Automatic classification,of resuscitation activities on birth-asphyxiated newborns using acceleration and ECG signals

Vu Huyen; Engan Kjersti; Eftestol Trygve; Katsaggelos Aggelos; Jatosh Samwel; Kusulla Simeon; Mduma Estomih; Kidanto Hussein; Ersdal Hege

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Automatic classification,of resuscitation activities on birth-asphyxiated newborns using acceleration and ECG signals

机译：使用加速和ECG信号自动分类窒息新生儿的复苏活动

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Objectives: Newborn deaths are reported to be caused mainly by birth asphyxia. Information learned from ventilation and other treatment could help increase survival rate of newborns in need of resuscitation. Characteristics of manual bag-mask ventilation have been studied in our previous works. However, other resuscitation activities could have important impacts as well. This paper illustrates the classification of several predefined resuscitation activities using information from acceleration and ECG signal.

机译：目的：据报道新生儿死亡主要是由出生窒息引起的。从通气和其他治疗中学到的信息可以帮助增加需要复苏的新生儿的存活率。我们以前的工作中已经研究了手动袋式口罩通风的特性。但是，其他复苏活动也可能产生重要影响。本文使用来自加速度和ECG信号的信息说明了几种预定义的复苏活动的分类。

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来源
《Biomedical signal processing and control》 |2017年第7期|20-26|共7页
作者
Vu Huyen; Engan Kjersti; Eftestol Trygve; Katsaggelos Aggelos; Jatosh Samwel; Kusulla Simeon; Mduma Estomih; Kidanto Hussein; Ersdal Hege;
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作者单位

Univ Stavanger, Dept Elect Engn & Comp Sci, Stavanger, Norway;

Univ Stavanger, Dept Elect Engn & Comp Sci, Stavanger, Norway;

Univ Stavanger, Dept Elect Engn & Comp Sci, Stavanger, Norway;

Northwestern Univ, Dept Elect Engn & Comp Sci, Evanston, IL 60208 USA;

Haydom Lutheran Hosp, Res Inst, Haydom, Manyara, Tanzania;

Haydom Lutheran Hosp, Res Inst, Haydom, Manyara, Tanzania;

Haydom Lutheran Hosp, Res Inst, Haydom, Manyara, Tanzania;

Muhimbili Natl Hosp MUHAS, Dept Obstet & Gynaecol, Dar Es Salaam, Tanzania;

Stavanger Univ Hosp, Dept Anesthesiol & Intens Care, Stavanger, Norway|Univ Stavanger, Dept Hlth Sci, Stavanger, Norway;

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正文语种 eng
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关键词
Newborns; Birth asphyxia; Acceleration signal; ECG signal; Short time energy; Wavelet packet decomposition; Linear discriminant analysis; Decision tree;

机译：新生儿;窒息;加速度信号;心电信号;短时能量;小波包分解;线性判别分析;决策树;

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机译：使用HRV和ECG衍生呼吸信号提取的新功能自动分类呼吸暂停和正常对象
2. Extracting Features from ECG and Respiratory Signals for Automatic Supervised Classification of Heartbeat Using Neural Networks [J] . Benali Medjahed Oussama, Bachir M`Hamed Saadi, Hadj Slimane Zine-Eddine Asian Journal of Information Technology . 2015,第2期

机译：使用神经网络从心电图和呼吸信号中提取特征以进行心跳的自动监督分类
3. Automatic classification of slow-wave sleep and REM-sleep stages using somnographic ECG signal: some preliminary results for obese and no-obese patients [J] . S. Khemiri, K. Aloui, M. S. Naceur International Journal of Signal and Imaging Systems Engineering . 2015,第1a2期

机译：使用超声ECG信号自动分类慢波睡眠和REM睡眠阶段：肥胖和非肥胖患者的一些初步结果
4. Detection of Activities During Newborn Resuscitation Based on Short-Time Energy of Acceleration Signal [C] . Huyen Vu, Trygve Eftestol, Kjersti Engan, International conference on image and signal processing . 2016

机译：基于加速信号短时能量的新生儿复苏过程中活动的检测
5. Compression of ECG signals with feature extraction, classification, and browsability. [D] . Huang, Bin. 2004

机译：具有特征提取，分类和可浏览性的ECG信号压缩。
6. Development and Validation of Open-Source Activity Intensity Count and Activity Intensity Classification Algorithms from Raw Acceleration Signals of Wearable Sensors [O] . Isabelle Poitras, Jade Clouâtre, Laurent J. Bouyer, 2020

机译：从可穿戴传感器的原始加速信号开发和验证开源活动强度计数和活动强度分类算法
7. Acceleration classification of earthquake signals and linear signals of human activity using smartphone accelerometer based on support vector machine algorithm [O] . Hapsoro Agung Nugroho, Haryas Subyantara Wicaksana 2019

机译：基于支持向量机算法的智能手机加速度计加速分类抗震信号和人类活动线性信号
8. Classification of Multichannel ECG Signals Using a Cross-Distance Analysis. [R] . Shahram, M., Nayebi, K. 2001

机译：使用跨距离分析对多通道ECG信号进行分类。

Automatic classification,of resuscitation activities on birth-asphyxiated newborns using acceleration and ECG signals

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