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Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-t...

Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-t...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1440830167

Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-the-art algorithms using a benchmark dataset

About this item

Full title

Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-the-art algorithms using a benchmark dataset

Publisher

United States: Public Library of Science

Journal title

PloS one, 2013-10, Vol.8 (10), p.e75196-e75196

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

Insufficient physical activity is the 4th leading risk factor for mortality. Methods for assessing the individual daily life activity (DLA) are of major interest in order to monitor the current health status and to provide feedback about the individual quality of life. The conventional assessment of DLAs with self-reports induces problems like reli...

Alternative Titles

Full title

Hierarchical, multi-sensor based classification of daily life activities: comparison with state-of-the-art algorithms using a benchmark dataset

Authors, Artists and Contributors

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_plos_journals_1440830167

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_1440830167

Other Identifiers

ISSN

1932-6203

E-ISSN

1932-6203

DOI

10.1371/journal.pone.0075196

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