Abstract
Cricothyrotomy is a life-saving procedure performed when an airway cannot be established through less invasive techniques. One of the main challenges of the research community in this area consists in designing and building a low-cost simulator that teaches essential anatomy, and providing a method of data collection for performance evaluation and guided instruction as well.
In this paper, we present a framework designed and developed for activity detection in the medical context. More in details, it first acquires data in real time from a cricothyrotomy simulator, when used by medical doctors, then it stores the acquired data into a scientific database and finally it exploits an Activity Detection Engine for finding expected activities, in order to evaluate the medical doctors’ performances in real time, that is very essential for this kind of applications. In fact, an incorrect use of the simulator promptly detected can save the patient’s life. The conducted experiments using real data show the approach efficiency and effectiveness. Eventually, we also received positive feedbacks by the medical personnel who used our prototype.
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- 1.
\(v_i\) refers both to the node \(v_i\) in A and the action symbol \(s_i\) labeling it.
- 2.
All experiments presented in this Section were conducted on a machine running Mac OS X 10.9.1, and mounting a 2 GHz Intel Core i7 processor with a 8 GB, 1600 MHz DDR3.
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D’Auria, D., Persia, F. (2015). A Framework for Real-Time Evaluation of Medical Doctors’ Performances While Using a Cricothyrotomy Simulator. In: Helfert, M., Holzinger, A., Belo, O., Francalanci, C. (eds) Data Management Technologies and Applications. DATA 2014. Communications in Computer and Information Science, vol 178. Springer, Cham. https://doi.org/10.1007/978-3-319-25936-9_12
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