Recognizing human activities from multi-modal sensors

机译：通过多模式传感器识别人类活动

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This paper describes a method of detecting and monitoring human activities which are extremely useful for understanding human behaviors and recognizing human interactions in a social network. By taking advantage of current wireless sensor network technologies, physical activities can be recognized through classifying multi-modal sensors data. The result shows that high recognition accuracy on a dataset of 6 daily activities of one carrier can be achieved by using suitable classifiers.

机译：本文介绍了一种检测和监视人类活动的方法，该方法对于理解人类行为和识别社交网络中的人类互动非常有用。通过利用当前的无线传感器网络技术，可以通过对多模式传感器数据进行分类来识别体育活动。结果表明，通过使用合适的分类器，可以在一个携带者的6个日常活动的数据集上实现较高的识别精度。

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来源
《Intelligence and Security Informatics, 2009. ISI '09》|2009年|220-222|共3页
会议地点 Dallas TX(US);Dallas TX(US)
作者
Shu Chen; Yan Huang;
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作者单位

Dept. of Comput. Sci. Eng., Univ. of North Texas, Denton, TX;

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关键词
behavioural sciences computing; social networking (online); wireless sensor networks; human activities detection; human activities monitoring; human behaviors; human interactions; multi-modal sensors; social network; wireless sensor network;

机译：行为科学计算；社交网络（在线）；无线传感器网络；人类活动检测；人类活动监控；人类行为；人类互动；多模式传感器；社交网络；无线传感器网络;

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1. Autonomous Human Activity Classification From Wearable Multi-Modal Sensors [J] . Lu Yantao, Velipasalar Senem IEEE sensors journal . 2019,第23期

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2. Recognizing multi-modal sensor signals using evolutionary learning of dynamic Bayesian networks [J] . Young-Seol Lee, Sung-Bae Cho Pattern Analysis and Applications . 2014,第4期

机译：使用动态贝叶斯网络的进化学习识别多模式传感器信号
3. Classical and deep learning methods for recognizing human activities and modes of transportation with smartphone sensors ? [J] . Gjoreski Martin, Janko Vito, Slapnicar Gasper, Information Fusion . 2020,第1期

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4. Recognizing Human Activities from Multi-Modal Sensors [C] . Shu Chen, Yan Huang IEEE International Conference on Intelligence and Security Informatics . 2009

机译：识别来自多模态传感器的人类活动
5. Automatic analysis of facial activity for multi-modal human-machine applications [D] . Reale, Michael James 2014

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6. Protocol for PD SENSORS: Parkinson’s Disease Symptom Evaluation in a Naturalistic Setting producing Outcome measuRes using SPHERE technology. An observational feasibility study of multi-modal multi-sensor technology to measure symptoms and activities of daily living in Parkinson’s disease [O] . Catherine Morgan, Ian Craddock, Emma L Tonkin, 2020

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7. Recognizing Human Activities from Multi-Modal Sensors [O] . Shu Chen Yan Huang 2013

机译：认识多模态传感器的人类活动

Recognizing human activities from multi-modal sensors

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