Using near infrared spectroscopy and heart rate variability to detect mental overload

Abstract

Mental workload is a key factor influencing the occurrence of human error, especially during piloting and remotely operated vehicle (ROV) operations, where safety depends on the ability of pilots to act appropriately. In particular, excessively high or low mental workload can lead operators to neglect critical information. The objective of the present study is to investigate the potential of functional near infrared spectroscopy (fNIRS) - a non-invasive method of measuring prefrontal cortex activity - in combination with measurements of heart rate variability (HRV), to predict mental workload during a simulated piloting task, with particular regard to task engagement and disengagement. Twelve volunteers performed a computer-based piloting task in which they were asked to follow a dynamic target with their aircraft, a task designed to replicate key cognitive demands associated with real life ROV operating tasks. In order to cover a wide range of mental workload levels, task difficulty was manipulated in terms of processing load and difficulty of control - two critical sources of workload associated with piloting and remotely operating a vehicle. Results show that both fNIRS and HRV are sensitive to different levels of mental workload; notably, lower prefrontal activation as well as a lower LF/HF ratio at the highest level of difficulty, suggest that these measures are suitable for mental overload detection. Moreover, these latter measurements point toward the existence of a quadratic model of mental workload.

Frequency analysis of a task-evoked pupillary response: Luminance-independent measure of mental effort

“…The ratio of PSD of the pupillary signal within Low and High frequency bands was significantly lower under load on memory condition compared to the control condition; but it did not differ in the luminance conditions. This result is in line with previous studies on the influence of mental workload on heart rate variability showing a greater increase of LF activity compared to HF activity (Durantin et al, 2014;Mizuno et al, 2011;Mukherjee et al, 2011). Nevertheless, note the difference between the frequency bands used in this study compared to the standardized bands used in heart rate variability studies.…”

“…Since the proposition of Pagani et al (1986), the ratio of cardiac signal powers within LF and HF bands, referred as LF/HF or LH ratio, although controversial (Billman, 2013), is often used to measure the sympatho-vagal balance. Some researchers reported an increase in LF/HF ratio induced by mental effort (Durantin et al, 2014;Mizuno et al, 2011;Mukherjee et al, 2011). Since LF/HF ratios in these studies were greater than 1, this increase could be interpreted as a greater increase in the LF band compared with the HF band.…”

The neuroergonomic evaluation of human machine interface design in air traffic control using behavioral and EEG/ERP measures

“…Our study is based on a neuroergonomic approach [30][31][32][33] which merges knowledge and methods from cognitive psychology, system engineering, and neurosciences. This approach aims to improve the system safety and efficiency at the workplace by considering human brain functioning.…”

Influence of computer work under time pressure on cardiac activity

“…Porges described stress as an autonomic state that reflects a disruption of homeostasis due to depressed parasympathetic tone [1]. Workload-related stress often produces changes in behavioral (e.g., higher error rates) [2,3] and physiological (e.g., faster heartbeat) functions [4,5]. Thus, the degree of stress can be mirrored from behavior performance and can be quantified on a physiological level.…”