Effect of Mental Workload on Breathing Pattern and Heart Rate for a Working Memory Task: A Pilot Study

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.