@inproceedings{ace86ca8ecc242a09d2a0c04559271e2,
title = "EGG: AI-Based Interactive Design Object for Managing Post-operative Pain in Children",
abstract = "The anticipation and effective management of pain in pediatric patients is an essential component of healthcare. AI-based interactive technologies can enhance postoperative pain management by objectively measuring pain and providing an effective distraction for children. This paper presents EGG, an AI-based interactive toy designed to estimate individual pain levels and subsequently engage the children through an immersive experience utilizing visual, tactile, and audio stimuli. An exploratory study involving 16 university students was conducted to assess EGG{\textquoteright}s capability to distract users from stressful situations. The findings indicate that EGG serves as an effective tool for shifting attention away from stressful tasks and towards interactions with the device. This study explores and demonstrates an approach to utilizing AI in the design of smart interactive products for pain measurement and management.",
keywords = "Interactive toy, Machine Learning, Pain management",
author = "Jing Li and Kuankuan Chen and Liuyiyi Yang and Milou Mutsaers and Emilia Barakova",
year = "2024",
month = may,
day = "31",
doi = "10.1007/978-3-031-61140-7_31",
language = "English",
isbn = "978-3-031-61139-1",
series = "Lecture Notes in Computer Science (LNCS)",
publisher = "Springer",
pages = "322--331",
editor = "{Ferr{\'a}ndez Vicente}, {Jos{\'e} Manuel} and {Val Calvo}, Mikel and Hojjat Adeli",
booktitle = "Artificial Intelligence for Neuroscience and Emotional Systems",
address = "Germany",
note = "10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024 ; Conference date: 04-06-2024 Through 07-06-2024",
}