According to the World Health Organization (WHO) cardiovascular diseases (CVDs) are the prime cause of death in developed countries. Arterial pulse waveform (APW) analysis provides a non-invasive way for early diagnosis of CVDs. The present work reports the elaboration of an automatic algorithm to extract and classify the acquired data of APW signals based on the risk of CVD related problems. To extract the data several signal pre-processing methods were applied for noise reduction and pulse segmentation. Then, a K-Means clustering algorithm was applied to select the higher quality APWs. The...