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...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175289 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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