Michael Bernhardt

ETH Zurich, Technical University of Munich, École Polytechnique Fédérale de Lausanne, New Jersey Institute of Technology

Papers

Total Citations

328

H-Index

About

Michael Bernhardt is a pioneering researcher in rehabilitation robotics, best known for his work on patient-cooperative control strategies for gait therapy. His most influential contribution is the development of the Lokomat, a robotic exoskeleton for treadmill training of patients with spinal cord injury or other locomotor dysfunctions. Bernhardt’s landmark 2005 paper on hybrid force-position control (171 citations) introduced a paradigm shift from rigid, predefined movement patterns to adaptive, cooperative behavior that responds to a patient’s voluntary effort. This human-centered approach, further elaborated in his 2005 work on rehabilitation robotics (41 citations), emphasizes intention detection and active patient participation rather than passive imposition of motion. He also advanced automated treadmill speed adaptation (78 citations), enabling self-paced training with natural acceleration and deceleration phases. Beyond clinical robotics, Bernhardt explored web-based command shaping for industrial robots handling swinging loads (38 citations), demonstrating versatility in control systems. His work has fundamentally influenced how rehabilitation robots are designed to promote neuroplasticity and motor recovery, making therapy more engaging and effective. Bernhardt’s research remains essential reading for engineers and clinicians developing next-generation assistive technologies.