An Implementation of the Novacode System for Cardiac Injury Risk Assessment
Advisor Information
Dr. Dongming Peng
Location
MBSC 201
Presentation Type
Poster
Start Date
6-3-2020 9:00 AM
End Date
6-3-2020 10:15 AM
Abstract
The Novacode system developed by Dr. Rautaharju is a system that is used to assess risk of cardiac injury in patients that have no history of cardiac injury. When this system is used, it is capable of assessing an individual’s risk of cardiac injury on a scale from high risk to low risk, with four categories of risk. By implementing this system in Matlab we can create a pre-filtering module that can limit the computational requirements for an electrocardiogram monitoring wireless transmission system with limited embedded resources. To do this, two tests are performed. The first is to take an existing database, with both healthy and unhealthy electrocardiogram recordings, and test the ability for the Novacode system to filter out the healthy recordings. The second is to utilize ECGSYN from PhysioNet to generate randomized synthetic electrocardiogram recordings and test the ability for the Novacode system to filter out the healthy recordings. These two tests will allow us to assess the Novacode as a pre-filter to limit the number of computations required in an embedded electrocardiogram monitoring device.
An Implementation of the Novacode System for Cardiac Injury Risk Assessment
MBSC 201
The Novacode system developed by Dr. Rautaharju is a system that is used to assess risk of cardiac injury in patients that have no history of cardiac injury. When this system is used, it is capable of assessing an individual’s risk of cardiac injury on a scale from high risk to low risk, with four categories of risk. By implementing this system in Matlab we can create a pre-filtering module that can limit the computational requirements for an electrocardiogram monitoring wireless transmission system with limited embedded resources. To do this, two tests are performed. The first is to take an existing database, with both healthy and unhealthy electrocardiogram recordings, and test the ability for the Novacode system to filter out the healthy recordings. The second is to utilize ECGSYN from PhysioNet to generate randomized synthetic electrocardiogram recordings and test the ability for the Novacode system to filter out the healthy recordings. These two tests will allow us to assess the Novacode as a pre-filter to limit the number of computations required in an embedded electrocardiogram monitoring device.