  Recent worldwide events shed light on the need of human-centered systems
engineering in the healthcare domain. These systems must be prepared to evolve
quickly but safely, according to unpredicted environments and ever-changing
pathogens that spread ruthlessly. Such scenarios suffocate hospitals'
infrastructure and disable healthcare systems that are not prepared to deal
with unpredicted environments without costly re-engineering. In the face of
these challenges, we offer the SA-BSN -- Self-Adaptive Body Sensor Network --
prototype to explore the rather dynamic patient's health status monitoring. The
exemplar is focused on self-adaptation and comes with scenarios that hinder an
interplay between system reliability and battery consumption that is available
after each execution. Also, we provide: (i) a noise injection mechanism, (ii)
file-based patient profiles' configuration, (iii) six healthcare sensor
simulations, and (iv) an extensible/reusable controller implementation for
self-adaptation. The artifact is implemented in ROS (Robot Operating System),
which embraces principles such as ease of use and relies on an active open
source community support.
