| タイトル |
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en
Privacy-Preserved Behavior Analysis and Fall Detection by an Infrared Ceiling Sensor Network
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| 作成者 |
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| アクセス権 |
open access |
| 権利情報 |
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| 主題 |
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Other
en
behavior analysis
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Other
en
fall detection
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Other
en
privacy-preserved
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Other
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ceiling sensor network
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Other
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infrared sensors
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NDC
548
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| 内容注記 |
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Abstract
en
An infrared ceiling sensor network system is reported in this study to realize behavior analysis and fall detection of a single person in the home environment. The sensors output multiple binary sequences from which we know the existence/non-existence of persons under the sensors. The short duration averages of the binary responses are shown to be able to be regarded as pixel values of a top-view camera, but more advantageous in the sense of preserving privacy. Using the "pixel values" as features, support vector machine classifiers succeeded in recognizing eight activities (walking, reading, etc.) performed by five subjects at an average recognition rate of 80.65%. In addition, we proposed a martingale framework for detecting falls in this system. The experimental results showed that we attained the best performance of 95.14% (F1 value), the FAR of 7.5% and the FRR of 2.0%. This accuracy is not sufficient in general but surprisingly high with such low-level information. In summary, it is shown that this system has the potential to be used in the home environment to provide personalized services and to detect abnormalities of elders who live alone.
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| 出版者 |
en
MDPI
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| 日付 |
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| 言語 |
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| 資源タイプ |
journal article |
| 出版タイプ |
VoR |
| 資源識別子 |
HDL
http://hdl.handle.net/2115/51701
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| 関連 |
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isIdenticalTo
DOI
https://doi.org/10.3390/s121216920
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| 収録誌情報 |
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en
Sensors
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巻12
号12
開始ページ16920
終了ページ16936
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| ファイル |
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| コンテンツ更新日時 |
2023-07-26 |
