Change search
ReferencesLink to record
Permanent link

Direct link
Confidence-based multiclass AdaBoost for physical activity monitoring
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-1971-4295
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany.
2013 (English)In: ISWC '13: Proceedings of the 2013 International Symposium on Wearable Computers, 2013, 13-20 p.Conference paper (Refereed)
Abstract [en]

Physical activity monitoring has recently become an important topic in wearable computing, motivated by e.g. healthcare applications. However, new benchmark results show that the difficulty of the complex classification problems exceeds the potential of existing classifiers. Therefore, this paper proposes the ConfAdaBoost.M1 algorithm. The proposed algorithm is a variant of the AdaBoost.M1 that incorporates well established ideas for confidence based boosting. The method is compared to the most commonly used boosting methods using benchmark datasets from the UCI machine learning repository and it is also evaluated on an activity recognition and an intensity estimation problem, including a large number of physical activities from the recently released PAMAP2 dataset. The presented results indicate that the proposed ConfAdaBoost.M1 algorithm significantly improves the classification performance on most of the evaluated datasets, especially for larger and more complex classification tasks.

Place, publisher, year, edition, pages
2013. 13-20 p.
National Category
Signal Processing Control Engineering Other Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:liu:diva-97524DOI: 10.1145/2493988.2494325ISBN: 978-1-4503-2127-3OAI: diva2:648293
17th Annual International Symposium on Wearable Computers,Zurich, Switzerland, September 8-12, 2013
Available from: 2013-09-14 Created: 2013-09-14 Last updated: 2015-09-22Bibliographically approved

Open Access in DiVA

fulltext(331 kB)431 downloads
File information
File name FULLTEXT01.pdfFile size 331 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Hendeby, Gustaf
By organisation
Automatic ControlThe Institute of Technology
Signal ProcessingControl EngineeringOther Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 431 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 305 hits
ReferencesLink to record
Permanent link

Direct link