Parameter Estimation of Human Nerve C-Fibers
using Matched Filtering and Multiple Hypothesis Tracking
(University of Erlangen)
IEEE Transactions Biomedical Engineering,
vol. 49, pp- 329-336, April 2002.
© 2002 IEEE
We describe how multiple-target tracking may be used to
estimate conduction velocity changes and
recovery constants of human nerve C-fibers.
These parameters discriminate different types of C-fibers and
pursuing this may promote new insights into
differential properties of nerve fiber membranes. Action
potentials (APs) were recorded from C-fibers
in the peroneal nerve of awake human subjects.
The APs were detected by a matched filter constituting a
maximum-likelihood constant false-alarm rate detector.
Using the multiple-hypothesis tracking method and
Kalman filtering, the detected AN (targets) in each trace
(scan) were associated to individual
nerve fibers (tracks) by their typical conduction latencies in response
to electrical stimulation.
The measurements were one-dimensional (range only)
and the APs were spaced in
time with intersecting trajectories.
In general, the AP amplitude of each C-fiber differed for different fibers.
Amplitude estimation was therefore
incorporated into the tracking algorithm to improve the performance.
The target trajectory was modeled as an exponential
decay with three unknowns. These parameters were
estimated iteratively by applying the simplex
method on the parameters that enter nonlinearly and the least
squares method on the parameters that enter linearly.
PhD Thesis by Björn Hammarberg.
on the implementation of the detection and discrimination algorithms.
SPIE Conference paper
on detection and discrimination of action potentials.
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