Walid Ali

Identifying artifacts in arterial blood pressure using morphogram variability

In this article we present a simple technique that utilizes the cross correlations between ECG signals and haemodynamic signals for the purpose of assessing signal quality and detecting artifacts in the arterial blood pressure (ABP) signal. The technique was tested using cases from a physician-annotated patient monitoring signal database from Beth IsraeUHarvard-MIT University data bank. The results were encouraging: 90% of the manually annotated artifacts were correctly classified as artifacts and 99% of the manually annotated true events were correctly classified (out of a tQtd Of 683 manualiy annotated alarms).

Memetic Optimization of Video Chain Designs

Improving image quality is the backbone of highly competitive display industry. Contemporary video processing system design is a challenging optimization problem. Generally, several video algorithms must be sequentially applied to real-time video data. Overall image quality depends on the nonlinear interactions between multiple design parameters: variable settings for each module (algorithm), the amount of data being transferred in the video processing chain as well as the order of the cascading modules. Unfortunately, no systematic techniques are currently available to configure the video chain without lengthy trial and error process. We propose a rapid and reliable method for optimization of composite video processing systems based on genetic algorithm coupled with local search heuristics. Video system configuration is evolved toward the best image quality, driven by an objective video quality metric. We analyze several local search approaches, including hill-climbing, simplex and estimation-of-distribution algorithms. Experimental study demonstrates superior performance of memetic strategies over the conventional genetic algorithm. We obtain novel and practical video chain solutions that are typically not attainable by regular design process.