An Ultra-Compact Low-Powered Closed-Loop Device for Control of the Neuromuscular System

Neuroprosthetic interfaces require light-weighted and power-optimized systems that combine acquisition and stimulation together with a computational unit capable to perform on-line analysis for closed-loop control. Here, we present an ultra-compact and low-power system able to acquire from 32 channels and stimulate independently using both current and voltage. The system has been validated in vivo for rats in the recording of spontaneous and evoked potentials and peripheral nerve stimulation, and it was tested to reproduce the muscular activity involved in gait. This device has potential application in long-term clinical therapies for the restoration of limb control and it can become a development platform for closed loop algorithms in neuromuscular interfaces.

[1]  G. P. Braz,et al.  Functional Electrical Stimulation Control of Standing and Stepping After Spinal Cord Injury: A Review of Technical Characteristics , 2009, Neuromodulation : journal of the International Neuromodulation Society.

[2]  R. Stein,et al.  Feed forward and feedback control for over-ground locomotion in anaesthetized cats , 2012, Journal of neural engineering.

[3]  C. Azevedo-Coste,et al.  Comparative analysis of transverse intrafascicular multichannel, longitudinal intrafascicular and multipolar cuff electrodes for the selective stimulation of nerve fascicles , 2011, Journal of neural engineering.

[4]  S. Yen,et al.  Polymeric C-shaped cuff electrode for recording of peripheral nerve signal , 2015 .

[5]  K. Ragnarsson Functional electrical stimulation after spinal cord injury: current use, therapeutic effects and future directions , 2008, Spinal Cord.

[6]  L. Fadiga,et al.  Recording High Frequency Neural Signals Using Conformable and Low-Impedance ECoG Electrodes Arrays Coated with PEDOT-PSS-PEG , 2016 .

[7]  W. Durfee,et al.  Methods for estimating isometric recruitment curves of electrically stimulated muscle , 1989, IEEE Transactions on Biomedical Engineering.

[8]  Luigi Raffo,et al.  Peripheral Neural Activity Recording and Stimulation System , 2011, IEEE Transactions on Biomedical Circuits and Systems.

[9]  L. Fadiga,et al.  Brain stimulation and recording with ultra-flexible PEDOT-CNT-coated micro-ECoG electrode arrays , 2017, Brain Stimulation.

[10]  Nitish V. Thakor,et al.  Erratum to: Implantable neurotechnologies: bidirectional neural interfaces—applications and VLSI circuit implementations , 2016, Medical & Biological Engineering & Computing.

[11]  Carlo J. De Luca,et al.  The Use of Surface Electromyography in Biomechanics , 1997 .

[12]  Nitish V. Thakor,et al.  Implantable neurotechnologies: electrical stimulation and applications , 2015, Medical & Biological Engineering & Computing.