Electrocardiogram (ECG) filtering algorithms for real-time ambulatory applications in harsh environments

The electrical activity of the heart i.e. ECG, can convey a lot of useful information about an individual’s health and psychological states. Wearable devices recording ECG signals can help monitor the physical health of soldiers remotely and help make critical decisions like casualty detection, remote triage, and medical management. However, ECG signal quality from these devices is often poor due to various problems such as sensor or body movement, environmental disturbances etc. In order to improve the signal quality there is a need to develop filtering methods for ECG so that reliable decisions can be made about individuals health even in noisy conditions. Additionally, in order to make medical decisions without any delays, it should not have a lag which puts additional constraints on the kind of filtering methods we can use. Hence there is a need for research in real time filtering method for ECG.

Faculty Supervisor:

Tiago H Falk

Student:

Partner:

Thales Canada Inc

Discipline:

Engineering

Sector:

Health and Related Sciences & Technology; Information and Communications Technology

University:

Université du Québec : Institut national de la recherche scientifique

Program: