The Readiness Potential: a systematic review about the influencing factors and the development of an algorithm for automatic features extraction
Leonardo Cardinali · 2019
The goals that this thesis work wants to achieve are two: one objective is to redact a schematic review of the Readiness Potential, the components it is made of (early BP, late BP and also LRP) and the factors modulating its waveform; the other is to write a program that performs onsets and amplitudes measurements using methods found in literature and to compare these results to observe the robustness of the different algorithms. These methods include peak and mean amplitude measurements using different parameters, as well as many onsets measurements, divided in criterion-based, baseline-based and regression-based methods. To understand the robustness of these techniques we divided our dataset in three categories: high-quality, medium-quality and low-quality data. For high-quality data, as expected, no problem arises and the measurements are correctly performed, while for lower quality data many measurements are impossible or produce implausible results. For amplitudes methods, the less reliable is the method based on the work from Wright et al., while the other two produce reliable results in medium and and high-quality conditions. For onset measurements, the method that revealed to be less reliable is the criterion-based method, while the most reliable methods are the regression-based methods. The cleanliness of the data on which the proposed algorithms are performed is crucial for the goodness of the measurements. One of the most problematic issue in dirty data is the noise present in the baseline period.