SUMMARYThis paper reports on our experience with a relational approach to support the analysis of existing software architectures. The analysis options provide for visualization and view calculation. The approach has been applied for reverse engineering. It is also possible to check concrete designs against architecture-related rules. The paper surveys the theory, the tools and some of the applications developed so far.

The ability of autistic children to learn by applying logical rules has been used widely in behavioral therapies for social training. We propose to teach social skills to autistic children through games that simultaneously stimulate social behavior and include recognition of elements of social interaction. For this purpose we created a multi-agent platform of interactive blocks, and we created appropriate games that require shared activities leading to a common goal. The games included perceiving and understanding elements of social behavior that non-autistic children can recognize. We argue that the importance of elements of social interaction such as perceiving interaction behaviors and assigning metaphoric meanings has been overlooked, and that they are very important in the social training of autistic children. Two games were compared by testing them with users. The first game focused only on the interaction between the agents and the other combined interaction between the agents and metaphoric meanings that are assigned to them. The results show that most of the children recognized the patterns of interaction as well as the metaphors when they were demonstrated through embodied agents and were included within games having features that engage the interest of this user group. The results also show the potential of the platform and the games to influence the social behavior of the children positively.

AimAlarm fatigue is a well-recognized patient safety concern in intensive care settings. Decreased nurse responsiveness and slow response times to alarms are the potentially dangerous consequences of alarm fatigue. The aim of this study was to determine the factors that modulate nurse responsiveness to critical patient monitor and ventilator alarms in the context of a private room neonatal intensive care setting.MethodsThe study design comprised of both a questionnaire and video monitoring of nurse-responsiveness to critical alarms. The Likert scale questionnaire, comprising of 50 questions across thematic clusters (critical alarms, yellow alarms, perception, design, nursing action, and context) was administered to 56 nurses (90% response rate). Nearly 6000 critical alarms were recorded from 10 infants in approximately 2400 hours of video monitoring. Logistic regression was used to identify patient and alarm-level factors that modulate nurse-responsiveness to critical alarms, with a response being defined as a nurse entering the patient’s room within the 90s of the alarm being generated.ResultsBased on the questionnaire, the majority of nurses found critical alarms to be clinically relevant even though the alarms did not always mandate clinical action. Based on video observations, for a median of 34% (IQR, 20–52) of critical alarms, the nurse was already present in the room. For the remaining alarms, the response rate within 90s was 26%. The median response time was 55s (IQR, 37-70s). Desaturation alarms were the most prevalent and accounted for more than 50% of all alarms. The odds of responding to bradycardia alarms, compared to desaturation alarms, were 1.47 (95% CI = 1.21–1.78; <0.001) while that of responding to a ventilator alarm was lower at 0.35 (95% CI = 0.27–0.46; p <0.001). For every 20s increase in the duration of an alarm, the odds of responding to the alarm (within 90s) increased to 1.15 (95% CI = 1.1–1.2; p <0.001). The random effect per infant improved the fit of the model to the data with the response times being slower for infants suffering from chronic illnesses while being faster for infants who were clinically unstable.DiscussionEven though nurses respond to only a fraction of all critical alarms, they consider the vast majority of critical and yellow alarms as useful and relevant. When notified of a critical alarm, they seek waveform information and employ heuristics in determining whether or not to respond to the alarm.ConclusionAmongst other factors, the category and duration of critical alarms along with the clinical status of the patient determine nurse-responsiveness to alarms.

This article presents the design and evaluation of a Robot Interaction Language (ROILA). This speech recognition friendly spoken artificial language is designed to be used by humans for interacting with robots. We evaluated the use of ROILA in a Dutch high school. The language was taught as a part of the science curriculum followed by a controlled experiment, where the language was compared against English. The results from the experiment showed that the ROILA performed better than English on account of both objective recognition accuracy and the subjective assessment by the students. We estimate the trade-off between this benefit in relation to the effort required to learn ROILA. In a regular usage scenario, it would pay off to use ROILA.