Machine learning assisted noncontact neonatal anthropometry using FMCW radar

Machine learning assisted noncontact neonatal anthropometry using FMCW radar

Abstract This study proposes a method for measuring the height and weight of a neonate conveniently, safely, and accurately by applying a convolutional neural network to frequency-modulated continuous-wave (FMCW) radar sensor data. Fifteen neonates, with parental consent, were enrolled in the study....

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Bibliographic Details
Main Authors: Jun Byung Park, Jae Yoon Na, Seung Hyun Kim, Jinjoo Choi, Jihyun Keum, Sung Ho Cho, Hyun-Kyung Park
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Neonates
Non-contact sensor
Machine learning
FMCW
Anthropometry
Online Access:https://doi.org/10.1038/s41598-025-99104-7
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https://doi.org/10.1038/s41598-025-99104-7

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