Feature selection and activity recognition from wearable sensors

Susanna Pirttikangas*, Kaori Fujinami, Tatsuo Nakajima

*この研究の対応する著者

研究成果: Conference contribution

176 被引用数 (Scopus)

抄録

We describe our data collection and results on activity recognition with wearable, coin-sized sensor devices. The devices were attached to four different parts of the body: right thigh and wrist, left wrist and to a necklace on 13 different testees. In this experiment, data was from 17 daily life examples from male and female subjects. Features were calculated from triaxial accelerometer and heart rate data within different sized time windows. The best features were selected with forward-back ward sequential search algorithm. Interestingly, acceleration mean values from the necklace were selected as important features. Two classifiers (multilayer perceptrons and kNN classifiers) were tested for activity recognition, and the best result (90.61 % aggregate recognition rate for 4-fold cross validation) was achieved with a kNN classifier.

本文言語English
ホスト出版物のタイトルUbiquitous Computing Systems - Third International Symposium, UCS 2006, Proceedings
出版社Springer Verlag
ページ516-527
ページ数12
ISBN(印刷版)3540462872, 9783540462873
DOI
出版ステータスPublished - 2006
イベント3rd International Symposium on Ubiquitous Computing Systems, UCS 2006 - Seoul, Korea, Republic of
継続期間: 2006 10月 112006 10月 13

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4239 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference3rd International Symposium on Ubiquitous Computing Systems, UCS 2006
国/地域Korea, Republic of
CitySeoul
Period06/10/1106/10/13

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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