Key result
A computational method using formal and psychoacoustic modeling successfully detects simultaneous masking in medical alarms.
A novel computational method using model checking can detect simultaneous masking in medical alarms before deployment, potentially improving patient safety.
May enable pre-deployment detection of masked alarms; leaves open whether it reduces clinical incidents.
The ability of people to hear and respond to auditory medical alarms is critical to the health and safety of patients. Unfortunately, concurrently sounding alarms can perceptually interact in ways that mask one or more of them: making them impossible to hear. Because masking may only occur in extremely specific and/or rare situations, experimental evaluation techniques are insufficient for detecting masking in all of the potential alarm configurations used in medicine. Thus, a real need exists for computational methods capable of determining if masking exists in medical alarm configurations before they are deployed. In this paper, we present such a method. Using a combination of formal modeling, psychoacoustic modeling, temporal logic specification, and model checking, our method is able to prove whether a modeled of a configuration of alarms can interact in ways that produce masking. This paper provides the motivation for this method, presents its details, describes its implementation, demonstrates its power with a case study, and outlines future work.
No takes yet. Share an insight, caveat, or question.
Hasanain et al. (2015) studied Medical alarms masking. Computational method using model checking was evaluated on Detection of simultaneous masking in medical alarms. A computational method combining formal modeling, psychoacoustic modeling, and model checking can successfully detect simultaneous masking in medical alarm configurations.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: