Parsimonious Identification of Physiological Indices for Monitoring Cognitive Fatigue
The objective of this study was to identify a parsimonious set of physiological measures that could be used to best predict cognitive fatigue levels. A 37 hour sleep deprivation study was conducted to induce reduced levels of alertness and cognitive impairment as measured by a psychomotor vigilance test. Non-invasive, wearable and ambulatory sensors were used to acquire cardio-respiratory and motion data during the sleep deprivation. Subsequently 23 potential predictors were derived from the raw sensor data. The least absolute shrinkage and selection operator, along with a cross validation strategy was used to create a sparse model and identify a minimum predictor subset that provided the best prediction accuracy. Final predictor selection was found to vary with task and context. Depending on context selected predictors indicated elevated levels of sympathetic nervous system activity, increased restlessness during engaging tasks and increased cardio-respiratory synchronization with increasing cognitive fatigue.
Keywordscognitive fatigue heart rate variability feature selection wearable sensors
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- 1.Kleitman, N.: Duration of sleep. In: Sleep and Wakefulness, pp. 114–121. University of Chicago Press, Chicago (1963)Google Scholar
- 2.National Sleep Foundation. In: 2005 Sleep in America poll. Washington, National Sleep Foundation (2005) Google Scholar
- 4.Carskadon, M.A., Roth, T.: Sleep restriction. In: Monk, T.H. (ed.) Sleep, sleepiness and performance. John Wiley & Sons, New York (1991)Google Scholar
- 8.Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology: Heart Rate Variability. Standards of Measurement, Physiological Interpretation, and Clinical Use.: Circulation 93, 1043–1065 (1996)Google Scholar
- 14.Tibshirani, R.: Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58, 267–288 (1996)Google Scholar