# Leadership Assessment in Pediatric Intensive Care Unit Team Training

arXiv: https://arxiv.org/abs/2505.24389 · HTML: https://mlsanity.com/paper/2505.24389/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 20 references that are in the map.
- First posted on arXiv 30 May 2025.

## Builds on (most cited first, 9 of 9)

- [Segment Anything](https://mlsanity.com/paper/2304.02643/) (2023)
- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [SAM 2: Segment Anything in Images and Videos](https://mlsanity.com/paper/2408.00714/) (2024)
- [Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives](https://mlsanity.com/paper/2311.18259/) (2023)
- [Project Aria: A New Tool for Egocentric Multi-Modal AI Research](https://mlsanity.com/paper/2308.13561/) (2023)
- [HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World](https://mlsanity.com/paper/2309.17024/) (2023)
- [EgoExoLearn: A Dataset for Bridging Asynchronous Ego- and Exo-centric View of Procedural Activities in Real World](https://mlsanity.com/paper/2403.16182/) (2024)
- [Towards Unified Surgical Skill Assessment](https://mlsanity.com/paper/2106.01035/) (2021)
- [Manipulation-skill Assessment from Videos with Spatial Attention Network](https://mlsanity.com/paper/1901.02579/) (2019)

## Built on by (most cited first, 3 of 3)

- [Multi-speaker Attention Alignment for Multimodal Social Interaction](https://mlsanity.com/paper/2511.17952/) (2025)
- [SocialDirector: Training-Free Social Interaction Control for Multi-Person Video Generation](https://mlsanity.com/paper/2605.10079/) (2026)
- [HelloWorld: Enabling Socially Interactive Characters in Video World Models](https://mlsanity.com/paper/2608.05070/) (2026)

## Abstract (arXiv)

This paper addresses the task of assessing PICU team's leadership skills by developing an automated analysis framework based on egocentric vision. We identify key behavioral cues, including fixation object, eye contact, and conversation patterns, as essential indicators of leadership assessment. In order to capture these multimodal signals, we employ Aria Glasses to record egocentric video, audio, gaze, and head movement data. We collect one-hour videos of four simulated sessions involving doctors with different roles and levels. To automate data processing, we propose a method leveraging REMoDNaV, SAM, YOLO, and ChatGPT for fixation object detection, eye contact detection, and conversation classification. In the experiments, significant correlations are observed between leadership skills and behavioral metrics, i.e., the output of our proposed methods, such as fixation time, transition patterns, and direct orders in speech. These results indicate that our proposed data collection and analysis framework can effectively solve skill assessment for training PICU teams.