Signals and Telecommunication Journal Yao-Liang Chung 15 2 2026 https://doi.org/10.6025/stj/2026/15/2/64-87 https://www.dline.info/stj/fulltext/v15n2/stjv15n2_2.pdf Contactless radar sensing has emerged as a transformative modality for non invasive, continuous vital signs monitoring. However, a rigorous multi-domain characterization of raw radar displacement signals under both normal and disordered breathing conditions remains a fundamental requirement for developing reliable clinical tools. This study presents a comprehensive multi domain analysis of radar derived vital signs, focusing on the contactless monitoring of resting respiration and the detection of apneic events. Utilizing the VITALSENSE 120 dataset, which comprises synchronized continuous wave radar recordings (sampled at 333.33 Hz) and clinical grade reference physiological signals, we systematically evaluated the radar displacement signal across multiple analytical domains. Results indicate that resting respiration exhibits stable periodic oscillations with a dominant respiratory frequency concentrated in the 0.1–0.5 Hz band, alongside strong temporal synchronization with reference signals. Conversely, apneic events are distinctly characterized by significant spectral power reduction in the respiratory band, marked envelope reduction indicating diminished thoracic displacement, and pronounced autocorrelation reduction reflecting the loss of respiratory rhythm periodicity. Furthermore, cross-domain analysis reveals a sharp drop in the correlation coefficient between the radar displacement and reference respiratory signals, while residual cardiac induced micromovements remain detectable. This multi-domain evidence base confirms the physiological interpretability of radar observations and quantifies the discriminative signatures necessary for separating spontaneous breathing from apnea, laying a solid foundation for robust, explainable AI/ML pipelines in remote healthcare.