Marion Gebhard

About

Marion Gebhard is a prominent researcher specializing in assistive robotics, human-robot interaction, and accessible interface design, with a particular focus on empowering individuals with severe motor impairments such as tetraplegia. Her work centers on developing innovative hands-free control systems that restore autonomy to people with limited or no limb mobility. Gebhard is best known for creating and iteratively refining AMiCUS (Adaptive Head Motion Control for User-friendly Support), a groundbreaking assistive robot system that enables tetraplegics to control a six-degree-of-freedom robotic arm using only head motion and gestures. This work, documented across multiple highly cited publications, has garnered over 50 citations for its foundational 2017 study alone and continues to attract significant academic attention. Her contributions extend to infrastructureless head- and eye-gaze interfaces, sensor fusion algorithms, and MARG-sensor-based orientation estimation, demonstrating a sophisticated command of both hardware design and signal processing. With a cumulative citation count exceeding 200 across her top works, Gebhard's research has meaningfully advanced the field of rehabilitation robotics. Her AMiCUS 2.0 development, tested with a patient with progressive multiple sclerosis, exemplifies her commitment to personalized, real-world application. Her research represents a vital bridge between cutting-edge robotics engineering and inclusive, human-centered technology design.

Research Focus

Key Achievements

Top Papers

1. 1
   Head Motion and Head Gesture-Based Robot Control: A Usability Study

   51 citations · 2017
2. 2
   Towards Robust Robot Control in Cartesian Space Using an Infrastructureless Head- and Eye-Gaze Interface

   37 citations · 2021
3. 3
   AMiCUS—A Head Motion-Based Interface for Control of an Assistive Robot

   35 citations · 2019
4. 4
   A novel head gesture based interface for hands-free control of a robot

   30 citations · 2016
5. 5
   Performance Analysis of a Head and Eye Motion-Based Control Interface for Assistive Robots

   16 citations · 2020
6. 6
   Evaluation of control modes for head motion-based control with motion sensors

   16 citations · 2015
7. 7
   SteadEye-Head—Improving MARG-Sensor Based Head Orientation Measurements Through Eye Tracking Data

   13 citations · 2020
8. 8
   Visual Sensor Fusion Based Autonomous Robotic System for Assistive Drinking

   11 citations · 2021
9. 9
   AMiCUS 2.0—System Presentation and Demonstration of Adaptability to Personal Needs by the Example of an Individual with Progressed Multiple Sclerosis

   10 citations · 2020
10. 10
    HUMAN-ROBOT SYNERGY FOR COOPERATIVE ROBOTS

    10 citations · 2016

Key Collaborators

Contact & Links