On the use of wavelet denoising and spike sorting techniques to process electroneurographic signals recorded using intraneural electrodes

Abstract

Among the possible interfaces with the peripheral nervous system (PNS), intraneural electrodes represent an interesting solution for their potential advantages such as the possibility of extracting spikes from electroneurographic (ENG) signals. Their use could increase the precision and the amount of information which can be detected with respect to other processing methods.In this study, in order to verify this assumption, thin-film longitudinal intrafascicular electrodes (tfLIFE) were implanted in the sciatic nerve of rabbits. Various sensory stimuli were applied to the hind limb of the animal and the elicited ENG signals were recorded using the tfLIFEs. These signals were processed to determine whether the different types of information can be decoded. Signals were wavelet denoised and spike sorted. Support vector machines were trained to use the spike waveforms found to infer the stimulus applied to the rabbit. This approach was also compared with previously used ENG processing methods.The results indicate that the combination of wavelet denoising and spike sorting techniques can increase the amount of information extractable from ENG signals recorded with intraneural electrodes. This strategy could allow the development of more effective closed-loop neuroprostheses and hybrid bionic systems connecting the human nervous system with artificial devices.

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications

“…Other techniques, more specific for PNS signals and based on spike sorting and classification, are more challenging form a computational perspective [7]. Taking into account the final goal of this work, in this paper one of these algorithms has been selected [11]. Originally tested on the animal model to decode afferences, i.e.…”

Decoding Information From Neural Signals Recorded Using Intraneural Electrodes: Toward the Development of a Neurocontrolled Hand Prosthesis

“…More information can be found in [28]. Various sensory stimuli were applied to the hind limb (i.e., ankle flexion/extension, flexion/extension of one or more toes, and stroking of cutaneous receptive fields) and the elicited signals were recorded using the tfLIFEs.…”

“…For each animal, the recording site with best signal to noise ratio was chosen using the automated procedure described in [28].…”

“…For each example, the feature vector was composed of the ratios between the number of spikes matching each template and the total number of spikes in the epoch [28]. Therefore, the absolute spike rates were not used, but rather the relative spike rates of each waveform w.r.t.…”

“…The gray lines (scales on the right) are the absolute spike rate of the corresponding spike waveforms evaluated on 1-s sliding windows. Reproduced with permission from [28].…”