In nerve cuff electrode recordings of neural signals, the pick-up of interfering signals can be reduced by choosing appropriate cuff configurations. In the traditionally used tripolar configuration, short circuiting of the end electrodes is expected to reduce the field inside the cuff from interfering signals. A model study suggests that moving the end electrodes toward the center of the cuff reduces the pick-up of interfering signals. In this paper, these properties are studied in more detail using a rabbit model. In addition, a new cuff configuration is suggested, which has an additional set of short circuited end electrodes. The total improvement of signal-to-noise ratio in the new configuration as compared with the traditionally used tripolar configuration was 73% for muscle signals and 127% for the stimulus pulse.

When a nerve cuff electrode is used for the recording of signals from peripheral nerves, cuff dimensions have to be chosen. Traditionally, the peak-to-peak amplitude of the single-fiber action potential (SFAP) is optimized through the choice of cuff diameter and cuff length. In this paper, the dependency of the root-mean-square (RMS) value of the nerve signal on the cuff dimensions was studied and compared with the peak-to-peak value of the SFAP. A simple approximation for signal optimization by cuff dimensioning is suggested. The results were obtained from modeled SFAPs and from the electroneurogram (ENG) created by superimposed SFAPs, obtained from an inhomogeneous volume conductor model. The results show that the RMS value of the nerve signal is considerably more sensitive to the cuff length than the SFAP peak-to-peak amplitude, and that the RMS of the ENG is a linear function of the fiber diameter.

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New designs of cuff electrodes for the recording of signals from peripheral nerves are typically tested in acute animal experiments before long-term evaluation takes place. A reproducible, cost-effective and fast method is presented for evaluating cuff electrodes with respect to signal amplitude, noise rejection, and, in some cases, selectivity, as an alternative to acute in vivo experiments. Comparisons with a computer model and with signals obtained from rabbit tibial nerve give good agreement with the new method. It is shown that an imperfect closure of the cuff around the nerve can easily lead to more than 50% loss of the signal amplitude. Noise from sources external to the cuff is not significantly affected by the closing mechanism, but is strongly reduced by a tripolar cuff configuration as compared with a monopolar one (reduction factor 2.8 to 58, mean = 6.5, n = 6). In dual-channel cuffs, cross-talk is below 1.2% indicating a very high selectivity.

Recordings of neural information for use as feedback in functional electrical stimulation are often contaminated with interfering signals from muscles and from stimulus pulses. The cuff electrode used for the neural recording can be optimized to improve the S/I ratio. In this work, we evaluate a model of both the nerve signal and the interfering signals recorded by a cuff, and subsequently use this model to study the signal to interference ratio of different cuff designs and to evaluate a recently introduced short-circuited tripolar cuff configuration. The results of the model showed good agreement with results from measurements in rabbits and confirmed the superior performance of the short-circuited tripolar configuration as compared with the traditionally used tripolar configuration.

In this paper, information about stance related skin contact forces was extracted from nerve cuff electrode recordings of human neural signals. Forces measured under the heel during standing were scaled and applied to the innervation area of the sural nerve on the side of the foot using a hand held force probe. The neural response to the stimuli was measured with a cuff chronically implanted around the sural nerve in one hemiplegic person. An artificial neural network was used for extraction of the applied force from the recorded nerve signal. The results showed that it is possible to extract information about absolute skin contact forces from the nerve signal with an average goodness of fit of 69.3% for all trials and 82.2% for the more dynamic trials. This information may be applicable as feedback signal in control of standing.

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