Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction

Jhun Ying Yang; Yen Ping Chen; Gwo Yun Lee; Shun Nan Liou; Jeen Shing Wang

doi:10.1007/978-3-540-74873-1_47

Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction

Jhun Ying Yang, Yen Ping Chen, Gwo Yun Lee, Shun Nan Liou, Jeen Shing Wang

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

53 Citations (Scopus)

Abstract

This paper presents a neuro-fuzzy classifer for activity recognition using one triaxial accelerometer and feature reduction approaches. We use a triaxial accelerometer to acquire subjects' acceleration data and train the neurofuzzy classifier to distinguish different activities/movements. To construct the neuro-fuzzy classifier, a modified mapping-constrained agglomerative clustering algorithm is devised to reveal a compact data configuration from the acceleration data. In addition, we investigate two different feature reduction methods, a feature subset selection and linear discriminate analysis. These two methods are used to determine the significant feature subsets and retain the characteristics of the data distribution in the feature space for training the neuro-fuzzy classifier. Experimental results have successfully validated the effectiveness of the proposed classifier.

Original language	English
Title of host publication	Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings
Editors	Lizhuang Ma, Matthias Rauterberg, Ryohei Nakatsu
Publisher	Springer Verlag
Pages	395-400
Number of pages	6
ISBN (Print)	3540748725, 9783540748724
DOIs	https://doi.org/10.1007/978-3-540-74873-1_47
Publication status	Published - 2007
Event	6th International Conference of Entertainment Computing, ICEC 2007 - Shanghai, China Duration: 2007 Sep 15 → 2007 Sep 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4740 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	6th International Conference of Entertainment Computing, ICEC 2007
Country	China
City	Shanghai
Period	07-09-15 → 07-09-17

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-74873-1_47

Fingerprint Dive into the research topics of 'Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction'. Together they form a unique fingerprint.

Cite this

Yang, J. Y., Chen, Y. P., Lee, G. Y., Liou, S. N., & Wang, J. S. (2007). Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction. In L. Ma, M. Rauterberg, & R. Nakatsu (Eds.), Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings (pp. 395-400). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4740 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-540-74873-1_47

Yang, Jhun Ying ; Chen, Yen Ping ; Lee, Gwo Yun ; Liou, Shun Nan ; Wang, Jeen Shing. / Activity recognition using one triaxial accelerometer : A neuro-fuzzy classifier with feature reduction. Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings. editor / Lizhuang Ma ; Matthias Rauterberg ; Ryohei Nakatsu. Springer Verlag, 2007. pp. 395-400 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{70d2de08107e409c81438f9e743ef23f,

title = "Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction",

abstract = "This paper presents a neuro-fuzzy classifer for activity recognition using one triaxial accelerometer and feature reduction approaches. We use a triaxial accelerometer to acquire subjects' acceleration data and train the neurofuzzy classifier to distinguish different activities/movements. To construct the neuro-fuzzy classifier, a modified mapping-constrained agglomerative clustering algorithm is devised to reveal a compact data configuration from the acceleration data. In addition, we investigate two different feature reduction methods, a feature subset selection and linear discriminate analysis. These two methods are used to determine the significant feature subsets and retain the characteristics of the data distribution in the feature space for training the neuro-fuzzy classifier. Experimental results have successfully validated the effectiveness of the proposed classifier.",

author = "Yang, {Jhun Ying} and Chen, {Yen Ping} and Lee, {Gwo Yun} and Liou, {Shun Nan} and Wang, {Jeen Shing}",

year = "2007",

doi = "10.1007/978-3-540-74873-1_47",

language = "English",

isbn = "3540748725",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "395--400",

editor = "Lizhuang Ma and Matthias Rauterberg and Ryohei Nakatsu",

booktitle = "Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings",

address = "Germany",

}

Yang, JY, Chen, YP, Lee, GY, Liou, SN & Wang, JS 2007, Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction. in L Ma, M Rauterberg & R Nakatsu (eds), Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4740 LNCS, Springer Verlag, pp. 395-400, 6th International Conference of Entertainment Computing, ICEC 2007, Shanghai, China, 07-09-15. https://doi.org/10.1007/978-3-540-74873-1_47

Activity recognition using one triaxial accelerometer : A neuro-fuzzy classifier with feature reduction. / Yang, Jhun Ying; Chen, Yen Ping; Lee, Gwo Yun; Liou, Shun Nan; Wang, Jeen Shing.

Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings. ed. / Lizhuang Ma; Matthias Rauterberg; Ryohei Nakatsu. Springer Verlag, 2007. p. 395-400 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4740 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Activity recognition using one triaxial accelerometer

T2 - 6th International Conference of Entertainment Computing, ICEC 2007

AU - Yang, Jhun Ying

AU - Chen, Yen Ping

AU - Lee, Gwo Yun

AU - Liou, Shun Nan

AU - Wang, Jeen Shing

PY - 2007

Y1 - 2007

N2 - This paper presents a neuro-fuzzy classifer for activity recognition using one triaxial accelerometer and feature reduction approaches. We use a triaxial accelerometer to acquire subjects' acceleration data and train the neurofuzzy classifier to distinguish different activities/movements. To construct the neuro-fuzzy classifier, a modified mapping-constrained agglomerative clustering algorithm is devised to reveal a compact data configuration from the acceleration data. In addition, we investigate two different feature reduction methods, a feature subset selection and linear discriminate analysis. These two methods are used to determine the significant feature subsets and retain the characteristics of the data distribution in the feature space for training the neuro-fuzzy classifier. Experimental results have successfully validated the effectiveness of the proposed classifier.

AB - This paper presents a neuro-fuzzy classifer for activity recognition using one triaxial accelerometer and feature reduction approaches. We use a triaxial accelerometer to acquire subjects' acceleration data and train the neurofuzzy classifier to distinguish different activities/movements. To construct the neuro-fuzzy classifier, a modified mapping-constrained agglomerative clustering algorithm is devised to reveal a compact data configuration from the acceleration data. In addition, we investigate two different feature reduction methods, a feature subset selection and linear discriminate analysis. These two methods are used to determine the significant feature subsets and retain the characteristics of the data distribution in the feature space for training the neuro-fuzzy classifier. Experimental results have successfully validated the effectiveness of the proposed classifier.

UR - http://www.scopus.com/inward/record.url?scp=38149112664&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38149112664&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-74873-1_47

DO - 10.1007/978-3-540-74873-1_47

M3 - Conference contribution

AN - SCOPUS:38149112664

SN - 3540748725

SN - 9783540748724

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 395

EP - 400

BT - Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings

A2 - Ma, Lizhuang

A2 - Rauterberg, Matthias

A2 - Nakatsu, Ryohei

PB - Springer Verlag

Y2 - 15 September 2007 through 17 September 2007

ER -

Yang JY, Chen YP, Lee GY, Liou SN, Wang JS. Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction. In Ma L, Rauterberg M, Nakatsu R, editors, Entertainment Computing - ICEC 2007 - 6th International Conference, Proceedings. Springer Verlag. 2007. p. 395-400. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-74873-1_47