Manuel Fujs

ETH Zurich

Papers

2

Total Citations

11

H-Index

2

About

Manuel Fujs is a researcher focused on the intersection of sleep science, wearable sensing, and robotic intervention. His key research areas include closed-loop systems for sleep enhancement, textile-based pressure sensing, and automated classification of sleep postures. Fujs made major contributions by developing a compact textile pressure sensor mattress that uses convolutional neural networks to classify recumbent body positions with high accuracy—a critical step for enabling closed-loop robotic interventions in position-dependent sleep disorders. This work has garnered 8 citations since 2023. He also advanced the field of non-pharmacological sleep therapy by designing a closed-loop autotuning system for a robotic bed that delivers vestibular stimulation through gentle rocking, aiming to improve sleep quality and support rehabilitation outcomes. This innovative approach, cited 3 times, offers a promising alternative to conventional treatments. Fujs’s work is notable for integrating machine learning with soft robotics and wearable sensing, demonstrating a practical path toward personalized, technology-driven sleep interventions that could benefit patients with sleep disorders and those undergoing motor rehabilitation.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Sleep position classification with a compact pressure textile sensor mattress using convolutional neural networks
8 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: ETH Zurich

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago