To predict the risk of delirium using physical activity and physiological data, each patient participating in the study will be categorized as to presence of delirium based on CAM-ICU questionnaire. Logistic regression analysis will be used to examine the relation between each physical activity variable (e.g. lying time) and physiological measures (e.g. heart rate) with delirium risk. Firstly, univariate logistic regression, using presence of delirium as the dependent variable, will be employed to investigate the relationship of the test variables. The Odd Ratios (OR) and coefficient of determination (R2) will be calculated for each explanatory variable. Then multivariate logistic regression using stepwise-automated methods will be performed to investigate the independent effects of the physical activity variables and physiological measures in predicting delirium. Sensitivities, specificities, positive and negative predictive values of different cut-off values will be calculated for any non-categorical variable shown to have an independent effect on predicting delirium. A two-sided P-value ≤0.05 will be considered to be statistically significant. Statistical analysis will be performed using SPSS (Statistical Package for the Social Sciences) statistics 22.0 (IBM, Armonk (name of town), NY (New York), USA).