Digital spectral analysis: with applications
Digital spectral analysis: with applications
Estimation of parameters and eigenmodes of multivariate autoregressive models
ACM Transactions on Mathematical Software (TOMS)
ACM Transactions on Mathematical Software (TOMS)
A comparison of multivariate autoregressive estimators
Signal Processing - Signal processing in UWB communications
Transmission of patient vital signs using wireless body area networks
Mobile Networks and Applications - Special issue on Wireless and Personal Communications
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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.