Björn Hammarberg

PhD Thesis, Uppsala University, ISBN 91-506-1551-3, March 2002.

Dissertation in Signal Processing to be publicly examined in room K23, Magistern, Dag Hammarskjölds väg 31, Uppsala on April 26, 2002 at 10.15 a.m.
Faculty Opponent: Prof Dick Stegeman
Dept of Clinical Neurophysiology, University Medical Centre Nijmegen,
The Netherlands.

The thesis available in Pdf.
Contents and Chapter 1 in Pdf (1.5M)

Paper copies of the thesis can be obtained from Ylva Johansson, Signals and Systems Group, Uppsala University, Box 528, SE-75120 Uppsala, Sweden.

Outline:

Overview of the research leading to this thesis.

Abstract:

Signal processing within the neurophysiological field is challenging and requires short processing time and reliable results. In this thesis, three main problems are considered.

First, a modified line source model for simulation of muscle action potentials (APs) is presented. It is formulated in continuous-time as a convolution of a muscle-fiber dependent transmembrane current and an electrode dependent weighting (impedance) function. In the discretization of the model, the Nyquist criterion is addressed. By applying anti-aliasing filtering, it is possible to decrease the discretization frequency while retaining the accuracy. Finite length muscle fibers are incorporated in the model through a simple transformation of the weighting function. The presented model is suitable for modeling large motor units.

Second, the possibility of discerning the individual AP components of the concentric nee-dle electromyogram (EMG) is explored. Simulated motor unit APs (MUAPs) are pre-filtered using Wiener filtering. The mean fiber concentration (MFC) and jitter are esti-mated from the prefiltered MUAPs. The results indicate that the assessment of the MFC may well benefit from the presented approach and that the jitter may be estimated from the concentric needle EMG with an accuracy comparable with traditional single fiber EMG.

Third, automatic, rather than manual, detection and discrimination of recorded C-fiber APs is addressed. The algorithm, detects the APs reliably using a matched filter. Then, the de-tected APs are discriminated using multiple hypothesis tracking combined with Kalman filtering which identifies the APs originating from the same C-fiber. To improve the per-formance, an amplitude estimate is incorporated into the tracking algorithm. Several years of use show that the performance of the algorithm is excellent with minimal need for audit.

Keywords:

Matched filter, asynchronous detection, Kalman filter, initialization, MHT, Wiener deconvolution, line source model, electromyography, needle EMG, motor unit po-tential, MUAP, mean fiber concentration, jitter, microneurography, C-fiber, spike sorting

Related publications:

IEEE Trans BME on fast action potential modeling simulations using the Line Source model, 2004. (pdf).

IEEE Trans BME, on parameter estimation of human nerve C-fibers.

J. Neuroscience, 1999 on attirbutes on C nociceptors in human skin.

Clin. Neurophysiology, 1999 on comparing concentric needle EMG and macro EMG.

SPIE Conference paper on detection and discrimination of action potentials.

Master thesis on the implementation of the detection and discrimination algorithms.