In this study, we propose a stress classification algorithm to determine whether the user is exposed to stress, using Empirical Mode Decomposition and Fast Fourier Transform on multiple bio-signals. Electrocardiogram (ECG) and Photoplethysmogram (PPG) signals were detected from the user’s arm for accurate classification of stress. Heart Rate Variability and Pulse Rate Variability were calculated and stress levels were evaluated. By using the EMD and FFT techniques, the bio-signals in the frequency band were analyzed in various stress levels. As a result of analyzing the stress, it was confirmed that R interval value and mean frequency value when stressed situation were lower values. The proposed system is expected to help mental health by indexing the degree of stress experienced by modern people.