论文标题
很少的运动，很大的结果：使用运动放大倍率揭示婴儿的微妙震颤
Little Motion, Big Results: Using Motion Magnification to Reveal Subtle Tremors in Infants
论文作者
论文摘要
检测震颤对于人类和机器都具有挑战性。怀孕期间接触阿片类药物的婴儿经常显示出出生后出生的症状和症状，这很容易通过人眼而错过。临床特征的星座称为新生儿戒律综合征（NAS），包括震颤，癫痫发作，易怒等。当前的护理标准使用Finnegan Neonatal戒律评分系统（FNASS），基于主观评估。使用FNAS进行监控需要高技能的护理人员，这使得持续监控困难。在本文中，我们提出了使用放大运动信号的自动震颤检测系统。我们演示了其在婴儿床边的床边视频上的适用性，展示了NAS的迹象。此外，我们测试了基于深卷网络的运动放大的不同模式，并确定动态模式在临床环境中最有效，并且是常见的定向变化。我们建议使用运动放大倍率来补充现有方案的NAS患者的出院策略和跟进。总体而言，我们的研究提出了在当前实践，培训和资源利用中弥合差距的方法。
Detecting tremors is challenging for both humans and machines. Infants exposed to opioids during pregnancy often show signs and symptoms of withdrawal after birth, which are easy to miss with the human eye. The constellation of clinical features, termed as Neonatal Abstinence Syndrome (NAS), include tremors, seizures, irritability, etc. The current standard of care uses Finnegan Neonatal Abstinence Syndrome Scoring System (FNASS), based on subjective evaluations. Monitoring with FNASS requires highly skilled nursing staff, making continuous monitoring difficult. In this paper we propose an automated tremor detection system using amplified motion signals. We demonstrate its applicability on bedside video of infant exhibiting signs of NAS. Further, we test different modes of deep convolutional network based motion magnification, and identify that dynamic mode works best in the clinical setting, being invariant to common orientational changes. We propose a strategy for discharge and follow up for NAS patients, using motion magnification to supplement the existing protocols. Overall our study suggests methods for bridging the gap in current practices, training and resource utilization.
