InfaSafe: A Comprehensive, Non-invasive Infant Monitoring System

被引:0
作者
Klicker, Lukas [1 ]
Maliwat, Alex [1 ]
Findura, Joanna [1 ]
Yu, Xinrui [1 ]
Gromov, Mikhail [1 ]
Saniie, Jafar [1 ]
机构
[1] Illinois Inst Technol, Dept Elect & Comp Engn, Embedded Comp & Signal Proc ECASP Res Lab, Chicago, IL 60616 USA
来源
2024 IEEE INTERNATIONAL CONFERENCE ON ELECTRO INFORMATION TECHNOLOGY, EIT 2024 | 2024年
关键词
infant monitoring; SIDS; feature extraction; deep learning;
D O I
10.1109/eIT60633.2024.10609853
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
InfaSafe emerges as a novel approach to infant health monitoring, uniquely positioned at the convergence of advanced artificial intelligence and edge computing. This system is designed not as a definitive solution but as an advanced platform for comprehensive data archiving, offering valuable insights into the complex and elusive nature of Sudden Unexpected Infant Death (SUID). InfaSafe utilizes AI algorithms for real-time pose estimation, breathing surveillance, and cry analysis, all within an edge computing framework that facilitates prompt and efficient data handling. This paper explores the development and capabilities of InfaSafe, underscoring its role in providing crucial, real-time insights and alerts for caregivers and its potential to contribute significantly to our understanding of neonatal health and SUID. The focus is on leveraging technological advancements to gather comprehensive data, which can be instrumental in shaping future research and interventions in neonatal care.
引用
收藏
页码:291 / 296
页数:6
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