Many medical devices have been shifting to personal platforms such as smartphones due to its ubiquitous availability, variety of included sensors, robust communication, and user-friendliness. By utilizing smartphones as a medical sensing device should improve the early detection of abnormalities and the long-term monitoring of health conditions. Tissue abnormalities will be detected by touch sensation due to mechanical property changes within the tissue. However, touch sensation is unquantifiable and subjective. We integrate the smartphone with a tactile sensor to build a portable and personalized tissue assessment device based on changes in mechanical properties. The Smartphone Tactile Imaging Probe (STIP) is developed to quantify the mechanical properties of the tissue. The proposed system has a dual-sensing mode: compression-based sensing (STIP-C) and indentation-based sensing (STIP-I). STIP–C is designed to detect and measure the size and hardness of the inclusion. It assesses mechanical property changes caused by the tumor inside the tissue. STIP–I is designed to measure the pitting parameters and viscoelastic properties of the tissue. This system will assess the viscoelasticity changes caused by fluid retention within the tissue. STIP estimates mechanical and viscoelastic behavior changes in the tissue and provides the risk evaluation of an underlying health problem. Breast cancer risk assessment and edema severity level classification are the main applications of STIP. We estimate the breast cancer risk by incorporating the patient’s personal risk value into the STIP-C data associated with the tumor mechanical properties to improve the risk assessment accuracy. To classify the edema severity level, the STIP-I measures the pitting parameters and viscoelastic properties of the tissue. From these parameters, we build a Viscoelastic Pitting Recovery (VPR) model. The model illustrates the changes in tissue viscoelastic behavior associated with the edema severity level. Using the VPR model, we use the thresholding method to classify the edema cases. We also developed customized phantoms representing the different amounts of fluid retention in the tissue. The experimental result found a relationship between the amounts of pitted depth from STIP-I and the fluid amount of a phantom. In this dissertation, we developed and tested a portable tissue mechanical property estimation system. The interchangeable dual-mode STIP sensing probe and risk assessment methods were developed for the breast tumor malignancy and edema severity applications. / Electrical and Computer Engineering