Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification.
Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification.
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DOI：
10.3390/s20215986
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发表时间：
2020-10-22
期刊：
影响因子：
--
通讯作者：
Myśliwiec A
中科院分区：
文献类型：
--
作者：
Doroniewicz I;Ledwoń DJ;Affanasowicz A;Kieszczyńska K;Latos D;Matyja M;Mitas AW;Myśliwiec A
在婴儿生命的早期阶段观察神经运动发育可以早期诊断缺陷并开始治疗过程。一般运动评估是一种自发的运动观察方法，它是当代尝试客观化和基于录像分析的计算机辅助诊断的基础。目前的研究试图自动检测扭动运动，这是新生儿在生命的最初几周所表现出的正常一般运动类别之一。5位专家将31段新生儿出生后第2天和第3天的录像分成包含扭动动作（随发生时间）和不良动作的视频，这些视频的特点是与正常情况相比运动质量较低。提出了描述每个肢体运动范围、性质和位置的新颖、客观的基于姿态的特征。在不同的特征提取时间窗和重叠时间下，评估了三种机器学习算法在留一交叉验证中的扭体检测。实验结果表明，该方法可以确定精度达80%的最优参数。根据视频中自动检测到的扭动动作百分比，将婴儿的动作分类为扭动动作或不良动作，ROC曲线下面积为0.83。
Observation of neuromotor development at an early stage of an infant’s life allows for early diagnosis of deficits and the beginning of the therapeutic process. General movement assessment is a method of spontaneous movement observation, which is the foundation for contemporary attempts at objectification and computer-aided diagnosis based on video recordings’ analysis. The present study attempts to automatically detect writhing movements, one of the normal general movement categories presented by newborns in the first weeks of life. A set of 31 recordings of newborns on the second and third day of life was divided by five experts into videos containing writhing movements (with occurrence time) and poor repertoire, characterized by a lower quality of movement in relation to the norm. Novel, objective pose-based features describing the scope, nature, and location of each limb’s movement are proposed. Three machine learning algorithms are evaluated in writhing movements’ detection in leave-one-out cross-validation for different feature extraction time windows and overlapping time. The experimental results make it possible to indicate the optimal parameters for which 80% accuracy was achieved. Based on automatically detected writhing movement percent in the video, infant movements are classified as writhing movements or poor repertoire with an area under the ROC (receiver operating characteristics) curve of 0.83.
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影响因子：
26.1
作者：
Novak, Iona;Morgan, Cathy;Adde, Lars;Blackman, James;Boyd, Roslyn N.;Brunstrom-Hernandez, Janice;Cioni, Giovanni;Damiano, Diane;Darrah, Johanna;Eliasson, Ann-Christin;de Vries, Linda S.;Einspieler, Christa;Fahey, Michael;Fehlings, Darcy;Ferriero, Donna M.;Fetters, Linda;Fiori, Simona;Forssberg, Hans;Gordon, Andrew M.;Greaves, Susan;Guzzetta, Andrea;Hadders-Algra, Mijna;Harbourne, Regina;Kakooza-Mwesige, Angelina;Karlsson, Petra;Krumlinde-Sundholm, Lena;Latal, Beatrice;Loughran-Fowlds, Alison;Maitre, Nathalie;McIntyre, Sarah;Noritz, Garey;Pennington, Lindsay;Romeo, Domenico M.;Shepherd, Roberta;Spittle, Alicia J.;Thornton, Marelle;Valentine, Jane;Walker, Karen;White, Robert;Badawi, Nadia
通讯作者：
Badawi, Nadia
影响因子：
3.3
作者：
Einspieler, Christa;Peharz, Robert;Marschik, Peter B.
通讯作者：
Marschik, Peter B.
DOI：
10.3390/s16122134
发表时间：
2016-12-14
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Chen H;Xue M;Mei Z;Bambang Oetomo S;Chen W
通讯作者：
Chen W
影响因子：
3.8
作者：
Abney DH;Warlaumont AS;Haussman A;Ross JM;Wallot S
通讯作者：
Wallot S
影响因子：
3.6
作者：
Glowinski, Sebastian;Losinski, Karol;Grochulska, Agnieszka
通讯作者：
Grochulska, Agnieszka