Remote Non-Intrusive Patient Monitoring

被引:0
|
作者
O'Donoghue, John [1 ]
Herbert, John [1 ]
Stack, Paul [1 ]
机构
[1] Univ Coll Cork, Dept Comp Sci, Cork, Ireland
来源
SMART HOMES AND BEYOND | 2006年 / 19卷
关键词
D O I
暂无
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
The Tyndall-DMS-Mote is a wireless sensor device that can monitor patient vital signs non-intrusively within and outside their home. Patient real-time vital sign readings (dynamic data) and archived records (static data) need to be managed, correlated and analysed in a cohesive manner to produce effective results. The Data Management System (DMS) has been developed to intelligently manage this data. Limited computation is available to clients executing on the sensor node. Presented is a Mobile-DMS-Client which executes on a Nokia 9500 Communicator. This client complements the Tyndall-DMS-Mote in its ability to locally process larger amounts of data thus reducing the need to communicate data to a remote server for computation. When external interaction is required (e.g. to a knowledge base or staff PDA) the DMS can supply information via a context aware agent middleware. Agents effectively encapsulate, extract and interpret real world context aware information ensuring physicians get the "correct" data on time every time. Patient vital sign readings are taken by Tyndall-DMS-Motes in a non-invasive non-intrusive manner. Details are given on the Mobile-DMS-Client and Tyndall-DMS-Mote prototypes and their ability to interpret patient blood pressure sensor readings.
引用
收藏
页码:180 / +
页数:3
相关论文
共 50 条
  • [41] Disaggregating Transform Learning for Non-Intrusive Load Monitoring
    Gaur, Megha
    Majumdar, Angshul
    [J]. IEEE ACCESS, 2018, 6 : 46256 - 46265
  • [42] Real time and non-intrusive driver fatigue monitoring
    Zhu, ZW
    Ji, Q
    [J]. ITSC 2004: 7TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, PROCEEDINGS, 2004, : 657 - 662
  • [43] Elimination of Overfitting of Non-intrusive Load Monitoring Model
    Zhou, Yongjun
    Ji, Chao
    Dong, Zhihua
    Yang, Lin
    Zhang, Shu
    [J]. 2021 IEEE IAS INDUSTRIAL AND COMMERCIAL POWER SYSTEM ASIA (IEEE I&CPS ASIA 2021), 2021, : 1567 - 1571
  • [44] Automatic Appliance Classification for Non-Intrusive Load Monitoring
    Chou, Po-An
    Chuang, Chi-Cheng
    Chang, Ray-I
    [J]. 2012 IEEE INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON), 2012,
  • [45] Designing a Novel Dataset for Non-Intrusive Load Monitoring
    Renaux, Douglas P. B.
    Linhares, Robson R.
    Pottker, Fabiana
    Lazzaretti, Andre E.
    Lima, Carlos R. E.
    Coelho Neto, Adil O.
    Campaner, Mateus H.
    [J]. 2018 VIII BRAZILIAN SYMPOSIUM ON COMPUTING SYSTEMS ENGINEERING (SBESC 2018), 2018, : 243 - 249
  • [46] Deep Sparse Coding for Non-Intrusive Load Monitoring
    Singh, Shikha
    Majumdar, Angshul
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (05) : 4669 - 4678
  • [47] Unsupervised Adaptive Non-Intrusive Load Monitoring System
    Chou, Po-An
    Chang, Ray-I
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013), 2013, : 3180 - 3185
  • [48] Non-intrusive and real time driver status monitoring
    [J]. ITSC 2004: 7TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, PROCEEDINGS, 2004, : 952 - 953
  • [49] Overview of non-intrusive load monitoring and identification techniques
    Aladesanmi, E. J.
    Folly, K. A.
    [J]. IFAC PAPERSONLINE, 2015, 48 (30): : 415 - 420
  • [50] Non-intrusive appliance load monitoring with bagging classifiers
    Kramer, Oliver
    Klingenberg, Thole
    Sonnenschein, Michael
    Wilken, Olaf
    [J]. LOGIC JOURNAL OF THE IGPL, 2015, 23 (03) : 359 - 368