mdh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A framework for automatic text generation of trends in physiological time series data
Örebro University, Sweden.
Örebro University, Sweden.ORCID iD: 0000-0003-3802-4721
Örebro University, Sweden.
2013 (English)In: Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013, 2013, p. 3876-3881Conference paper, Published paper (Refereed)
Abstract [en]

Health monitoring systems using wearable sensors have rapidly grown in the biomedical community. The main challenges in physiological data monitoring are to analyse large volumes of health measurements and to represent the acquired information. Natural language generation is an effective method to create summaries for both clinicians and patients as it can describe useful information extracted from sensor data in textual format. This paper presents a framework of a natural language generation system that provides a text-based representation of the extracted numeric information from physiological sensor signals. More specifically, a new partial trend detection algorithm is introduced to capture the particular changes and events of health parameters. The extracted information is then represented considering linguistic characterisation of numeric features. Experimental analysis was performed using a wearable sensor and demonstrates a possible output in natural language text.

Place, publisher, year, edition, pages
2013. p. 3876-3881
National Category
Engineering and Technology Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-26806DOI: 10.1109/SMC.2013.661ISI: 000332201904002Scopus ID: 2-s2.0-84890455979ISBN: 9780769551548 (print)OAI: oai:DiVA.org:mdh-26806DiVA, id: diva2:768015
Conference
2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013; Manchester; United Kingdom; 13 October 2013 through 16 October 2013
Available from: 2014-12-02 Created: 2014-12-02 Last updated: 2017-01-25Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Ahmed, Mobyen Uddin

Search in DiVA

By author/editor
Ahmed, Mobyen Uddin
Engineering and TechnologyElectrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 27 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf