Uppsala universitet

Parameter Estimation of Human Nerve C-Fibers using
Matched Filtering and Multiple Hypothesis Tracking

Björn Hammarberg (Hansson), Clemens Forster, and Erik Torebjörk

Accepted for publication in IEEE Transactions on Biomedical Engineering.

Longer version: Report, Signals and Systems Group, Uppsala University.

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 persuing 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 APs (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.

Related publications:
Paper version in IEEE Trans. Biomedical Engineering, vol 49, April 2002. SPIE Conference paper on the detection and tracking.
Master thesis on the implementation of the tracking problem.

Paper Report
Paper in PDF format PDF Longer version in PDF format PDF (1335 K),   Postscript (1548 K),
compressed PS (gz) (428 K)

| Related research | Main entry in list of publications |
Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.