… A triaxial accelerometer-based human activity recognition via eemd-based features and game…
neural networks: A case study using the UP-Fall detection dataset[J]. Computers in Biology …

… the problems with existing human fall detection methods for … high false detection rates, an
infrared image human fall detection … of the human target is found through a neural network, and …

… Fourth, the gait recognition was introduced from support vector machine, auto-encoder and
convolutional neural network, respectively, and the above methods from the two application …

… the convolutional neural network (CNN) was used to automatically extract the features of
human activity da… Evaluation of accelerometer based multi-sensor versus single-sensor activity …

… role and application of convolutional neural networks in the field … Accelerometerbased fall
detection using machine learning:… tional neural network autoencoders for human fall detection[…

… of artificial intelligence methods based on artificial neural network and machine learning
related methods in sports injury prediction, detection of abnormal human behavior, com-petitive …

… 基于卷积神经网络(convolutional neural network, CNN)来识别目标体当前的状态行为(选取4种
状态:即静止,车行,步行和其他),进而为室内定位提供依据不同运动状态实现相应定位切换的方法. …

… shot multibox detector) 方法在公开数据集(UR Fall Detection Dataset)上检测精度可以达到
95.1%.为克服光照 不均等因素,文献[5]提出了融合运动特征的CNN (convolutional neural network)…

… Human fall detection method based on SE-CNN [J]. Comput … Accelerometerbased fall
detection using machine learning: … Deep neural networkbased double-check method for fall …

患者发生跌倒或坠床事件会给自身和社会带来沉重负担. 近年来,“物联网+ 医疗” 深度融合, 迅速
发展. 物联网技术被应用于监测和预警患者跌倒事件. 本文从患者跌倒物联网监测预警系统的技术…