This paper presents a signal pre-processing and feature extraction approach based on electrocardiogram (ECG) sensor signal. The extracted features are used to formulate cases in a case-based reasoning system to develop a personalized stress diagnosis system. The results obtained from the evaluation show a performance close to an expert in the domain in diagnosing stress using ECG sensor signal.