Literature DB >> 8724170

Neural signals for command control and feedback in functional neuromuscular stimulation: a review.

J A Hoffer1, R B Stein, M K Haugland, T Sinkjaer, W K Durfee, A B Schwartz, G E Loeb, C Kantor.   

Abstract

In current functional neuromuscular stimulation systems (FNS), control and feedback signals are usually provided by external sensors and switches, which pose problems such as donning and calibration time, cosmesis, and mechanical vulnerability. Artificial sensors are difficult to build and are insufficiently biocompatible and reliable for implantation. With the advent of methods for electrical interfacing with nerves and muscles, natural sensors are being considered as an alternative source of feedback and command signals for FNS. Decision making methods for higher level control can perform equally well with natural or artificial sensors. Recording nerve cuff electrodes have been developed and tested in animals and demonstrated to be feasible in humans for control of dorsiflexion in foot-drop and grasp in quadriplegia. Electromyographic signals, being one thousand times larger than electroneurograms, are easier to measure but have not been able to provide reliable indicators (e.g., of muscle fatigue) that would be useful in FNS systems. Animal studies have shown that information about the shape and movement of arm trajectories can be extracted from brain cortical activity, suggesting that FNS may ultimately be directly controllable from the central nervous system.

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Year:  1996        PMID: 8724170

Source DB:  PubMed          Journal:  J Rehabil Res Dev        ISSN: 0748-7711


  10 in total

Review 1.  Dynamic principles of gait and their clinical implications.

Authors:  Arthur D Kuo; J Maxwell Donelan
Journal:  Phys Ther       Date:  2009-12-18

2.  Probabilistic modeling of selective stimulation of the human sciatic nerve with a flat interface nerve electrode.

Authors:  Matthew A Schiefer; Dustin J Tyler; Ronald J Triolo
Journal:  J Comput Neurosci       Date:  2012-01-06       Impact factor: 1.621

3.  Point-process analysis of neural spiking activity of muscle spindles recorded from thin-film longitudinal intrafascicular electrodes.

Authors:  Luca Citi; Milan Djilas; Christine Azevedo-Coste; Ken Yoshida; Emery N Brown; Riccardo Barbieri
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

4.  Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces.

Authors:  Silvestro Micera; Paolo M Rossini; Jacopo Rigosa; Luca Citi; Jacopo Carpaneto; Stanisa Raspopovic; Mario Tombini; Christian Cipriani; Giovanni Assenza; Maria C Carrozza; Klaus-Peter Hoffmann; Ken Yoshida; Xavier Navarro; Paolo Dario
Journal:  J Neuroeng Rehabil       Date:  2011-09-05       Impact factor: 4.262

5.  Spike sorting of muscle spindle afferent nerve activity recorded with thin-film intrafascicular electrodes.

Authors:  Milan Djilas; Christine Azevedo-Coste; David Guiraud; Ken Yoshida
Journal:  Comput Intell Neurosci       Date:  2010-03-30

6.  An animal model of functional electrical stimulation: evidence that the central nervous system modulates the consequences of training.

Authors:  M A Hook; J W Grau
Journal:  Spinal Cord       Date:  2007-08-14       Impact factor: 2.772

Review 7.  On the viability of implantable electrodes for the natural control of artificial limbs: review and discussion.

Authors:  Max Ortiz-Catalan; Rickard Brånemark; Bo Håkansson; Jean Delbeke
Journal:  Biomed Eng Online       Date:  2012-06-20       Impact factor: 2.819

8.  Effectiveness of supplemental grasp-force feedback in the presence of vision.

Authors:  M Zafar; C L Van Doren
Journal:  Med Biol Eng Comput       Date:  2000-05       Impact factor: 3.079

Review 9.  Restoration of motor function following spinal cord injury via optimal control of intraspinal microstimulation: toward a next generation closed-loop neural prosthesis.

Authors:  Peter J Grahn; Grant W Mallory; B Michael Berry; Jan T Hachmann; Darlene A Lobel; J Luis Lujan
Journal:  Front Neurosci       Date:  2014-09-17       Impact factor: 4.677

10.  Multiunit Activity-Based Real-Time Limb-State Estimation from Dorsal Root Ganglion Recordings.

Authors:  Sungmin Han; Jun-Uk Chu; Hyungmin Kim; Jong Woong Park; Inchan Youn
Journal:  Sci Rep       Date:  2017-03-09       Impact factor: 4.379

  10 in total

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