胎动
可穿戴计算机
计算机科学
持续监测
计算机视觉
胎儿监护
人工智能
运动(音乐)
惯性测量装置
远程病人监护
压力传感器
生物医学工程
胎儿
实时计算
连续血糖监测
模拟
呼吸监测
可穿戴技术
作者
Lim Wei Yap,Arie Levin,Yiwen Jiang,Duong Nhu,Shu Gong,Ritesh Rikain Warty,David Vera Anaya,Qinhao Li,Yan Lu,Rui Gao,Xin Zhang,Talha Ilyas,Vinayak Smith,Allison Thomas,Aswandi Wibrianto,Yuxin Zhang,Jane Limas,Sharon A. McCracken,Jonathan M Morris,Ben W Mol
出处
期刊:Science Advances
[American Association for the Advancement of Science]
日期:2025-11-26
卷期号:11 (48)
标识
DOI:10.1126/sciadv.ady2661
摘要
Continuous fetal movement monitoring in late pregnancy may improve fetal wellbeing and pregnancy outcomes. While fetal movements can be visualized with ultrasound, it is intermittent and limited to clinical settings. Inertial measurement units may enable at-home fetal monitoring but usually require a large-footprint, multisensor design. Here, we report smart, compact wearable pressure-strain combo sensors continuously monitoring fetal movements through maternal abdominal skin motions. In the 2D and 3D artificial abdomen systems, our octagonal-shaped gold nanowire–based strain sensor served as an isotropic sensor, enabling omnidirectional simulated “kicking load” detection within an area of ~77 (2D) and ~217 cm 2 (3D), while an interdigitated electrode–based pressure sensor showed highly sensitive localized load detection. Building upon these findings, we designed compact pressure- and strain-sensing integrated Band-Aids and tested on 59 pregnant women. We developed machine learning models to distinguish fetal from nonfetal movements with >90% accuracy in ultrasound-based validation studies. This AI-powered, Band-Aid–like sensing system offers potential as a compact, comfortable, and accurate continuous out-of-hospital fetal movement monitoring technology.
科研通智能强力驱动
Strongly Powered by AbleSci AI