Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/108387
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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Shinmoto Torres, R. | - |
dc.contributor.author | Ranasinghe, D. | - |
dc.contributor.author | Shi, Q. | - |
dc.contributor.editor | Stojmenovic, I. | - |
dc.contributor.editor | Cheng, Z. | - |
dc.contributor.editor | Guo, S. | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2014 / Stojmenovic, I., Cheng, Z., Guo, S. (ed./s), vol.131, pp.384-395 | - |
dc.identifier.isbn | 9783319115689 | - |
dc.identifier.issn | 1867-8211 | - |
dc.identifier.issn | 1867-822X | - |
dc.identifier.uri | http://hdl.handle.net/2440/108387 | - |
dc.description | Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 131) | - |
dc.description.abstract | The development of human activity monitoring has allowed the creation of multiple applications, among them is the recognition of high falls risk activities of older people for the mitigation of falls occurrences. In this study, we apply a graphical model based classification technique (conditional random field) to evaluate various sliding window based techniques for the real time prediction of activities in older subjects wearing a passive (batteryless) sensor enabled RFID tag. The system achieved maximum overall real time activity prediction accuracy of 95% using a time weighted windowing technique to aggregate contextual information to input sensor data. | - |
dc.description.statementofresponsibility | Roberto Luis Shinmoto Torres, Damith C. Ranasinghe, and Qinfeng Shi | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER INTERNATIONAL PUBLISHING AG | - |
dc.relation.ispartofseries | Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering | - |
dc.rights | © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014 | - |
dc.source.uri | http://link.springer.com/chapter/10.1007/978-3-319-11569-6_30 | - |
dc.subject | Conditional random fields; RFID; Feature extraction | - |
dc.title | Evaluation of wearable sensor tag data segmentation approaches for real time activity classification in elderly | - |
dc.type | Conference paper | - |
dc.contributor.conference | 10th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (MOBIQUITOUS) (2 Dec 2013 - 4 Dec 2013 : Tokyo, Japan) | - |
dc.identifier.doi | 10.1007/978-3-319-11569-6_30 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Ranasinghe, D. [0000-0002-2008-9255] | - |
dc.identifier.orcid | Shi, Q. [0000-0002-9126-2107] | - |
Appears in Collections: | Aurora harvest 8 Mathematical Sciences publications |
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RA_hdl_108387.pdf Restricted Access | Restricted Access | 262.57 kB | Adobe PDF | View/Open |
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