Body sensor networks based sensor fusion for cardiovascular biosignal predictions
Document Type
Conference Proceeding
Publication Date
12-1-2008
Abstract
A Multivariate Autoregressive (MAR) model based sensor fusion technique is developed in this work to improve the reliability and accuracy of cardiovascular biosignal prediction by taking advantages of combining sensory data from heterogeneous biosensors in a network. The importance and potential applications of sensor fusion in body sensor networks are introduced. Real-world data from MIT-BIH multi-parameter database MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) is used to verify the MAR model performance. The effects of model order number and involved biosignal number are studied. The experiments also show that ECG signals can be partially recovered from other biosignals even if the ECG input is completely missing. Copyright 2008 ACM.
Publication Title
Proceedings of the 2nd International Workshop on Systems and Networking Support for Health Care and Assisted Living Environments, HealthNet'08
Recommended Citation
Li, H.,
&
Tan, J.
(2008).
Body sensor networks based sensor fusion for cardiovascular biosignal predictions.
Proceedings of the 2nd International Workshop on Systems and Networking Support for Health Care and Assisted Living Environments, HealthNet'08.
http://doi.org/10.1145/1515747.1515752
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/12495