Most PPG-based methods for extracting the respiratory rate (RR) rely on changes in the PPG signal's amplitude, baseline, or frequency. However, several other parameters may provide more valuable information for accurate RR computation. In this study, we explored the capabilities of the respiratory-induced variations in successive systolic differences (RISSDV) of PPG signals to estimate RR. We partitioned fifty-three publicly available recordings into eight 1-min segments and identified peaks and troughs of the PPG signals to quantify respiratory-induced variations in amplitude (RIAV), baseline (RIIV), frequency (RIFV), and peak-to-peak amplitude differences (RISSDV). RR values were extracted by determining the peak frequency of the power spectral density of the four variations and the reference respiratory signal. We assessed each feature's performance by computing the root-mean-squared (RMSE) and mean absolute errors (MAE). RISSDV errors were significantly lower than those of RIAV (RMSE and MAE: p < 0.001), RIIV (RMSE: p < 0.01; MAE p < 0.05), and RIFV (RMSE and MAE: p < 0.001), and it appeared less sensitive to absent or missed PPG pulses than respiratory-induced frequency variations. Further research is necessary to extrapolate these findings to subjects under ambulatory rather than stationary conditions, including pediatric and neonatal populations.