Timely detection and assessment of a disease is the most crucial and fundamental step of an effective treatment. In cases of neurological disorders, a prompt and accurate diagnosis is vital to prevent permanent brain damage that could also be lethal. Evoked potential (EP) monitoring, especially in operation theatre and intensive care, is an important indicator of the proper brain functioning and the depth of anesthesia. Currently, detection and interpretation of EP is visual, time consuming and requires trained professionals. Also, EPs are very difficult to detect in real time and its manual detection and interpretation results in large element of inconsistency and subjectivity. We have developed an algorithm, which is capable of automatically detecting and interpreting the EEG waveforms for the presence or absence of EP in real time and warn the user about the possible abnormalities. The proposed looks for the presence or absence of the EPs in the pre-selected time windows. The entire duration of the waveforms are not examined. Typically the examined data are about 10-15 % of the total recorded data. Our project objectives were: 1) To convert the paper form of patient EEG records in to digital format, suitable for computer processing. 2) To smoothen the waveform to reduce the misclassification due to noise or transient effects. 3) To identify peaks and troughs in the waveforms and calculate the latency and amplitudes of the EP in the critical sections of three channels of somatosensory EP records. 4) To flash warning signals and mark the sections of the waveforms if any abnormality is detected. The MATLAB image processing and signal processing toolbox were used to develop the algorithms. Our software works well and is successful in detecting the peaks and valleys and then calculating the peak amplitude and onset latency in the EP waveforms. However, it has not been tested extensively. It may require further improvements for achieving robustness and consistency. Algorithm has been validated against the pre-specified criteria and the results have been very interesting.