Estimation and detection of the hemodynamic response (HDR) are of great importance in functional MRI (fMRI) data analysis. In this paper, we propose the use of three H∞ adaptive filters (finite memory, exponentially weighted, and time-varying) for accurate estimation and detection of the HDR. The H∞ approach is used because it safeguards against the worst case disturbances and makes no assumptions on the (statistical) nature of the signals [B. Hassibi and T. Kailath, in Proc. ICASSP, 1995, vol. 2, pp.949-952; T. Ratnarajah and S. Puthusserypady, in Proc. 8th IEEE Workshop DSP, 1998, pp. 1483-1487]. Performances of the proposed techniques are compared to the conventional t-test method as well as the well-known LMSs and recursive least squares algorithms. Extensive numerical simulations show that the proposed methods result in better HDR estimations and activation detections.
|Number of pages||10|
|Journal||IEEE Transactions on Biomedical Engineering|
|Publication status||Published - 1 May 2010|
- Activation detection
- Functional MRI (fMRI)
- H filters
- Hemodynamic response (HDR)