Mental fatigue measurement using eye metrics: A systematic literature review.

Mental fatigue measurement techniques utilize one or a combination of the cognitive, affective, and behavioral responses of the body. Eye-tracking and electrooculography, which are used to compute eye-based features, have gained momentum with increases in accuracy and robustness of the lightweight equipment emerging in the markets and can be used for objective and continuous assessment of mental fatigue. The main goal of this systematic review was to summarize the various eye-based features that have been used to measure mental fatigue and explore the relation of eye-based features to mental fatigue. The review process, following the preferred reporting items for systematic reviews and meta-analyses, used the electronic databases Web of Science, Scopus, ACM digital library, IEEE Xplore, and PubMed. Of the 1,385 retrieved documents, 34 studies met the inclusion criteria, resulting in 21 useful eye-based features. Categorizing these into eight groups revealed saccades as the most promising category, with saccade mean and peak velocity providing quick access to the cognitive states within 30 min of fatiguing activity. Complex brain networks involving sympathetic and parasympathetic nervous systems control the relation of mental fatigue to tonic pupil size and have the potential to indicate mental fatigue in controlled experimental conditions. Other categories, like blinks, are derived from the field of sleep research and should be used with caution. Several limitations emerged in the analysis, including varied experimental methods, use of dim lighting during the experiment (that could possibly also induce sleepiness), and use of unclear data analysis techniques, thereby complicating comparisons between studies.

Mental fatigue prediction during eye-typing.

Mental fatigue is a common problem associated with neurological disorders. Until now, there has not been a method to assess mental fatigue on a continuous scale. Camera-based eye-typing is commonly used for communication by people with severe neurological disorders. We designed a working memory-based eye-typing experiment with 18 healthy participants, and obtained eye-tracking and typing performance data in addition to their subjective scores on perceived effort for every sentence typed and mental fatigue, to create a model of mental fatigue for eye-typing. The features of the model were the eye-based blink frequency, eye height and baseline-related pupil diameter. We predicted subjective ratings of mental fatigue on a six-point Likert scale, using random forest regression, with 22% lower mean absolute error than using simulations. When additionally including task difficulty (i.e. the difficulty of the sentences typed) as a feature, the variance explained by the model increased by 9%. This indicates that task difficulty plays an important role in modelling mental fatigue. The results demonstrate the feasibility of objective and non-intrusive measurement of fatigue on a continuous scale.

Emergence of an Action Repository as Part of a Biologically Inspired Model of Speech Processing: The Role of Somatosensory Information in Learning Phonetic-Phonological Sound Features.

A comprehensive model of speech processing and speech learning has been established. The model comprises a mental lexicon, an action repository and an articulatory-acoustic module for executing motor plans and generating auditory and somatosensory feedback information (Kröger and Cao, 2015). In this study a "model language" based on three auditory and motor realizations of 70 monosyllabic words has been trained in order to simulate early phases of speech acquisition (babbling and imitation). We were able to show that (i) the emergence of phonetic-phonological features results from an increasing degree of ordering of syllable representations within the action repository and that (ii) this ordering or arrangement of syllables is mainly shaped by auditory information. Somatosensory information helps to increase the speed of learning. Especially consonantal features like place of articulation are learned earlier if auditory information is accompanied by somatosensory information. It can be concluded that somatosensory information as it is generated already during the babbling and the imitation phase of speech acquisition is very helpful especially for learning features like place of articulation. After learning is completed acoustic information together with semantic information is sufficient for determining the phonetic-phonological information from the speech signal. Moreover it is possible to learn phonetic-phonological features like place of articulation from auditory and semantic information only but not as fast as when somatosensory information is also available during the early stages of learning.