Paper Info
Title
Effect Of Mental Workload On Breathing Pattern And Heart Rate For A Working Memory Task: A Pilot Study
Abstract
Mental workload or cognitive load is the total amount of mental resources required while doing a task. Apart from qualitative measures, various physiological signals are being used for assessment of mental workload. However, very limited research has been done on assessment of cognitive load from respiratory signals. In the present study, we have tried to analyze the cognitive load mainly based on respiratory features. n-back memory test has been modified to impart low and high cognitive load. The peripheral blood volume signal (PPG) collected while executing the task is used to reconstruct the breathing pattern signal. A number of morphological as well as statistical features are calculated from this reconstructed signal. Finally a classifier is used for classifying the low and high cognitive load. Results show that a classification accuracy of 76.8% is obtained while using respiratory features only. A maximum accuracy of 81.80% is obtained if we combine time domain PPG features with respiratory features. The features finally selected can also be used to study the habituation effect.
Year
DOI
Venue
2019
10.1109/EMBC.2019.8856458
2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Keywords
Field
DocType
Cognitive load, mental workload, breathing pattern, PPG, random forest
Time domain,Computer vision,Task analysis,Pattern recognition,Computer science,Heart rate variability,Workload,Working memory,Artificial intelligence,Breathing,Classifier (linguistics),Cognitive load
Conference
Volume
ISSN
Citations 
2019
1557-170X
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Dibyanshu Jaiswal111.72
Arijit Chowdhury2117.83
Tanushree Banerjee301.01
Debatri Chatterjee42811.52