Papers

3

Total Citations

20

H-Index

2

About

Nikolas Hesse is a researcher at the intersection of computer vision, biomechanics, and rehabilitation robotics. His primary work focuses on developing markerless motion tracking systems to quantify human movement, with a particular emphasis on improving gait therapy for children and adolescents with neurological disorders. His most cited paper, a 2023 validation study (16 citations), demonstrates how markerless tracking can replace cumbersome marker-based systems to measure kinematic behavior during robot-assisted gait training—a breakthrough that lowers barriers for clinical adoption. Hesse also investigates the clinical utility of actuated pelvis movements in robotic therapy, using clustering analysis of trunk movements to determine when such interventions are beneficial based on a patient’s functional ability. Earlier in his career, he contributed to computer vision and remote sensing, evaluating image-based location recognition on large-scale UAV imagery. By combining rigorous technical validation with clinically meaningful applications, Hesse’s work directly supports more personalized, data-driven rehabilitation strategies for young patients with gait impairments.

Research Focus

Key Achievements

2
H-Index
3
Papers
20
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Markerless motion tracking to quantify behavioral changes during robot-assisted gait training: A validation study
16 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Zurich, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago