Optimization of selective stimulation parameters for multi-contact electrodes

Abstract

Background: Multi-contact stimulating electrodes are gaining acceptance as a means for interfacing with the peripheral nervous system. These electrodes can potentially activate many independent populations of motor units within a single peripheral nerve, but quantifying their recruitment properties and the overlap in stimulation between contacts is difficult and time consuming. Further, current methods for quantifying overlap between contacts are ambiguous and can lead to suboptimal selective stimulation parameters. This study describes a novel method for optimizing stimulation parameters for multi-contact peripheral stimulating electrodes to produce strong, selective muscle contractions. The method is tested with four-contact spiral nerve-cuff electrodes implanted on bilateral femoral nerves of two individuals with spinal cord injury, but it is designed to be extendable to other electrode technologies with higher densities of contacts.

Methods: To optimize selective stimulation parameters for multi-contact electrodes, first, recruitment and overlap are characterized for all contacts within an electrode. Recruitment is measured with the twitch response to single stimulus pulses, and overlap between pairs of contacts is quantified by the deviation in their combined response from linear addition of individual responses. Simple mathematical models are fit to recruitment and overlap data, and a cost function is defined to maximize recruitment and minimize overlap between all contacts.

Results: Results are presented for four-contact nerve-cuff electrodes stimulating bilateral femoral nerves of two human subjects with spinal cord injury. Knee extension moments between 11.6 and 43.2 Nm were achieved with selective stimulation through multiple contacts of each nerve-cuff with less than 10% overlap between pairs of contacts. The overlap in stimulation measured in response to selective stimulation parameters was stable at multiple repeated time points after implantation.

Conclusions: These results suggest that the method described here can provide an automated means of determining stimulus parameters to achieve strong muscle contractions via selective stimulation through multi-contact peripheral nerve electrodes.

Figures

Figure 1

The CWRU spiral nerve-cuff electrode. The CWRU four-contact spiral nerve-cuff electrode was implanted around bilateral femoral nerves to stimulate the knee extensor muscles. Each contact is connected to an independent channel of stimulation.

Figure 2

Recruitment and overlap data, and goodness-of-fit of mathematical models. (a) Recruitment data for a single contact, fit with a Gompertz model. (b) Average R2 and AICc ranking of eight models fit to recruitment data. A higher AICc rank score denotes a better fit. (c) Overlap data for two contacts within a nerve-cuff, fit with a third-order polynomial model. (d) Average R2 and AICc ranking of five models fit to overlap data.

Figure 3

Twitch/tetanic relationship. An example of the relationship between twitch (circles) and tetanic (triangles) recruitment curves. A linear scaling factor is calculated as the ratio of the maxima of these curves.

Figure 4

Optimal selective knee extension moment. Knee extension moments as a result of optimal selective stimulation parameters selected by minimizing the cost function described above. Every pairwise combination of contacts in each electrode had less than 10% overlap.

Figure 5

Stability of overlap in stimulation. Overlap in stimulation between pairs of contacts in four nerve-cuff electrodes implanted in two human subjects. Also shown to the right are means and standard deviations of overlap for each pair of contacts. No mean was statistically greater than 10%.