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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Bibliographic Details
Main Author: Kng, Yew Chian
Other Authors: Luo Jun
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175289
Description
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.