Due to the uncertainty and inherent complexity in the zero-phase digital Riesz differentiator-type optimisation problem, numerous distinct objectives must be taken into account together to obtain an accurate frequency response of the designed Riesz digital differentiator. In this article, the realisation of finite impulse response (FIR)-type zero-phase digital Riesz first-order differentiator (DRFOD) is proposed by employing a metaheuristic multiobjective salp swarm algorithm (MOSSA). An adequately developed multiobjective function is formulated to optimise the coefficients of the DRFOD to achieve the near-ideal magnitude response along with an almost zero-phase response characteristic. The performance of the MOSSA-based DRFOD is compared to the state-of-the-art non-dominated sorting genetic algorithm version II (NSGA-II) and multiobjective particle swarm optimisation (MOPSO)-based DRFODs. The statistical results show that the performance of the proposed DRFOD not only holds supremacy over the MOPSO and NSGA-II-based DRFODs in terms of magnitude and phase errors but also for convergence speed. The maximum phase error (MPE) and normalised maximum absolute magnitude error (MAMEnorm) of the proposed DRFOD are as low as 4.9648E−014 degrees and 0.0110, respectively. Regarding MAMEnorm, the proposed MOSSA-based DRFOD achieves a percentage of improvements (PI) of 84 and 83% compared to NSGA-II and MOPSO-based DRFODs, respectively. Similarly, in terms of MPE, the proposed DRFOD design achieves PI of 49 and 15% compared to MOPSO and NSGA-II-based designs, respectively. Also, the exemplary applications on real PhysioNet ECG signals are thoroughly examined to ensure the practical applicability of the zero-phase characteristics of the proposed DRFOD.