SIPLAB: Sensing, Interaction & Perception Lab

Full-body tracking in the wild sparse wearable IMUs and UWB ranging for mobile pose estimation

play

Hand out of view interaction full around-the-body tracking for Virtual Reality using a wrist IMU

play

ViGather teleconferencing with a joint experience across PCs and Virtual Reality

play

cardiovascular monitoring measuring blood pressure each second

Haptic controllers rich haptic feedback in Virtual Reality

play

Team SIPLAB meet the people in the lab

UltraInertialPoser
HOOV
ViGather
Glabella
Haptic PIVOT
Team SIPLAB

In the SIPLAB at ETH Zürich, we're a cross-disciplinary research group in computational interaction, embodied perception, and mobile health. Our work spans human-computer interaction, mixed reality, and machine learning. We are part of the Department of Computer Science, affiliated with the Department of Information Technology & Electrical Engineering, and HCI@ETH.

egocentric motion tracking scalable methods for action & motion capture

computational interaction decoding embodied input for situated adaptive systems

predictive mobile health signal processing for physiological data in the wild

Projects to appear and recent research

ACM SIGGRAPH 2024 (to appear). Ultra Inertial Poser: Scalable Motion Capture and Tracking from Sparse Inertial Sensors and Ultra-Wideband Ranging. (preprint)
IEEE EMBC 2024 (to appear). Robust Heart Rate Detection via Multi-Site Photoplethysmography.
IEEE EMBC 2024 (to appear). Predicting Sleep Quality via Unsupervised Learning of Cardiac Activity.
ACM CUI 2024 (to appear). Chatbots With Attitude: Enhancing Chatbot Interactions Through Dynamic Personality Infusion.
ACM EICS 2024 (to appear). MARLUI: Multi-Agent Reinforcement Learning for Adaptive Point-and-Click UIs. (preprint)
ACM IMWUT 2024. The Personality Dimensions GPT-3 Expresses During Human-Chatbot Interactions.
ACM IMWUT 2024. Detecting Users' Emotional States during Passive Social Media Use.
IEEE ICRA 2024. MiBOT: A head-worn robot that modulates cardiovascular responses through human-like soft massage.
npj Digital Medicine. Modeling Multiple Sclerosis using Mobile and Wearable Sensor Data.
IEEE Transactions on Visualization and Computer Graphics 2024. Comparing Synchronous and Asynchronous Task Delivery in Mixed Reality Environments.

Affiliations and collaborations

In our projects, we collaborate with faculty and students at the Department of Health Sciences and Technology, the Robotics, Systems and Control (RSC) program at the Department of Mechanical and Process Engineering, and the Faculty of Medicine at University of Zurich.

We are part of ETH's Competence Centre for Rehabilitation Engineering and Science (ETH RESC). We are also affiliated with the ETH AI Center, the Max Planck ETH Center for Learning Systems (CLS), the ELLIS Unit Zürich, and the Zurich Information Security & Privacy Center (ZISC).