In this paper, a technique named I-EQM, able to dynamically isolate first order equivalent mutants, is proposed. I-EQM works by employing a novel dynamic execution scheme that integrates both first and second order mutation. The proposed approach combines the "impact" on the program execution of the first order mutants with the "impact" on the output of second order ones, to isolate likely to be first order equivalent mutants. Experimental results on a benchmark set of manually classified mutants, selected from real word programs, reveals that I-EQM achieves to classify equivalent mutants with a 71% and 82% classification precision and recall respectively. These results improve the previously proposed approaches by selecting (retrieving) a considerably higher number of killable mutants with only a limited loss on the classification precision.