Application of optimal multichannel filtering to simulated nerve signals.
The optimal linear filters derived in the preceding paper can be thoroughly evaluated using computer simulations, based on the properties of mammalian sensory and motor nerve fibres. Using reasonable values for action potential waveforms, conduction velocity and electrode noise, good separation of motor and sensory signals can be obtained. The performance of the filters is degraded by 1) increasing the electrode noise, 2) introducing dispersion in the conduction velocities, or 3) variation in the waveform of the action potentials from that used in designing the filters. However, the variations needed to seriously degrade performance are quite large compared to those which are likely to be present in mammalian nerves. Use of these filters to distinguish different classes of sensory (or motor) signals based on conduction velocity is discussed.
D000200:Action Potentials; D000818:Animals; D002415:Cats; D004566:Electrodes; D004582:Electronics, Medical / Q000295:instrumentation; D005374:Filtration; D008959:Models, Neurological; D009046:Motor Neurons / Q000502:physiology*; D009412:Nerve Fibers / Q000502:physiology*; D009431:Neural Conduction; D011984:Sensory Receptor Cells / Q000502:physiology*; D009435:Synaptic Transmission