HIDRA: a hierarchical instrument for distributed real-time analysis of biological signals

The role of computer based techniques in patient monitoring: technical note

In this paper the requirements of Neurophysiology and Neurotraumatology monitoring are analyzed. As a result a set of designated systems were developed by the authors a short description of which is given in the paper. Finally the future perspectives and problems to be faced are briefly described.

A parallel software architecture for building intelligent medical monitors

Intensive care units become more complicated each day as the number of devices developed to monitor various aspects of a patient's status continues to increase. Intelligent monitors attempt to reduce this complexity by interpreting the data and presenting a high level summary to the clinician. We propose an innovative parallel software architecture for constructing intelligent medical monitors: the process trellis. The process trellis is an explicitly parallel structure, and therefore can take advantage of the performance gains available from parallel computing hardware. It does not, however, presuppose any expertise in parallel programming on the part of the application programmer. A prototype cardiovascular monitor has been built using this parallel software architecture. Preliminary testing of the monitor has shown that real-time cardiovascular monitoring, including data calculations, symbolic classification, and interpretation can be accomplished in real-time.

Heterogeneous computer network for real-time hemodynamic signal processing

A computer network is described that allows real-time processing, graphical monitoring and off-line analysis of blood pressure, nervous activity and Doppler signals recorded in conscious rats. Real-time processing is performed by an acquisition station using a powerful microprocessor, allowing extraction and storage of several characteristic parameters from each cardiac cycle and real-time graphical monitoring. The experimenter can thereby follow the time evolution of the hemodynamic parameters. Experimental data are sent through the local network to a workstation that ensures off-line processing such as chronograms, histograms and statistical analyses.

Physiologic trend detection and artifact rejection: a parallel implementation of a multi-state Kalman filtering algorithm

Using a parallel implementation of the multi-state Kalman filtering algorithm, we have developed an accurate method of reliably detecting and identifying trends, abrupt changes, and artifacts from multiple physiologic data streams in real-time. The Kalman filter algorithm was implemented within an innovative software architecture for parallel computation: a parallel process trellis. Examples, processed in real-time, of both simulated and actual data serve to illustrate the potential value of the Kalman filter as a tool in physiologic monitoring.