Neuromuscular diseases often result in elevated passive joint impedance (PJI), impacting the daily lives of affected individuals. To be able to apply assistive devices that compensate for PJI, it is essential to identify the PJI correctly. This study aims to identify and model the PJI of the elbow joint, to improve the control of force-based controlled active-assistance exoskeleton devices by distinguishing the voluntary from the passive forces. We used an elbow device to measure the PJI in twelve healthy males with the shoulder abducted at a 90˚ angle. The study investigates both static and dynamic conditions, encompassing various contraction velocities (≤ 0.20 rad/s) and shoulder flexion positions (0˚ and ±45˚). The analysis estimates the hysteresis, equilibrium position, and elastic property. Subsequently, based on the average elbow PJI, we developed a regression model, with the statistical analysis revealing no significant differences between the conditions, except for the observed hysteresis under varying velocities. Based on the tested conditions, the findings indicate that a single low-velocity dynamic measurement can serve as the basis for deriving a general elbow PJI regression model.