Modeling Fetal Heart Rate and Fetal Circulation during Labor

Recent progress in the development of computer algorithms for detecting pathological changes in fetal heart rate (FHR) variability (fHRV) and electroencephalogram (EEG) points to a potentially groundbreaking technology for detecting fetal acidemia and inflammation during labour. Using FHR and EEG as a diagnostic tool is an attractive option because they can be acquired noninvasively. Despite its promises, however, the current methodology has limitations. In this project, we aim to develop a computational model that can be used to gain insight into the physiological connection between fHRV and EEG variability. One of the challenges for a purely statistical approach is the inability to distinguish correlated processes from coupled processes. Another important feature of the current problem is the non-stationary nature of the data as the underlying processes are highly dynamic. Our model will provide guidance for identification of the relationship between fHRV and EEG, which will promote building next generation algorithms.

Faculty Supervisor:

Huaxiong Huang

Student:

Partner:

Therapeutic Monitoring Systems Inc (Ottawa, ON);NeuroDevNet

Discipline:

Life Sciences

Sector:

Professional, scientific and technical services

University:

York University

Program: