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The objective of this project is to develop a mechanism to detect fatigue via eye-tracking measures
Fatigue can have an impact on the physical as well as the emotional health of the individuals. Detection of fatigue is the first step towards its management.
Background
Fatigue can be a disabling symptom in neurological disorders like cerebral palsy, muscular dystrophy, amyotrophic lateral sclerosis [2]. Fatigue can affect aspects of life other than just health, like emotions, productivity and social behavior [4] and result in additional reduction in attention, cognitive processing power, reaction times and task performance [3]. Moreover, for people with neurological disorders who use alternate means like eye-tracking for communication, onset of fatigue can imply a halt in communication.
Objectives
Fatigue is a composite concept. It is closely inter-correlated with cognitive load, attention and task performance. Hence, it is important to assess all aspects of fatigue. The idea is to induce cognitive load, and study the fatigue levels using subjective questionnaires and attention tests before and after the experiment. Since the first use-case in this project is people with neurological disorders, and monitoring fatigue when they are using their communication system, the experiments will be based around the task of gaze-typing.
Here are the five stages of the project, defined by five experiments:
- Assess gaze-typing as a task to induce cognitive load.
- Cognitive load measurement on a large scale and exploration of fatigue
- Pilot study with people with neurological disorders to explore the experiment boundaries
- Inclusion of attention tests in the experiment protocol
- Longitudinal study with people with neurological disorders
This kind of assessment finds application in measuring the cognitive load and/or fatigue during various tasks, like flying aircrafts [1], long haul driving and performing surgery after a long shift [4]. Fatigue is a major source of human error in these professions and often results in a case of life and death.
References
- Gianluca Borghini, Laura Astolfi, Giovanni Vecchiato, Donatella Mattia, and Fabio Babiloni. 2014. Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness. Neuroscience and Biobehavioral Reviews 44: 58–75. https://doi.org/10.1016/j.neubiorev.2012.10.003
- Abhijit Chaudhuri and Peter O Behan. 2004. Fatigue in neurological disorders. The Lancet 363: 1–11. Retrieved from papers2://publication/doi/10.1016/S0140-6736(04)15794-2
- Jesper F. Hopstaken, Dimitri van der Linden, Arnold B. Bakker, and Michiel A.J. Kompier. 2015. A multifaceted investigation of the link between mental fatigue and task disengagement. Psychophysiology 52, 3: 305–315. https://doi.org/10.1111/psyp.12339
- André Pimenta, Davide Carneiro, José Neves, and Paulo Novais. 2016. A neural network to classify fatigue from human-computer interaction. Neurocomputing 172: 413–426. https://doi.org/10.1016/j.neucom.2015.03.105