Preliminary Results of Branch Level, Brachial Plexus Peripheral Nerve Stimulation on a Non-Human Primate.

Restoring functional hand control is a priority for those suffering from neurological impairments. Functional electrical stimulation (FES) is commonly applied to assist with rehabilitation. However, FES applied intramuscularly typically results in complex surgeries requiring many implants. This paper presents the preliminary findings from a feasibility study focused on evaluating the potential to access the upper extremity peripheral nerves through a single surgical approach (axillary approach). A single Japanese macaque (macaca fuscata) monkey was used to validate the feasibility of this study. Four of the five peripheral nerves which control the upper extremity were exposed, and had multi-contact epineural cuffs implanted: median, radial, ulnar and musculocutaneous. The axillary nerve was not accessible for epineural cuff placement with the current surgical approach used in this study. Electrical stimuli were used to produce movement contraction patterns of muscles relevant to the innervated peripheral nerves. In addition, to assist in quantifying the outcome, evoked potentials were simultaneously recorded from five extrinsic forearm flexors during median nerve stimulation. This feasibility study demonstrated that the axillary approach enables electrode placement to four of the five peripheral nerves required for upper extremity control through a single skin incision.Clinical relevance- This study demonstrated that the electrode placement to most of the peripheral nerves that control the arm and hand can be done by a single surgical approach: axillary approach.

Electrode-Skin Impedance Model Parameter Estimation in the Frequency-Domain.

This paper presents a method for identifying parameter values for a double parallel resistor/constant-phase-element model of the electrode-skin interface for individual silver and silver/silver chloride electrodes. The impedance of each electrode was measured in five from 1 Hz-10 kHz. Phase features of these data were used to guide initial estimates for parameter values which were refined using a least squares algorithm. Resultant model impedances were compared with experimental data across a typical biosignal bandwidth (1 Hz-500 Hz). The method was effective in estimating component values in most datasets, and resulted in a mean relative RMS error of 7 % (σ = 8.3%) across the biosignal bandwidth.Clinical relevance- This work establishes a feature-based method for finding component parameter estimates for an electrode contact impedance model.

Low-cost stimulation resistant electromyography.

Surface Electromyography (sEMG) is the non-invasive measurement of skeletal muscle contraction bio-potentials. Measuring sEMG of a stimulated muscle can prove particularly difficult due to large scale and long lasting stimulation-induced artefacts: if an sEMG device does not account for such artefacts, its measurements can be swamped and components damaged. sEMG has been used in a wide range of clinical and biomedical fields, providing measures such as muscular fatigue and subject intent. The recording of sEMG can prove difficult due to signal contamination such as movement artefact and mains interference. There are very few commercial sEMG devices that contain protection against large stimulation voltages or measures to reduce artefact transient times. Furthermore, most commercial or research level designs are not open source; these designs are effectively an inflexible black box to researchers and developers. This research presents the design, test and validation of an open source sEMG design, able to record muscle bio-potentials concurrently to electrical stimulation. The open source, low-cost nature of the design provides accessibility to researchers without the time and cost associated with design development. The design has been tested on the forearms of four able-bodied subjects during 25 Hz constant current stimulation, and has been shown to record subject volitional sEMG and M-wave without saturation.

Data captured using low-cost active electromyography.

Surface electromyography (sEMG) data was captured for three able-body subjects, from their right biceps brachii using the POLE sensor outlined in "Low-cost active electromyography" [1]. Data was captured for 45 seconds per subject, resulting in 12-21 contractions per subject. The raw data files, along with a sinusoidal waveform have been provided. This allows users of the POLE sensor to verify their low-cost sEMG device has been populated and configured correctly. This data also allows researchers/developers to compare their results against this low-cost, low noise sEMG device. The frequency content of the raw sEMG data is also of interest; this is calculated by applying a fast Fourier transform (FFT). The process applied to perform these algorithms is supplied in a MATLAB script.