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Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation


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Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group


Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

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Haptic Intelligence Intelligent Control Systems Conference Paper Enhancing Surgical Team Collaboration and Situation Awareness through Multimodal Sensing Allemang–Trivalle, A. In Proceedings of the ACM International Conference on Multimodal Interaction, 716-720, Extended abstract (5 pages) presented at the ACM International Conference on Multimodal Interaction (ICMI) Doctoral Consortium, Paris, France, October 2023 (Published)
Surgery, typically seen as the surgeon's sole responsibility, requires a broader perspective acknowledging the vital roles of other operating room (OR) personnel. The interactions among team members are crucial for delivering quality care and depend on shared situation awareness. I propose a two-phase approach to design and evaluate a multimodal platform that monitors OR members, offering insights into surgical procedures. The first phase focuses on designing a data-collection platform, tailored to surgical constraints, to generate novel collaboration and situation-awareness metrics using synchronous recordings of the participants' voices, positions, orientations, electrocardiograms, and respiration signals. The second phase concerns the creation of intuitive dashboards and visualizations, aiding surgeons in reviewing recorded surgery, identifying adverse events and contributing to proactive measures. This work aims to demonstrate an innovative approach to data collection and analysis, augmenting the surgical team's capabilities. The multimodal platform has the potential to enhance collaboration, foster situation awareness, and ultimately mitigate surgical adverse events. This research sets the stage for a transformative shift in the OR, enabling a more holistic and inclusive perspective that recognizes that surgery is a team effort.
DOI BibTeX

Haptic Intelligence Intelligent Control Systems Miscellaneous Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test: Code Khojasteh, B., Solowjow, F., Trimpe, S., Kuchenbecker, K. J. Code published as a companion to the journal article "Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test" in IEEE Transactions on Automation Science and Engineering, July 2023 (Published) DOI BibTeX