Mental workload classification using heart rate metrics

The ability of different short-term heart rate variability metrics to classify the level of mental workload (MWL) in 140 s segments was studied. Electrocardiographic data and event related potentials (ERPs), calculated from electroencephalographic data, were collected from 13 healthy subjects during the performance of a computerised cognitive multitask test with different task load levels. The amplitude of the P300 component of the ERPs was used as an objective measure of MWL. Receiver operating characteristics analysis (ROC) showed that the time domain metric of average interbeat interval length was the best-performing metric in terms of classification ability.

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