This paper introduces a novel, open-source middleware framework for communication with medical devices and an application using the middleware named intensive care window (ICW). The middleware enables communication with intensive care unit bedside-installed medical devices over standard and proprietary communication protocol stacks. The ICW application facilitates the acquisition of vital signs and physiological parameters exported from patient-attached medical devices and sensors. Moreover, ICW provides runtime and post-analysis procedures for data annotation, data visualization, data query, and analysis. The ICW application can be deployed as a stand-alone solution or in conjunction with existing clinical information systems providing a holistic solution to inpatient medical condition monitoring, early diagnosis, and prognosis.

Intensive Care Units are widely considered as the most technologically advanced environments within a hospital. In such environments, physicians are confronted with multiple medical devices that monitor the inpatients. The capability to collect, store, process, and share inpatient monitoring data along with the remarks of the treating physicians can bring tremendous benefits to all aspects of Intensive Care Medicine (practice, research, education). The IC-Window makes it feasible for physicians to extract, view, store, and replay Clinically Interesting Episodes through simple, intuitive user interfaces.

Research on fingerprint classification has primarily focused on finding improved classifiers, image and feature enhancement, and less on the development of novel fingerprint representations. Using an AM-FM representation for each fingerprint, we obtain significant gains in classification performance as compared to the commonly used National Institute of Standards system, for the same classifier.