Rapid detection and measurement of blood flow is essential in clinical care; it is one of the fundamental vital signs used to detect physiological parameters such as heart rate and blood flow and is one of the most utilized measures in assessing the health of an individual. Photoplethysmography (PPG) is a method quickly growing in popularity for point-of-care diagnostics, using light to detect blood volume shifts. However, PPG has poor penetration depth and cannot detect deep arteries, and it is susceptible to movement artifacts. The central objective of this thesis is to develop an electromagnetic sensor for the detection of blood flow for capturing hemodynamic information in the deep arteries. To accomplish this an RF resonant skin patch sensor was designed as a planar spiral, and a biological model was constructed to detect biofluid shifts due to arterial pulsatile changes in a controlled environment. This sensing technology was then further refined to optimize for body placement and penetration depth and was validated for reproducibility and accuracy in a human multisite arterial study. The sensor response was investigated via simultaneous acquisition of PPG, ECG and sensor signals for each landmark. Significant shifts in the resonant frequency were detected when the skin patch sensor was placed over important arterial landmarks, and the peak-peak intervals (PPI) were highly correlated (R2 > 0.97) with corresponding changes in PPG and ECG signal.