2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)最新文献_第3页

Prediction-based personalized offloading of cellular traffic through WiFi networks 通过WiFi网络进行基于预测的蜂窝流量个性化卸载

2016 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2016-03-14 DOI: 10.1109/PERCOM.2016.7456516

Suyeon Kim, Yohan Chon, Seokjun Lee, H. Cha

引用次数: 7

A probabilistic model for early prediction of abnormal clinical events using vital sign correlations in home-based monitoring 基于家庭监测的生命体征相关性早期预测异常临床事件的概率模型

2016 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2016-03-14 DOI: 10.1109/PERCOM.2016.7456519

A. Forkan, I. Khalil

{"title":"A probabilistic model for early prediction of abnormal clinical events using vital sign correlations in home-based monitoring","authors":"A. Forkan, I. Khalil","doi":"10.1109/PERCOM.2016.7456519","DOIUrl":"https://doi.org/10.1109/PERCOM.2016.7456519","url":null,"abstract":"Chronic diseases are major causes of deaths in Australia and throughout the world. This necessitates the need for a self-care, preventive, predictive and protective assisted living system where a patient can be monitored continuously using wearable and wireless sensors. In real-time home monitoring system, various biological signals of a patient are obtained continuously using a mobile device (smart phone or tablet) and sent to the cloud to discover patient-specific abnormalities. The objective of this work is to develop a probabilistic model that identifies the future clinical abnormalities of a patient using recent and past values of multiple vital signs (e.g. heart rate, blood pressure, respiratory rate). Chronic patients living alone in home die of various diseases for the lack of an efficient automated system having prior prediction ability in the irregularities of vital signs. In this paper, Hidden Markov Model (HMM) is adopted to predict different clinical onsets using the temporal behaviours of six biosignals. The HMM models are trained and evaluated using continuous monitoring data of more than 1000 patients collected from the MIMIC-II database of MIT physiobank archive. The best models are selected using expectation maximisation (EM) algorithm and used in personalized remote monitoring system to forecast the most probable forthcoming clinical states of a continuously monitored patient. The scalable power of cloud computing is utilized for fast learning of various clinical events from large samples. The results obtained from the innovative home-based monitoring application show a new approach of detecting clinical anomalies using multi-parameter trends.","PeriodicalId":275797,"journal":{"name":"2016 IEEE International Conference on Pervasive Computing and Communications (PerCom)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125659028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 33

MT-Diet: Automated smartphone based diet assessment with infrared images MT-Diet:自动基于智能手机的饮食评估与红外图像

2016 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2016-03-14 DOI: 10.1109/PERCOM.2016.7456506

Junghyo Lee, Ayan Banerjee, S. Gupta

引用次数: 17

Riding quality evaluation through mobile crowd sensing 基于移动人群感知的骑行质量评价

2016 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2016-03-14 DOI: 10.1109/PERCOM.2016.7456517

S. Tan, Xiaoliang Wang, G. Maier, Wenzhong Li

引用次数: 7

Group mobility classification and structure recognition using mobile devices 基于移动设备的群体移动性分类和结构识别

2016 IEEE International Conference on Pervasive Computing and Communications (PerCom) Pub Date : 2016-03-14 DOI: 10.1109/PERCOM.2016.7456523

He Du, Zhiwen Yu, Fei Yi, Zhu Wang, Qi Han, Bin Guo

引用次数: 18