Accession Number:

ADA619033

Title:

Predicting Electrocardiogram and Arterial Blood Pressure Waveforms with Different Echo State Network Architectures

Descriptive Note:

Conference paper

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC

Personal Author(s):

• Fong, Allan
• Mittu, Ranjeev
• Ratwani, Raj
• Reggia, James

Report Date:

2014-11-01

Pagination or Media Count:

11.0

Abstract:

Alarm fatigue caused by false alarms and alerts is an extremely important issue for the medical staff in Intensive Care Units. The ability to predict electrocardiogram and arterial blood pressure waveforms can potentially help the staff and hospital systems better classify a patients waveforms and subsequent alarms. This paper explores the use of Echo State Networks, a specific type of neural network for mining, understanding, and predicting electrocardiogram and arterial blood pressure waveforms. Several network architectures are designed and evaluated. The results show the utility of these echo state networks, particularly ones with larger integrated reservoirs, for predicting electrocardiogram waveforms and the adaptability of such models across individuals. The work presented here offers a unique approach for understanding and predicting a patients waveforms in order to potentially improve alarm generation. We conclude with a brief discussion of future extensions of this research.

Descriptors:

• *BLOOD PRESSURE
• *ELECTROCARDIOGRAPHY
• *FALSE ALARMS
• *NETWORK ARCHITECTURE
• *TIME SERIES ANALYSIS
• ADAPTERS
• BIOMEDICAL INFORMATION SYSTEMS
• CHAOS
• CLASSIFICATION
• CLINICAL MEDICINE
• DECISION MAKING
• INTENSIVE CARE UNITS
• LEARNING MACHINES
• MATHEMATICAL PREDICTION
• MEDICAL SUPPLIES
• MONITORING
• NEURAL NETS
• PATIENTS
• PHYSIOLOGICAL EFFECTS
• TRAUMA
• WAVEFORMS

Subject Categories:

• Anatomy and Physiology
• Medicine and Medical Research
• Biomedical Instrumentation and Bioengineering

Distribution Statement:

APPROVED FOR PUBLIC RELEASE