Evaluation of Algorithms to Measure a Psychophysical Threshold Using Digital Applications

The use of digital applications like in mobile phone or on the web to perform psychophysical measurements led to the introduction of algorithms to guide the users in test execution. In this paper we show four algorithms, two already well known: STRICTN and PEST, and a two that we propose: PESTN and BESTN. All the algorithms aim at estimating the level of a psychophysical capability by performing a sequence of simple tests; starting from initial level N, the test is executed until the target level is reached. They differ in the choice of the next steps in the sequences and the stopping condition. We have simulated the application of the algorithms and we have compared them by answering a set of research questions. Finally, we provide guidelines to choose the best algorithm based on the test goal. We found that while STRICTN provides optimal results, it requires the largest number of steps, and this may hinder its use; PESTN can overcome these limits without compromising the final results.