Fully Implantable Multi-Channel Measurement System for Acquisition of Muscle Activity

This paper presents intramuscular electromyogram (EMG) signals obtained with a fully implantable measurement system that were recorded during goal directed arm movements. In a first implantation thin film electrodes were epimysially implanted on the deltoideus of a rhesus macaque and the encapsulation process was monitored by impedance measurements. Increase of impedance reached a constant level after four weeks indicating a complete encapsulation of electrodes. EMG recorded with these electrodes yielded a signal-to-noise ratio of about 80 dB at 200 Hz. The EMG recorded during goal-directed arm movements showed a high similarity to movements in the same direction and at the same time presented clear differences between different movement directions in time domain. Six classifiers and seven time and frequency domain features were investigated with the aim of discriminating the direction of arm movement from EMG signals. Reliable recognition of arm movements was achieved for a subset of the movements under investigation only. A second implantation of the whole measurement system for nine weeks demonstrated simple handling during surgery and good biotolerance in the animals.

[1]  Ming-Shaung Ju,et al.  In vivo impedance evaluation of Au/PI microelectrode with surface modulated by alkanethiolate self-assembled monolayers , 2011, Biomedical microdevices.

[2]  Mohsen Mosayebi Samani,et al.  An implantable telemetry system for long-term bio-signal recording , 2010, 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings.

[3]  A. Chan,et al.  Surface Electromyographic Signals Using Dry Electrodes , 2010, IEEE Transactions on Instrumentation and Measurement.

[4]  D T Hutchinson,et al.  Continuous Detection and Decoding of Dexterous Finger Flexions With Implantable MyoElectric Sensors , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[5]  B Hudgins,et al.  Myoelectric signal processing for control of powered limb prostheses. , 2006, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[6]  P. Dario,et al.  Control of multifunctional prosthetic hands by processing the electromyographic signal. , 2002, Critical reviews in biomedical engineering.

[7]  Michael W. Keith,et al.  A surgically-implanted intramuscular electrode for an implantable neuromuscular stimulation system , 1994 .

[8]  Hong-Bo Xie,et al.  Classification of the mechanomyogram signal using a wavelet packet transform and singular value decomposition for multifunction prosthesis control , 2009, Physiological measurement.

[9]  Michael Greenacre,et al.  Biplots in Practice , 2009 .

[10]  Stephanie Westendorff,et al.  Implementation of Spatial Transformation Rules for Goal-Directed Reaching via Gain Modulation in Monkey Parietal and Premotor Cortex , 2009, The Journal of Neuroscience.

[11]  Wenwei Yu,et al.  Preliminary results of online classification of upper limb motions from around-shoulder muscle activities , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[12]  A Searle,et al.  Real time impedance plots with arbitrary frequency components , 1999, Physiological measurement.

[13]  Bruce C. Wheeler,et al.  EMG feature evaluation for movement control of upper extremity prostheses , 1995 .

[14]  S. Micera,et al.  New technologies in manufacturing of different implantable microelectrodes as an interface to the peripheral nervous system , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..

[15]  Anna Jaskólska,et al.  Muscle stiffness at different force levels measured with two myotonometric devices , 2012, Physiological measurement.

[16]  Tom Chau,et al.  Automatic detection of muscle activity from mechanomyogram signals: a comparison of amplitude and wavelet-based methods , 2010, Physiological measurement.

[17]  Stephanie Westendorff,et al.  Acquisition of myoelectric signals to control a hand prosthesis with implantable epimysial electrodes , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[18]  S. Leonhardt,et al.  Characterization of textile electrodes and conductors using standardized measurement setups , 2010, Physiological measurement.

[19]  Dennis C. Tkach,et al.  Study of stability of time-domain features for electromyographic pattern recognition , 2010, Journal of NeuroEngineering and Rehabilitation.

[20]  Wenwei Yu,et al.  A study on classification of upper limb motions from around-shoulder muscle activities , 2009, 2009 IEEE International Conference on Rehabilitation Robotics.

[21]  W. Krautschneider,et al.  Acquisition of muscle activity with a fully implantable multi-channel measurement system , 2012, 2012 IEEE International Instrumentation and Measurement Technology Conference Proceedings.

[22]  D.S. Hedin,et al.  Rechargeable wireless EMG sensor for prosthetic control , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[23]  P. Welch The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms , 1967 .

[24]  Jung Kim,et al.  Optical muscle activation sensors for estimating upper limb force level , 2011, 2011 IEEE International Instrumentation and Measurement Technology Conference.

[25]  R.F. Weir,et al.  The Optimal Controller Delay for Myoelectric Prostheses , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[26]  Patrick van der Smagt,et al.  Surface EMG in advanced hand prosthetics , 2008, Biological Cybernetics.

[27]  Sverre Grimnes,et al.  Bioimpedance and Bioelectricity Basics , 2000 .

[28]  Daryl R Kipke,et al.  Complex impedance spectroscopy for monitoring tissue responses to inserted neural implants , 2007, Journal of neural engineering.

[29]  Hans Dietl,et al.  User demands for sensory feedback in upper extremity prostheses , 2012, 2012 IEEE International Symposium on Medical Measurements and Applications Proceedings.

[30]  Kevin L Kilgore,et al.  Durability of implanted electrodes and leads in an upper-limb neuroprosthesis. , 2003, Journal of rehabilitation research and development.

[31]  Justin C. Sanchez,et al.  Quantifying long-term microelectrode array functionality using chronic in vivo impedance testing , 2012, Journal of neural engineering.

[32]  Desney S. Tan,et al.  Demonstrating the feasibility of using forearm electromyography for muscle-computer interfaces , 2008, CHI.

[33]  E Miraldi,et al.  Impedance spectroscopy of conductive commercial hydrogels for electromyography and electroencephalography. , 2010, Physiological measurement.

[34]  Adrian D. C. Chan,et al.  Flexible dry electrode for recording surface electromyogram , 2010, 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings.

[35]  Levi J. Hargrove,et al.  A Comparison of Surface and Intramuscular Myoelectric Signal Classification , 2007, IEEE Transactions on Biomedical Engineering.

[36]  L J Hargrove,et al.  Determining the Optimal Window Length for Pattern Recognition-Based Myoelectric Control: Balancing the Competing Effects of Classification Error and Controller Delay , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[37]  L. Leija,et al.  Evaluation of electrical impedance of Pt–Ir epimysial electrodes under implantation in muscles , 2002 .

[38]  He Huang,et al.  An Analysis of EMG Electrode Configuration for Targeted Muscle Reinnervation Based Neural Machine Interface , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[39]  R.N. Scott,et al.  A new strategy for multifunction myoelectric control , 1993, IEEE Transactions on Biomedical Engineering.

[40]  Marcelo Haberman,et al.  Insulating electrodes: a review on biopotential front ends for dielectric skin–electrode interfaces , 2010, Physiological measurement.