Literature DB >> 19224729

Implantable myoelectric sensors (IMESs) for intramuscular electromyogram recording.

Richard F ff Weir1, Phil R Troyk, Glen A DeMichele, Douglas A Kerns, Jack F Schorsch, Huub Maas.   

Abstract

We have developed a multichannel electrogmyography sensor system capable of receiving and processing signals from up to 32 implanted myoelectric sensors (IMES). The appeal of implanted sensors for myoelectric control is that electromyography (EMG) signals can be measured at their source providing relatively cross-talk-free signals that can be treated as independent control sites. An external telemetry controller receives telemetry sent over a transcutaneous magnetic link by the implanted electrodes. The same link provides power and commands to the implanted electrodes. Wireless telemetry of EMG signals from sensors implanted in the residual musculature eliminates the problems associated with percutaneous wires, such as infection, breakage, and marsupialization. Each implantable sensor consists of a custom-designed application-specified integrated circuit that is packaged into a biocompatible RF BION capsule from the Alfred E. Mann Foundation. Implants are designed for permanent long-term implantation with no servicing requirements. We have a fully operational system. The system has been tested in animals. Implants have been chronically implanted in the legs of three cats and are still completely operational four months after implantation.

Entities:  

Mesh:

Year:  2009        PMID: 19224729      PMCID: PMC3157946          DOI: 10.1109/TBME.2008.2005942

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  22 in total

1.  Muscle activity in rapid multi-degree-of-freedom elbow movements: solutions from a musculoskeletal model.

Authors:  R V Gonzalez; L D Abraham; R E Barr; T S Buchanan
Journal:  Biol Cybern       Date:  1999-05       Impact factor: 2.086

2.  Performances of hill-type and neural network muscle models-toward a myosignal-based exoskeleton.

Authors:  J Rosen; M B Fuchs; M Arcan
Journal:  Comput Biomed Res       Date:  1999-10

Review 3.  The extraction of neural strategies from the surface EMG.

Authors:  Dario Farina; Roberto Merletti; Roger M Enoka
Journal:  J Appl Physiol (1985)       Date:  2004-04

4.  A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control.

Authors:  Abidemi Bolu Ajiboye; Richard F ff Weir
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2005-09       Impact factor: 3.802

5.  Simulation of intramuscular EMG signals detected using implantable myoelectric sensors (IMES).

Authors:  Madeleine M Lowery; Richard F ff Weir; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2006-10       Impact factor: 4.538

6.  Pattern-recognition arm prosthesis: a historical perspective-a final report.

Authors:  R W Wirta; D R Taylor; F R Finley
Journal:  Bull Prosthet Res       Date:  1978

7.  Experience with Swedish multifunctional prosthetic hands controlled by pattern recognition of multiple myoelectric signals.

Authors:  C Almström; P Herberts; L Körner
Journal:  Int Orthop       Date:  1981       Impact factor: 3.075

8.  Intramuscular electrical stimulation: tissue damage.

Authors:  J T Mortimer; D Kaufman; U Roessman
Journal:  Ann Biomed Eng       Date:  1980       Impact factor: 3.934

9.  Real-time myoprocessors for a neural controlled powered exoskeleton arm.

Authors:  Ettore E Cavallaro; Jacob Rosen; Joel C Perry; Stephen Burns
Journal:  IEEE Trans Biomed Eng       Date:  2006-11       Impact factor: 4.538

10.  A comparison of the effects of electrode implantation and targeting on pattern classification accuracy for prosthesis control.

Authors:  Todd R Farrell; Richard F Ff Weir
Journal:  IEEE Trans Biomed Eng       Date:  2008-09       Impact factor: 4.538

View more
  51 in total

1.  Real-time simultaneous and proportional myoelectric control using intramuscular EMG.

Authors:  Lauren H Smith; Todd A Kuiken; Levi J Hargrove
Journal:  J Neural Eng       Date:  2014-11-14       Impact factor: 5.379

2.  Electromyogram-based neural network control of transhumeral prostheses.

Authors:  Christopher L Pulliam; Joris M Lambrecht; Robert F Kirsch
Journal:  J Rehabil Res Dev       Date:  2011

3.  Novel postural control algorithm for control of multifunctional myoelectric prosthetic hands.

Authors:  Jacob L Segil; Richard F Weir
Journal:  J Rehabil Res Dev       Date:  2015

4.  Activation of individual extrinsic thumb muscles and compartments of extrinsic finger muscles.

Authors:  J Alexander Birdwell; Levi J Hargrove; Todd A Kuiken; Richard F Ff Weir
Journal:  J Neurophysiol       Date:  2013-06-26       Impact factor: 2.714

5.  Dexterous control of a prosthetic hand using fine-wire intramuscular electrodes in targeted extrinsic muscles.

Authors:  Christian Cipriani; Jacob L Segil; J Alex Birdwell; Richard F ff Weir
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2014-01-21       Impact factor: 3.802

6.  Comparison of surface and intramuscular EMG pattern recognition for simultaneous wrist/hand motion classification.

Authors:  Lauren H Smith; Levi J Hargrove
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2013

7.  Toward the Bionic Face: A Novel Neuroprosthetic Device Paradigm for Facial Reanimation Consisting of Neural Blockade and Functional Electrical Stimulation.

Authors:  Nate Jowett; Robert E Kearney; Christopher J Knox; Tessa A Hadlock
Journal:  Plast Reconstr Surg       Date:  2019-01       Impact factor: 4.730

8.  Myoelectric Control System and Task-Specific Characteristics Affect Voluntary Use of Simultaneous Control.

Authors:  Lauren H Smith; Todd A Kuiken; Levi J Hargrove
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-03-06       Impact factor: 3.802

9.  Extrinsic finger and thumb muscles command a virtual hand to allow individual finger and grasp control.

Authors:  J Alexander Birdwell; Levi J Hargrove; Richard F ff Weir; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2014-07-31       Impact factor: 4.538

10.  Use of probabilistic weights to enhance linear regression myoelectric control.

Authors:  Lauren H Smith; Todd A Kuiken; Levi J Hargrove
Journal:  J Neural Eng       Date:  2015-11-23       Impact factor: 5.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.