RESUMEN
In 2021, the International Olympic Committee ventured virtual space by launching their first ever Olympic Virtual Series - featuring virtual baseball, cycling, rowing, sailing and motor racing. Interestingly, all these virtual events take strongly after their physical counterparts. Which begs the question: Where are the massively popular esports games like Fortnite, League of Legends, and Dota?-What do the Olympic Virtual Series have that these popular video games do not? Here, we argue for the inclusion of esports within the Olympic program. In many respects, esports "act" and "behave" just like traditional sports. We argue that esports and traditional sports share many of the same values, like the values of meritocracy, competition, fair play, and the value of having a "level playing field". Yet, in esports, many of these values remain underappreciated, losing out to negative values such as physical inactivity and game-addiction. To preserve what is worth preserving, we borrow from Value Sensitive Design to ameliorate the design-tensions that are foregrounded in esports. Thereby, paving possible ways toward the inclusion of esports in the Olympic program. Ultimately, the question for the IOC should not be "does it look like 'real sport', as we know it?", but rather: are they sporting, rule-led, and fair activities worth preserving and setting an example for a new digitally savvy generation?
RESUMEN
Cardiac surgery patients infrequently mobilize during their hospital stay. It is unclear for patients why mobilization is important, and exact progress of mobilization activities is not available. The aim of this study was to select and evaluate accelerometers for objective qualification of in-hospital mobilization after cardiac surgery. Six static and dynamic patient activities were defined to measure patient mobilization during the postoperative hospital stay. Device requirements were formulated, and the available devices reviewed. A triaxial accelerometer (AX3, Axivity) was selected for a clinical pilot in a heart surgery ward and placed on both the upper arm and upper leg. An artificial neural network algorithm was applied to classify lying in bed, sitting in a chair, standing, walking, cycling on an exercise bike, and walking the stairs. The primary endpoint was the daily amount of each activity performed between 7 a.m. and 11 p.m. The secondary endpoints were length of intensive care unit stay and surgical ward stay. A subgroup analysis for male and female patients was planned. In total, 29 patients were classified after cardiac surgery with an intensive care unit stay of 1 (1 to 2) night and surgical ward stay of 5 (3 to 6) nights. Patients spent 41 (20 to 62) min less time in bed for each consecutive hospital day, as determined by a mixed-model analysis (p < 0.001). Standing, walking, and walking the stairs increased during the hospital stay. No differences between men (n = 22) and women (n = 7) were observed for all endpoints in this study. The approach presented in this study is applicable for measuring all six activities and for monitoring postoperative recovery of cardiac surgery patients. A next step is to provide feedback to patients and healthcare professionals, to speed up recovery.