3D accelerometer features' differences between young and older people, and between lower back and neck band sensor placements

Juho Merilahti, Miikka Ermes

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)

Abstract

In earlier studies, we have developed activity recognition algorithm which are based on features calculated from 3D accelerometer sensor data placed on a hip, close to the centre of mass. In the development subjects have been young adults. Now we study are the input features of the algorithm generalized for older adults and for different sensor placement; in this case worn as a necklace. From the 3D accelerometer resultant magnitude the following features were calculated for each second: spectral entropy, peak frequency, power and range. The frequency domain features behaved in a relatively stable manner in the set-ups but the time domain features differed significantly from statistical and algorithm perspective between the set-ups. By developing time domain features to be more inter-individual independent would be beneficial for activity recognition algorithms
Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages7885-7887
ISBN (Electronic)978-1-4244-4122-8
ISBN (Print)978-1-4244-4121-1
DOIs
Publication statusPublished - 2011
MoE publication typeA4 Article in a conference publication
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society: EMBC 2011 - Boston, United States
Duration: 30 Aug 20113 Sept 2011

Conference

Conference33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/TerritoryUnited States
CityBoston
Period30/08/113/09/11

Keywords

  • Accelerometer
  • context recognition
  • older people

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