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- W3187110475 abstract "Lying is a common behavior that humans deceive and mislead others by concealing plots, false statements, and distorting facts which is important for intelligence service, bank, and justice department. In this paper, a system based on a DIFCW radar with machine learning is presented to perform polygraph. The radar is utilized to achieve non-contact measurement of heartbeat and respiratory signals. Based on the two signals, several features are extracted. And a model is trained through machine learning to determine whether the subject lie. In the experiment, a database of 11 males and 10 females with 435 lies and 562 truths are established. The accuracy rate of heartbeat and respiratory polygraph detection attach to 63.2% and 61.5%." @default.
- W3187110475 created "2021-08-16" @default.
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- W3187110475 date "2021-05-23" @default.
- W3187110475 modified "2023-09-25" @default.
- W3187110475 title "Lie Detection Based on a DIFCW Radar with Machine Learning" @default.
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- W3187110475 doi "https://doi.org/10.1109/iws52775.2021.9499642" @default.
- W3187110475 hasPublicationYear "2021" @default.
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