Detection of human movement by near field imaging / : development of a novel method and applications

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Sepponen, Raimo, Prof.
dc.contributor.author Rimminen, Henry
dc.date.accessioned 2012-08-29T11:53:42Z
dc.date.available 2012-08-29T11:53:42Z
dc.date.issued 2011
dc.identifier.isbn 978-952-60-3497-3 (PDF)
dc.identifier.isbn 978-952-60-3496-6 (printed)
dc.identifier.issn 1459-1111
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/4945
dc.description.abstract The proportion of senior citizens is increasing, which requires more resources in the care services. The effectiveness of these services is proposed to be increased by remote monitoring of senior citizens living at home or in nursing homes. The monitoring can be performed with various types of sensors, but the solution presented here incorporates most of the functionalities found in related work in one comprehensive system. The system that was developed uses electric field sensing to detect human presence and movement. Falls and the vital functions of a fallen person can also be extracted from the signals. The sensor arrangement consists of a matrix of thin planar electrodes under the floor surface, which makes the system completely undetectable and discreet. It is not disturbed by shading or darkness and does not require a lot of computing power. Computer vision does not enjoy these advantages. Furthermore, no devices need to be worn and no batteries need to be charged, as with systems based on transponders worn by the subject. If identification is required, the system developed in this work does not rule out the use of transponders. The impedances of the electrodes are measured using a tuned transformer and a phase-sensitive detector. A signal-to-noise ratio of 37 dB has been achieved with this structure. The mean positioning error when observing people who are walking is 21 cm. Multiple people can be discriminated with a 90% certainty if the distance between them is 78 cm. The sensitivity and specificity in fall detection have been found to be 91% and 91%, respectively. The cardiac activity and respiration are clearly visible when a person lies prone or supine on the floor. A capacitive radio frequency identification (RFID) tag in a shoe was developed for person identification. The system developed here has been installed in a large nursing home. The nurses have indicated their satisfaction in a comprehensive questionnaire, which was conducted by a representative of the nurses. Positive feedback has also been obtained from a senior person living alone and from his family members. en
dc.format.extent Verkkokirja (4840 KB, 54 s.)
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Aalto-yliopiston teknillinen korkeakoulu en
dc.relation.ispartofseries Helsinki University of Technology, Applied Electronics Laboratory. B, Research reports, 20 en
dc.relation.haspart [Publication 1]: Henry Rimminen, Matti Linnavuo, and Raimo Sepponen. 2008. Human tracking using near field imaging. In: Proceedings of the Second International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health 2008). Tampere, Finland. 30 January - 1 February 2008. Pages 148-151. © 2008 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (ICST). By permission. en
dc.relation.haspart [Publication 2]: Henry Rimminen and Raimo Sepponen. 2009. Biosignals with a floor sensor - Near field imaging floor sensor measures impedance changes in the torso. In: Teodiano Freire Bastos Filho and Hugo Gamboa (editors). Proceedings of the Second International Conference on Biomedical Electronics and Devices (BIODEVICES 2009). Porto, Portugal. 14-17 January 2009. Setubal, Portugal. INSTICC Press. Pages 125-130. ISBN 978-989-8111-64-7. © 2009 Institute for Systems and Technologies of Information, Control and Communication (INSTICC). By permission. en
dc.relation.haspart [Publication 3]: H. Rimminen, J. Lindström, and R. Sepponen. 2009. Positioning accuracy and multi-target separation with a human tracking system using near field imaging. International Journal on Smart Sensing and Intelligent Systems, volume 2, number 1, pages 156-175. © 2009 by authors. en
dc.relation.haspart [Publication 4]: Henry Rimminen, Juha Lindström, Matti Linnavuo, and Raimo Sepponen. 2010. Detection of falls among the elderly by a floor sensor using the electric near field. IEEE Transactions on Information Technology in Biomedicine, volume 14, number 6, pages 1475-1476. © 2010 Institute of Electrical and Electronics Engineers (IEEE). By permission. en
dc.relation.haspart [Publication 5]: Henry Rimminen, Matti Linnavuo, and Raimo Sepponen. 2010. Human identification and localization using active capacitive RFID tags and an electric field floor sensor. International Review of Electrical Engineering, volume 5, number 3, pages 1061-1068. © 2010 Praise Worthy Prize. By permission. en
dc.subject.other Electrical engineering
dc.title Detection of human movement by near field imaging / : development of a novel method and applications en
dc.type G5 Artikkeliväitöskirja fi
dc.contributor.school Aalto-yliopiston teknillinen korkeakoulu fi
dc.contributor.department Elektroniikan laitos fi
dc.contributor.department Department of Electronics en
dc.subject.keyword electric field sensing en
dc.subject.keyword near field imaging en
dc.subject.keyword indoor tracking en
dc.subject.keyword fall detection en
dc.identifier.urn URN:ISBN:978-952-60-3497-3
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en
dc.contributor.supervisor Sepponen, Raimo, Prof.


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