Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review

Abstract

For those individuals with upper-extremity amputation, a daily normal living activity is no longer possible or it requires additional effort and time. With the aim of restoring their sensory and motor functions, theoretical and technological investigations have been carried out in the field of neuroprosthetic systems. For transmission of sensory feedback, several interfacing modalities including indirect (non-invasive), direct-to-peripheral-nerve (invasive), and cortical stimulation have been applied. Peripheral nerve interfaces demonstrate an edge over the cortical interfaces due to the sensitivity in attaining cortical brain signals. The peripheral nerve interfaces are highly dependent on interface designs and are required to be biocompatible with the nerves to achieve prolonged stability and longevity. Another criterion is the selection of nerves that allows minimal invasiveness and damages as well as high selectivity for a large number of nerve fascicles. In this paper, we review the nerve-machine interface modalities noted above with more focus on peripheral nerve interfaces, which are responsible for provision of sensory feedback. The invasive interfaces for recording and stimulation of electro-neurographic signals include intra-fascicular, regenerative-type interfaces that provide multiple contact channels to a group of axons inside the nerve and the extra-neural-cuff-type interfaces that enable interaction with many axons around the periphery of the nerve. Section Current Prosthetic Technology summarizes the advancements made to date in the field of neuroprosthetics toward the achievement of a bidirectional nerve-machine interface with more focus on sensory feedback. In the Discussion section, the authors propose a hybrid interface technique for achieving better selectivity and long-term stability using the available nerve interfacing techniques.

Effects of HD‐tDCS on Resting‐State Functional Connectivity in the Prefrontal Cortex: An fNIRS Study

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Reduction of Onset Delay in Functional Near-Infrared Spectroscopy: Prediction of HbO/HbR Signals

“…Moreover, the use of q-step-head prediction with improved fitting can help in the hybridization of fNIRS with other rapid modalities such as EEG. Nevertheless, further research is still required to improve the fitting of the predicted fNIRS signals with an accuracy more than 90% using advanced signal processing (Ghafoor et al, 2017;Chen et al, 2018;Hong et al, 2018a) and adaptive algorithms (Iqbal et al, 2018;Nguyen Q. C. et al, 2018). In the future, other types of kernels should also be investigated for further improvement of the predicted fNIRS signals.…”

Application of functional near-infrared spectroscopy in the healthcare industry: A review

“…The understanding of encoding and decoding of neuronal activation is important in developing BCI applications to complement the neural encoding and decoding being used in medical robotics research which use nerve-machine interfaces. [370][371][372][373][374]…”