An ICEEMDAN and SAX-based method for determining English reading comprehension status using functional near-infrared spectroscopy signals
Ural Akincioglu, Onder Aydemir, Ahmet Cil, Muhammed Baydere
TL;DR
This paper introduces a new method using brain signals to assess English reading comprehension quickly and objectively.
Contribution
The novel contribution is combining ICEEMDAN and SAX for analyzing fNIRS signals to determine reading comprehension status.
Findings
The proposed method achieved a classification accuracy of 89.02% using a double-validation labeling strategy.
Using k-NN classifier, the method showed effectiveness in determining reading comprehension status from fNIRS data.
The ICEEMDAN and SAX-based approach outperformed single-labeling strategies in accuracy.
Abstract
Accurate, rapid, and objective reading comprehension assessments, which are critical in both daily and educational lives, can be effectively conducted using brain signals. In this study, we proposed an improved complementary ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and symbolic aggregate approximation (SAX)-based method for determining the whole text reading comprehension status in English using functional near-infrared spectroscopy (fNIRS) signals. A total of 450 trials were recorded from 15 healthy participants as they read English texts. To facilitate labeling, participants were asked to rate their comprehension of the text using self-assessment scores, followed by answering a multiple-choice question with four options that comprehensively covered the whole text’s content. The proposed method consists of pre-processing, feature extraction, and…
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Taxonomy
TopicsEEG and Brain-Computer Interfaces · Heart Rate Variability and Autonomic Control · Advanced Chemical Sensor Technologies