Cardiovascular data (blood pressure, ECG, etc.) is often analysed using Heart Rate Variability (HRV) methods. Indeed, there have been over 26,000 papers which refer to HRV since the first articles appeared in 1965. The first step of all HRV methods is to extract the beat-to-beat intervals, which are then analysed in numerous ways. But the first step involves discarding the vast majority of the data and clearly HRV methods cannot detect any changes in the shape of the waveform. The paper “Beyond HRV: attractor reconstruction using the entire cardiovascular waveform data for novel feature extraction” by Philip Aston, Mark Christie (King’s College London), Ying Huang and Manasi Nandi (King’s College London), which has been published in the journal Physiological Measurement, proposes that “it is time to move beyond HRV and to develop a new generation of methods of analysis of physiological data that analyse all of the data contained within a particular waveform”. The paper describes such a method, based on attractor reconstruction using delay coordinates. An example demonstrates that the new method can clearly detect a change in some sample blood pressure data that HRV methods do not detect, confirming that the method does indeed go “beyond HRV”.  The paper is published open access, and a link to the paper is here.