Open AccessEvaluating cognitive task result through heart rate pattern analysis
Author(s) -
Yu Juan,
Liu Guang Yuan,
Wen Wan Hui,
Chen Chuan Wu
Publication year - 2020
Publication title -
healthcare technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.45
H-Index - 19
ISSN - 2053-3713
DOI - 10.1049/htl.2018.5068
Subject(s) - heartbeat , computer science , subtraction , task (project management) , cognition , binary classification , pattern recognition (psychology) , artificial intelligence , elementary cognitive task , numerical digit , speech recognition , support vector machine , psychology , mathematics , neuroscience , computer security , management , arithmetic , economics
The measurement of the right and wrong results of cognitive tasks has important applications in many commercial and educational areas such as the drivers’ training system, the simulation training and online learning system. This Letter aims to distinguish the heartbeat pattern of cognitively wrong responses to that of cognitively right responses based on the electrocardiogram (ECG) through 36 subjects with different professional backgrounds. The experimental design methods were double‐digit and five‐digit addition/subtraction, which were blindly selected by subjects from a black box. Through the R–R interval (RRI) series obtained from the ECG data, some linear, nonlinear and moment features were extracted to evaluate the cognitive task results by using pattern recognition methods. The binary classification of RRI datasets indicated that autonomic nerve patterns of the right and wrong cognitive heartbeat responses were distinguishable.