Electrical Impedance Spectroscopy (EIS) has shown promising results for differentiating between malignant and benign tumors, which exhibit different dielectric properties. However, the performance of current EIS systems has been inadequate and unacceptable in clinical practice. In the last several years, we have been developing and testing a new EIS approach using resonance frequencies for detection and classification of suspicious tumors. From this experience, we identified several limitations of current technologies and designed a new EIS system with a number of new characteristics that include (1) an increased A/D (analog-to-digital) sampling frequency, 24 bits, and a frequency resolution of 100 Hz, to increase detection sensitivity (2) automated calibration to monitor and correct variations in electronic components within the system, (3) temperature sensing and compensation algorithms to minimize impact of environmental change during testing, and (4) multiple inductor-switching to select optimum resonance frequencies. We performed a theoretical simulation to analyze the impact of adding these new functions for improving performance of the system. This system was also tested using phantoms filled with variety of liquids. The theoretical and experimental test results are consistent with each other. The experimental results demonstrated that this new EIS device possesses the improved sensitivity and/or signal detection resolution for detecting small impedance or capacitance variations. This provides the potential of applying this new EIS technology to different cancer detection and diagnosis tasks in the future.