A Signal Processing Approach to Practical Neurophysiology.
A Search for Improved Methods in Clinical Routine and Reseach.
PhD Thesis, Uppsala University,
The thesis available in Postscript :
Contents and Chapter 1
in Pdf (1.5M)
Paper copies of the thesis can be obtained from
Signals and Systems Group, Uppsala University,
Box 528, SE-75120 Uppsala, Sweden.
Overview of the research leading to this thesis.
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.
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
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.
on the implementation of the detection and discrimination algorithms.