Age effects on EEG correlates of the Wisconsin card sorting test

Body and brain undergo several changes with aging. One of the domains in which these changes are more remarkable relates with cognitive performance. In the present work, electroencephalogram (EEG) markers (power spectral density and spectral coherence) of age-related cognitive decline were sought whilst the subjects performed the Wisconsin Card Sorting Test (WCST). Considering the expected age-related cognitive deficits, WCST was applied to young, mid-age and elderly participants, and the theta and alpha frequency bands were analyzed. From the results herein presented, higher theta and alpha power were found to be associated with a good performance in the WCST of younger subjects. Additionally, higher theta and alpha coherence were also associated with good performance and were shown to decline with age and a decrease in alpha peak frequency seems to be associated with aging. Additionally, inter-hemispheric long-range coherences and parietal theta power were identified as age-independent EEG correlates of cognitive performance. In summary, these data reveals age-dependent as well as age-independent EEG correlates of cognitive performance that contribute to the understanding of brain aging and related cognitive deficits.

Integration methods in dynamic analysis

"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"

The Portuguese version of the Psychological Adjustment to Separation Test-Part A (PAST-A): a study with recently and non-recently divorced adults

Past research has demonstrated that divorced adults show more health problems and psychological distress than married adults. Considering the high prevalence rates of divorce among Western countries, new and robust measures should be developed to measure psychological distress after this specific transition in adulthood. The aim of this study was to adapt and validate a Portuguese version of the Psychological Adjustment to Separation Test-Part A (PAST-A; Sweeper and Halford in J Family Psychol 20(4):632–640, 2006). PAST-A is a self-report measure that assesses two key dimensions of separation adjustment problems: lonely-negativity and former partner attachment. Psychometric properties of the Portuguese version of PAST-A were assessed in terms of factor structure, internal consistency, and convergent and divergent validity, in an online convenience sample with divorced adults (N = 460). The PAST-A two-factor structure was confirmed by exploratory and confirmatory factor analyses, with each factor demonstrating very satisfactory internal consistency and good convergence. In terms of discriminant validity, the Portuguese PAST-A reveals a distinct factor from psychological growth after divorce. The results provided support for the use of the Portuguese PAST-A with divorced adults and also suggested that the explicative factors of the psychological adjustment to divorce may be cross-cultural stable. The non-existence of validated divorce-related well-being measures and its implications for divorce research are also discussed.

Critical events in mechanically ventilated patients

Mechanical Ventilation is an artificial way to help a Patient to breathe. This procedure is used to support patients with respiratory diseases however in many cases it can provoke lung damages, Acute Respiratory Diseases or organ failure. With the goal to early detect possible patient breath problems a set of limit values was defined to some variables monitored by the ventilator (Average Ventilation Pressure, Compliance Dynamic, Flow, Peak, Plateau and Support Pressure, Positive end-expiratory pressure, Respiratory Rate) in order to create critical events. A critical event is verified when a patient has a value higher or lower than the normal range defined for a certain period of time. The values were defined after elaborate a literature review and meeting with physicians specialized in the area. This work uses data streaming and intelligent agents to process the values collected in real-time and classify them as critical or not. Real data provided by an Intensive Care Unit were used to design and test the solution. In this study it was possible to understand the importance of introduce critical events for Mechanically Ventilated Patients. In some cases a value is considered critical (can trigger an alarm) however it is a single event (instantaneous) and it has not a clinical significance for the patient. The introduction of critical events which crosses a range of values and a pre-defined duration contributes to improve the decision-making process by decreasing the number of false positives and having a better comprehension of the patient condition.

Optimization techniques to detect early ventilation extubation in intensive care units

The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.