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Brain Activity and Healthcare in the Smart Home
KTH, School of Engineering Sciences (SCI).
KTH, School of Engineering Sciences (SCI).
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

A step towards improving living standards for elderly and patients is to incorporate healthcare systems in the home. Aiming to increase the safety and independence of these groups this paper highlights a few possible approaches. Specifically the focus has been on; fall detection using the Electroencephalography (EEG) sensor Emotiv EPOC, a monitoring and drug administration system, a control system for home appliances based on EEG and sleep improvement with EEG in the smart home.

A fall detection study has been performed, determining whether a fall can be differentiated from similar events. The study concludes that EEG sensors might have potential as part of a fall detection system. The remainder of the project is theoretical. It holds potential, however experiments need to be performed for further conclusions.

Place, publisher, year, edition, pages
2014. , 10 p.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-153912OAI: oai:DiVA.org:kth-153912DiVA: diva2:753867
Educational program
Master of Science in Engineering -Engineering Physics
Available from: 2014-10-09 Created: 2014-10-09 Last updated: 2014-10-09Bibliographically approved

Open Access in DiVA

Sofie Andersson & Hannes Carlsson kandidatexam(746 kB)355 downloads
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4635bcef48e850610c4eead8d5e339b702e5494619014d1df32a890e63c08a470b8575099b586c922e3670d4d1f5a28446358676b9a379101e661d6a70e9536b
Type fulltextMimetype application/pdf

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CiteExportLink to record
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Citation style
  • apa
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  • ieee
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More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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