Abstract
The aim of this study was to determine the effect of heartbeat-evoked potentials (HEPs) on the performance of an event-related potential (ERP)-based classification of mental workload (MWL). We produced low- and high-MWLs using a mental arithmetic task and measured the ERP response of 14 participants. ERP trials were divided into three conditions based on the effect of HEPs on ERPs: ERPHEP, containing the heartbeat in a period of 280–700ms in ERP epochs after the target; ERPA-HEP, not including the heartbeat within the same period; and ERPT, all trials including ERPA-HEP and ERPHEP. We then compared MWL classification performance using the amplitude and latency of the P600 ERP among the three conditions. The ERPA-HEP condition achieved an accuracy of 100% using a radial basis function-support vector machine (with 10-fold cross-validation), showing an increase of 14.3 and 28.6% in accuracy compared to ERPT (85.7%) and ERPHEP (71.4%), respectively. The results suggest that evoked potentials caused by heartbeat overlapped or interfered with the ERPs and weakened the ERP response to stimuli. This study reveals the effect of the evoked potentials induced by heartbeats on the performance of the MWL classification based on ERPs.
Highlights
Event-related potentials (ERPs) provide a powerful method for interpreting the relationship between the human mind and the brain
In the paired t-test, the subjective mental effort questionnaire (SMEQ) score of the high-mental workload (MWL) condition was significantly higher than that of the low-MWL condition [t(13) = −9.238, Hedges’ g = 3.796, 95% CI 2.556–5.036, p < 0.001]
A paired t-test of target accuracy in the ERP task showed a significant difference between the low- (M = −1.27, standard deviation (SD) = 3.29) and high-MWL (M = −10.13, SD = 8.38) conditions [t(13) = 3.762, Hedges’ g = −1.392, 95% CI –2.217 to −0.566, p < 0.01]
Summary
Event-related potentials (ERPs) provide a powerful method for interpreting the relationship between the human mind and the brain. Because brain activity in response to a single event or stimulus is not usually visible in electroencephalogram (EEG) signals, the ERP technique is required to measure the response to a stimulus in many trials (Coles and Rugg, 1995; Boudewyn et al, 2018). Changes of ERP by Hearbeat (Uriguen and Garcia-Zapirain, 2015) These artifacts can affect EEG signals and interfere with relevant or dominant potentials in ERPs. many previous studies have sought to remove artifacts, such as muscular activity (Chen et al, 2019; Zou et al, 2020), cardiac activity (Hamaneh et al, 2014; Dai et al, 2019), eyeblinks, and ocular movements (Dimigen, 2020; Egambaram et al, 2020). Evoked potentials are difficult to remove or recover because, unlike noise, they do not cause a change in the dominant pattern of the EEG signal but are instead contained in the EEG signal itself (Schandry and Montoya, 1996; McCraty et al, 2009)
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