Papers

4

Total Citations

43

H-Index

3

About

Jan Kuschan is a leading researcher in industrial ergonomics and human-robot collaboration, with a focus on mitigating musculoskeletal disorders in manual assembly. His work centers on developing soft robotic exosuits and inertial measurement unit (IMU)-based systems to detect worker fatigue and recognize human actions in real time. His most cited paper (2021, 34 citations) introduces a novel fatigue recognition method for overhead assembly tasks, using machine learning to automatically identify physical stress and trigger exosuit assistance. This contribution directly addresses a major cause of workplace injury and absenteeism. Kuschan also created a specialized IMU-based human action recognition dataset for cyclic overhead car assembly and disassembly (2022), filling a critical gap in industrial motion datasets that are essential for advancing exoskeleton control and human-robot interaction. His 2021 work on IMU-based action recognition for soft-robotic exoskeletons further demonstrates his commitment to reducing discomfort and stiffness in wearable assistive devices. Additionally, Kuschan contributed to the "Production environment of tomorrow" (ProMo) project, developing a partially automated repair process for small tool moulds, targeting the needs of SMEs. Through these efforts, Kuschan is shaping safer, more efficient industrial workplaces.

Research Focus

Key Achievements

3
H-Index
4
Papers
43
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Fatigue recognition in overhead assembly based on a soft robotic exosuit for worker assistance
34 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Fraunhofer Institute for Production Systems and Design Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago