Various studies have looked at the efficiency of artificial vessel and tissue networks in the study of photoplethysmography (PPG) in an effort to better understand the origin of various morphological features present in the signal. Whilst there are all reasonable attempts made to replicate geometrical features such as vessel depth, vessel wall thickness and diameter etc., not many studies have attempted to replicate the mechanical properties such as vessel elasticity and tissue compressibility. This study reports two methods for tissue mechanical testing for the analysis of vessel elasticity and tissue compressibility. A two-part polydimethylsiloxane (PDMS) was used as a base material for both tissue and vessel construction, and the properties altered by changing the curing component ratio. Tissue compression properties were investigated using an industrially calibrated materials testing device using the protocol from the ASTM 0575-91 testing method. Vessel elasticity was investigated using a custom method and apparatus to report vessel diameter and length change simultaneously. Tissue compressive properties proved reasonably easy to replicate through catalyst alteration, however the vessel elasticity properties were found to be higher than expected at all reasonable catalyst ratios. The property of hyper-elasticity was observed in the artificial vessels though, leading to the conclusion that alternative material recipes or construction methods may be needed to correctly replicate the expected mechanical characteristics. Clinical Relevance- The latest generation of health monitoring devices, especially those that are wearable and used widely by individuals wishing to monitor their health daily are becoming smarter and more sophisticated in their functionality. The majority of such devices use photoplethysmography (PPG) as their primary monitoring technique. Being able to replicate the PPG in a phantom allows the continued study and development of devices, and to improve their functionality without the continued need for extensive user-testing.