We can now buy consumer brain-computer interface devices to help us meditate and focus, but what are we aiming to achieve? Mental workload (MWL) is an established concept, and as a form of personal data could be useful for making positive life changes. However, MWL is typically only studied for isolated tasks to avoid overload and underload. We investigated lived experiences of MWL, aiming to understand how tracking such data could implicate our everyday lives. 19 participants, that had previously experienced tracking their mental workload, took part in interviews and an Interpretive Phenomenological Analysis identified four superordinate themes. Results point towards mixed and changing perceptions of MWL and the importance of fluctuating between MWL levels in daily life in terms of performances, perceptions, and wellbeing. These findings are captured in an apparent Cycle, which outside factors can disrupt, and we discuss these cycles in terms of personal informatics and work performance.

The motivation behind using physiological measures to estimate cognitive activity is typically to build technology that can help people to understand themselves and their work, or indeed for systems to do so and adapt. While functional Near Infrared Spectroscopy (fNIRS) has been shown to reliably reflect manipulations of mental workload in different work tasks, we still need to establish whether fNIRS can differentiate variety within common office-like tasks in order to broaden our understanding of the factors involved in tracking them in real working conditions. 20 healthy participants (8 females, 12 males), whose work included office-like tasks, took part in a user study that investigated a) the sensitivity of fNIRS for measuring mental workload variations in representations of everyday reading and writing tasks, and b) how representations of natural interruptions are reflected in the data. Results supported fNIRS measuring PFC activation in differentiating between workload levels for reading tasks but not writing tasks in terms of increased oxygenated haemoglobin (O2Hb) and decreased deoxygenated haemoglobin (HHb), for harder conditions compared to easier conditions. There was considerable support for fNIRS in detecting changes in workload levels due to interruptions. Variations in workload levels during the interruptions could be understood in relation to spare capacity models. These findings may guide future work into sustained monitoring of cognitive activity in real-world settings.