Personal Identification using Gait Data on Slipper-device with Accelerometer

Miyu Fujii, Kaho Kato, Chengshuo Xia, Yuta Sugiura

研究成果: Conference contribution

抄録

In this paper we presented a method of gait identification by slippers with an accelerometer to perform privacy-friendly personal identification. The gait data from accelerometer during walking is adopted from developed slipper devices as the personal unique data used for identification. Gait data is processed by Fast Fourier Transform to extract the frequency features and the Support vector machine (SVM) is used to identify the subject. Through assessing the different segmentation window size and various sensor positions, the results showed that an average accuracy was 95.0% using six sensors, and an average accuracy of 93.3% using three sensors placed at optimal positions.

本文言語English
ホスト出版物のタイトル5th Asian CHI Symposium 2021
編集者Josh B. Tedjasaputra, Briane Paul V. Samson, Masitah Ghazali, Eunice Sari, Eunice Sari, Sayan Sarcar, Dilrukshi Gamage, Yohannes Kurniawan
出版社Association for Computing Machinery, Inc
ページ74-79
ページ数6
ISBN(電子版)9781450382038
DOI
出版ステータスPublished - 2021 5 8
イベント5th Asian CHI Symposium 2021 - Virtual, Online, Japan
継続期間: 2021 5 72021 5 8

出版物シリーズ

名前5th Asian CHI Symposium 2021

Conference

Conference5th Asian CHI Symposium 2021
国/地域Japan
CityVirtual, Online
Period21/5/721/5/8

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信
  • 人間とコンピュータの相互作用
  • 情報システム
  • ソフトウェア

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