificial actuators using shared feedback.
- To investigate the role of ground reaction force (GRF) as a coordinating signal for human-exosuit interaction.
Main Methods:
- Implementation of Force Modulated Compliance (FMC) to adjust joint stiffness based on real-time GRF input.
- Application of the GRF-informed controller in an active soft biarticular thigh exosuit (BATEX).
- Testing the system in human walking experiments to assess gait performance and coordination.
Main Results:
- The GRF-informed controller significantly increased preferred walking speed.
- The system advanced the transition point from walking to running.
- A notable reduction in metabolic cost was observed during human-exosuit interaction.
Conclusions:
- GRF-based control effectively enhances human-exosuit coordination by aligning assistance with natural gait dynamics.
- This bioinspired approach provides a scalable framework for real-world locomotion support.
- Harmonizing human and robotic contributions through shared feedback is key to improving wearable assistive device performance.
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