Radio-frequency (RF) sensing for deep awareness of human physical status - part II

The application of radar signal processing techniques, specifically with ultra-wideband (UWB) radar is investigated in this study. The intention is to non-invasively detect and classify human emotions using UWB radar. Features related to breathing and heart rate are extracted from the signal. Mac...

全面介紹

Saved in:
書目詳細資料
主要作者: Kng, Yew Chian
其他作者: Luo Jun
格式: Final Year Project
語言:English
出版: Nanyang Technological University 2024
主題:
在線閱讀:https://hdl.handle.net/10356/175289
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
實物特徵
總結:The application of radar signal processing techniques, specifically with ultra-wideband (UWB) radar is investigated in this study. The intention is to non-invasively detect and classify human emotions using UWB radar. Features related to breathing and heart rate are extracted from the signal. Machine learning techniques are then applied to classify between emotions defined by the arousal-valence theory. The dataset was created by exposing subjects to different videos meant to incite different responses while being monitored by a UWB radar.