Objective. To date, continuous cuff-based non-invasive blood pressure (NIBP) monitoring remains limited. NIBP provides intermittent readings for systolic blood pressure (SBP) but misses short-term SBP fluctuations. Newly developed approaches that use the photoplethysmogram (PPG) for estimating SBP generalize poorly without calibration due to subject-specific vascular properties. To overcome these limitations, we reformulate PPG-based SBP estimation as estimating the change in SBP ( (Formula presented) (Formula presented) ) between two time points. Approach. We implemented a learning-based approach that compares pairs of 20-second PPG segments to estimate (Formula presented) (Formula presented). Our approach was developed and evaluated on 12 279 patients, with a held-out test set comprising 2457 patients, collected from the VitalDB and MIMIC-III datasets. Root mean squared error ( (Formula presented) (Formula presented) ), Pearson correlation coefficient ( (Formula presented) (Formula presented) ), and Cohen’s kappa ( (Formula presented) (Formula presented) ) were used for performance quantification. Main results. On the held-out test sets, our approach achieved (Formula presented) (Formula presented) of 14.53/11.37 mmHg, (Formula presented) (Formula presented) of 0.79/0.65, and (Formula presented) (Formula presented) of 0.57/0.44 for PPG-based (Formula presented) (Formula presented) (VitalDB/MIMIC-III), across segment pairs separated by 1 min to multiple hours. Errors occurred primarily in cases where morphological analyses identified only minor changes in the waveform despite large (Formula presented) (Formula presented) values, especially in MIMIC-III. Model predictions correlated more strongly with SBP than with heart rate, indicating reliance on pulse wave morphology. Long-term analysis demonstrated stable (Formula presented) (Formula presented) estimation over 28 h. Significance. Our results support the potential of morphology-based relative blood pressure estimation using PPG. The introduced approach could complement cuff-based monitoring by filling gaps between intermittent measurements, particularly during sleep, where cuff inflations are disruptive.