Due to the high cost of equipment and lack of trained personnel, manual palpation is a preferred alternative breast examination technique over mammography. The process involves a thorough search pattern using trained fingers and applying adequate pressure, with the objective of identifying solid masses from the surrounding breast tissue. However, palpation requires skills that must be obtained through adequate training in order to ensure proper diagnosis. Consequently, palpation performance and reporting techniques have been inconsistent. Automating the palpation technique would optimize the performance of self-breast examination, optimize clinical breast examinations (CBE), and enable the visualization of breast abnormalities as well as assessing their mechanical properties. Various methods of reconstructing the internal mechanical properties of breast tissue abnormalities have been explored. However, all systems that have been reported are bulky and rely on complex electronic systems. Hence, they are both expensive and require trained medical professionals. The methods also do not involve palpation, a key element in CBE. This research aims in developing a portable and inexpensive automated palpable system that mimics CBE to quantitatively image breast lumps. The method uses a piezoresistive sensor equipped probe consisting of an electronic circuit for collecting deformation-induced electrical signals. The piezoresistive sensor is made by spraying microwave exfoliated graphite/latex blend on a latex sheet. Lumps can be detected by monitoring a change in electrical resistance caused by the deformation of the sensor which is induced by abnormalities in the breast tissue. The electrical signals are collected using a microcontroller and a pixelated image of the breast can be reconstructed. The research is still in progress, and this report serves as proof of concept testing by pressing the probe with hand pressure and reconstructing the electrical signals using Microsoft Excel. Four maps were created for qualitatively analyzing the result. The pressure maps clearly display areas where pressure was applied, indicating the potential of the probe in detecting breast tissue abnormalities. The pressure maps show the feasibility for using such a sensor for the application in CBE. Furthermore, a sensor such as this is also possible of detecting the depth and size of masses within breast tissue, which, may lead to a more accurate diagnosis. Better manufacturing, accuracy, precision, and realtime data feeds are areas of future consideration for this project. This project involves knowledge and applications from mechanical, electrical, computational, and materials engineering.