This paper proposes principles and methods for assessing the robustness of ST segment analysers and algorithms. We describe an evaluation protocol, procedures and performance measures suitable for assessing the robustness. An ST analyser is robust if its performance is not critically dependent on the variation of the noise content of input signals and on the choice of the database used for testing, and if its analysis parameters are not critically tuned to the database used for testing. The protocol to assess the robustness includes: (1) a noise stress test addressing the aspect of variation of input signals; (2) a bootstrap evaluation of algorithm performance addressing the aspect of distribution of input signals and (3) a sensitivity analysis addressing the aspect of variation of analyser's architecture parameters. An ST analyser is considered to be robust if the performance measurements obtained during these procedures remain above the predefined critical performance boundaries. We illustrate the use of the robustness protocol and robustness measures by a case study in which we assessed the robustness of our Karhunen-Loève transform based ischaemic ST episode detection and quantification algorithm using the European Society of Cardiology ST-T database.