Biomedical subjects

M I Oppenheim

Publications and source records attributed to M I Oppenheim.

4 recordsLinked to original sources

PubMed2000

Design of a clinical alert system to facilitate development, testing, maintenance, and user-specific notification.

Creation and maintenance of electronic clinical alerts within a hospital's electronic medical record (EMR) or database poses a number of challenges. Development can require significant programming effort. Final testing should ideally be performed in a real clinical environment without clinician notification, which may create technical challenges. After an alert is in production, modifications may become necessary in response clinician feedback, changes in clinical factors, or technical issues. Changes may be required in the knowledge base utilized by the alert or in the presentation of the alert condition to the clinicians. Occasionally, different users within the clinical environment may wish to have the same alert data presented differently. We have developed a strategy which allows development of multi-functional alerts and facilitates modification of alert function and/or presentation with minimal to no programming effort. Some elements of this scheme may be appropriate for incorporation into clinical alerting standards.

Artificial Intelligence↗

PubMed1995

An innovative dicrotic notch detection algorithm which combines rule-based logic with digital signal processing techniques.

Automated, real-time localization of the dicrotic notch, a component of the arterial pressure waveform, represents a deceptively complex problem in computerized biomedical signal processing. The high-frequency nature of the notch can make it difficult to distinguish from artifactual noise or from other high-frequency physiological components of the waveform. In addition, the contour of the notch varies with vascular status and with propagation through arterial beds, requiring any detection algorithm to recognize various possible notch conformations. Finally, location of the notch along the waveform may vary widely depending on other hemodynamic variables, further complicating detection algorithms. We have reviewed various published algorithms and have implemented a number of them to determine the strengths and shortcomings of each. We then developed a reliable and accurate hybrid algorithm which utilizes the strengths of the various algorithmic approaches reviewed; after analyzing the waveform, the algorithm selects the most appropriate method for accurate notch localization based on a series of waveform features. The application of rule-based logic represents a relatively unique approach to digital signal processing.

Algorithms↗

PubMed1992

BIO-SPEAD: a parallel computing environment to accelerate development of biologic signal processing algorithms.

We have created BIO-SPEAD (pronounced speed), a BIOlogical Signal Processing Environment for Algorithm Development. BIO-SPEAD is designed to accelerate development of complex algorithms which integrate information derived from single or multiple physiologic waveforms. BIO-SPEAD currently performs all of the basic analyses of several arterial blood pressure waveforms, and allows the user to utilize the results of those low-level analyses for development of more complex algorithms. We utilized a parallel programming architecture called the Process Trellis which keeps the different tasks, or processes, within BIO-SPEAD independent of each other. Additionally, we have developed a graphics interface to enable the user to visualize the waveform under analysis, the low-level system analysis, and the internal workings of the algorithm under development. The system has been used for several algorithm development projects and has demonstrated its utility.

Algorithms↗

PubMed1991

A parallel computing interface to facilitate development of physiologic signal processing algorithms.

We have created a system to aid in the development of algorithms related to the blood pressure waveform. The system performs all of the basic analyses of the waveform, and allows the user to utilize the results of those analyses for the algorithm under development. We have used a parallel programming architecture which keeps the different tasks, or processes, within the system independent of each other. Additionally, we have developed a graphics interface to enable the user to visualize the waveform, the system analysis, and the internal workings of the algorithm under development.

Algorithms↗