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

Juho Merilahti; Miikka Ermes

doi:10.1109/IEMBS.2011.6091944

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

Juho Merilahti, Miikka Ermes

VTT Technical Research Centre of Finland

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-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 language	English
Title of host publication	Proceedings
Subtitle of host publication	Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	7885-7887
ISBN (Electronic)	978-1-4244-4122-8
ISBN (Print)	978-1-4244-4121-1
DOIs	https://doi.org/10.1109/IEMBS.2011.6091944
Publication status	Published - 2011
MoE publication type	A4 Article in a conference publication
Event	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society: EMBC 2011 - Boston, United States Duration: 30 Aug 2011 → 3 Sept 2011

Conference

Conference	33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/Territory	United States
City	Boston
Period	30/08/11 → 3/09/11

Keywords

Accelerometer
context recognition
older people

Access to Document

10.1109/IEMBS.2011.6091944

Cite this

Merilahti, J., & Ermes, M. (2011). 3D accelerometer features' differences between young and older people, and between lower back and neck band sensor placements. In Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 (pp. 7885-7887). IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.1109/IEMBS.2011.6091944

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

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",

keywords = "Accelerometer, context recognition, older people",

author = "Juho Merilahti and Miikka Ermes",

note = "Project code: 35479; 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society : EMBC 2011 ; Conference date: 30-08-2011 Through 03-09-2011",

year = "2011",

doi = "10.1109/IEMBS.2011.6091944",

language = "English",

isbn = "978-1-4244-4121-1",

pages = "7885--7887",

booktitle = "Proceedings",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

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}

Merilahti, J & Ermes, M 2011, 3D accelerometer features' differences between young and older people, and between lower back and neck band sensor placements. in Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. IEEE Institute of Electrical and Electronic Engineers, pp. 7885-7887, 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, Massachusetts, United States, 30/08/11. https://doi.org/10.1109/IEMBS.2011.6091944

3D accelerometer features' differences between young and older people, and between lower back and neck band sensor placements. / Merilahti, Juho; Ermes, Miikka.

Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. IEEE Institute of Electrical and Electronic Engineers, 2011. p. 7885-7887.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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T1 - 3D accelerometer features' differences between young and older people, and between lower back and neck band sensor placements

AU - Merilahti, Juho

AU - Ermes, Miikka

N1 - Project code: 35479

PY - 2011

Y1 - 2011

N2 - 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

AB - 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

KW - Accelerometer

KW - context recognition

KW - older people

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DO - 10.1109/IEMBS.2011.6091944

M3 - Conference article in proceedings

SN - 978-1-4244-4121-1

SP - 7885

EP - 7887

BT - Proceedings

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 30 August 2011 through 3 September 2011

ER -

Merilahti J, Ermes M. 3D accelerometer features' differences between young and older people, and between lower back and neck band sensor placements. In Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011. IEEE Institute of Electrical and Electronic Engineers. 2011. p. 7885-7887 doi: 10.1109/IEMBS.2011.6091944

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

Abstract

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Keywords

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