The study is a multicentric prospective randomised cross-over study. It evaluates the compatibility of patients with the device without altering the routine treatment applied. During this evaluation, either the clinician-adjusted values on the device or the standard pre-set values are used to obtain hourly and 30-minute PVA (Patient Ventilator Asynchrony) recordings. These recordings will be analysed offline to identify the settings used and to compare the hourly and 30-minute PVA (Patient Ventilator Asynchrony) values when synchronisation is automatically set. The relationships and differences between these values will be analysed. For this purpose, the IntelliSync+ option, already available on the device, will be used. This software continuously analyses waveform signals at least a hundred times per second. This allows for the immediate detection of patient efforts and the initiation of inspiration and expiration in real time, thereby replacing traditional trigger settings for inspiration and expiration. If the patient is already synchronised with this option, it will then be possible to switch to traditional synchronisation settings for comparison. Statistical analyses will be conducted using SPSS 24.0, JASP (Just Another Statistical Programme), Jamovi ( fork of JASP), or R software. Initially, all numerical and categorical data will be evaluated using descriptive statistical methods. The distributions of numerical variables will be examined using visual (histograms and probability plots) and analytical methods (Kolmogorov-Smirnov/Shapiro-Wilk tests). Mean/SD (standard deviation) or median/interquartile range (IQR) will be used as measures of distribution. For comparing numerical data that follows a normal distribution, the Student-t test will be used, and for non-normally distributed data, the Mann-Whitney U or Wilcoxon signed-rank tests will be employed. PVA (Patient Ventilator Asynchrony) values will be statistically compared. For the analysis of categorical data, the Chi-Square test will be applied. Bayesian analysis may also be used as necessary during the writing of the study. The results obtained will be interpreted and reported by the researchers. Results with a p value below 0.05 will be considered statistically significant.