paper-with-me

홈 › Papers

Physiologically-Informed Predictability of a Teammate's Future Actions Forecasts Team Performance

2025-01-25 · Yinuo Qin, Richard T. Lee, Weijia Zhang, Xiaoxiao Sun, Paul Sajda

In collaborative environments, a deep understanding of multi-human teaming dynamics is essential for optimizing performance. However, the relationship between individuals' behavioral and physiological markers and their combined influence on overall team performance remains poorly understood. To explore this, we designed a triadic human collaborative sensorimotor task in virtual reality (VR) and introduced a novel predictability metric to examine team dynamics and performance. Our findings reveal a strong connection between team performance and the predictability of a team member's future actions based on other team members' behavioral and physiological data. Contrary to conventional wisdom that high-performing teams are highly synchronized, our results suggest that physiological and behavioral synchronizations among team members have a limited correlation with team performance. These insights provide a new quantitative framework for understanding multi-human teaming, paving the way for deeper insights into team dynamics and performance.

📄 PDF Abstract BibTeX arXiv:2501.15328

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

On the stability of equilibria of the physiologically-informed dynamic causal model

2021-01-14 · Sayan Nag

Experimental manipulations perturb the neuronal activity. This phenomenon is manifested in the fMRI response. Dynamic causal model and its variants can model these neuronal responses along with the BOLD responses [1, 2, …

Physiologically Informed Deep Learning: A Multi-Scale Framework for Next-Generation PBPK Modeling

2026-02-09 · Shunqi Liu, Han Qiu, Tong Wang arxiv

Physiologically Based Pharmacokinetic (PBPK) modeling is a cornerstone of model-informed drug development (MIDD), providing a mechanistic framework to predict drug absorption, distribution, metabolism, and excretion (ADM…

Interpretable Concept-Guided Polynomial Tabular Kolmogorov-Arnold Network for EEG-Based Mild Cognitive Impairment Detection

2026-06-24 · Yosef Bernardus Wirian, Qiang Cheng arxiv

Early and scalable detection of mild cognitive impairment (MCI) remains an unresolved clinical challenge. Existing EEG-based screening approaches are constrained by handcrafted feature pipelines that discard neurophysiol…

Modeling Human Temporal Uncertainty in Human-Agent Teams

2020-10-09 · Maya Abo Dominguez, William La, James C. Boerkoel Jr

Automated scheduling is potentially a very useful tool for facilitating efficient, intuitive interactions between a robot and a human teammate. However, a current gapin automated scheduling is that it is not well underst…

Scheduling

Generating Plans that Predict Themselves

2018-02-14 · Jaime F. Fisac, Chang Liu, Jessica B. Hamrick, S. Shankar Sastry 외

Collaboration requires coordination, and we coordinate by anticipating our teammates' future actions and adapting to their plan. In some cases, our teammates' actions early on can give us a clear idea of what the remaind…