Literature DB >> 7868148

Multiple site electromyograph amplitude estimation.

E A Clancy1, N Hogan.   

Abstract

Temporal whitening of individual surface electromyograph (EMG) waveforms and spatial combination of multiple recording sites have separately been demonstrated to improve the performance of EMG amplitude estimation. This investigation combined these two techniques by first whitening, then combining the data from multiple EMG recording sites to form an EMG amplitude estimate. A phenomenological mathematical model of multiple sites of the surface EMG waveform, with analytic solution for an optimal amplitude estimate, is presented. Experimental surface EMG waveforms were then sampled from multiple sites during nonfatiguing, constant-force, isometric contractions of the biceps or triceps muscles, over the range of 10-75% maximum voluntary contraction. A signal-to-noise ratio (SNR) was computed from each amplitude estimate (deviations about the mean value of the estimate were considered as noise). Results showed that SNR performance: 1) increased with the number of EMG sites, 2) was a function of the sampling frequency, 3) was predominantly invariant to various methods of determining spatial uncorrelation filters, 4) was not sensitive to the intersite correlations of the electrode configuration investigated, and 5) was best at lower levels of contraction. A moving average root mean square estimator (245-ms window) provided an average +/- standard deviation (A +/- SD) SNR of 10.7 +/- 3.3 for single site unwhitened recordings. Temporal whitening and four combined sites improved the A +/- SD SNR to 24.6 +/- 10.4. On one subject, eight whitened combined sites were achieved, providing an A +/- SD SNR or 35.0 +/- 13.4.

Mesh:

Year:  1995        PMID: 7868148     DOI: 10.1109/10.341833

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


  8 in total

1.  Surface electromyography and mechanomyography recording: a new differential composite probe.

Authors:  B Gregori; E Galié; N Accornero
Journal:  Med Biol Eng Comput       Date:  2003-11       Impact factor: 2.602

2.  Influence of advanced electromyogram (EMG) amplitude processors on EMG-to-torque estimation during constant-posture, force-varying contractions.

Authors:  Edward A Clancy; Oljeta Bida; Denis Rancourt
Journal:  J Biomech       Date:  2005-10-20       Impact factor: 2.712

3.  Customized interactive robotic treatment for stroke: EMG-triggered therapy.

Authors:  Laura Dipietro; Mark Ferraro; Jerome Joseph Palazzolo; Hermano Igo Krebs; Bruce T Volpe; Neville Hogan
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2005-09       Impact factor: 3.802

4.  Two degrees of freedom, dynamic, hand-wrist EMG-force using a minimum number of electrodes.

Authors:  Chenyun Dai; Ziling Zhu; Carlos Martinez-Luna; Thane R Hunt; Todd R Farrell; Edward A Clancy
Journal:  J Electromyogr Kinesiol       Date:  2019-04-16       Impact factor: 2.368

Review 5.  The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury.

Authors:  Morufu Olusola Ibitoye; Eduardo H Estigoni; Nur Azah Hamzaid; Ahmad Khairi Abdul Wahab; Glen M Davis
Journal:  Sensors (Basel)       Date:  2014-07-14       Impact factor: 3.576

6.  Myoelectric Control Performance of Two Degree of Freedom Hand-Wrist Prosthesis by Able-Bodied and Limb-Absent Subjects.

Authors:  Ziling Zhu; Jianan Li; William J Boyd; Carlos Martinez-Luna; Chenyun Dai; Haopeng Wang; He Wang; Xinming Huang; Todd R Farrell; Edward A Clancy
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2022-04-11       Impact factor: 4.528

7.  A Comparative Approach to Hand Force Estimation using Artificial Neural Networks.

Authors:  Farid Mobasser; Keyvan Hashtrudi-Zaad
Journal:  Biomed Eng Comput Biol       Date:  2012-07-30

8.  Automated Channel Selection in High-Density sEMG for Improved Force Estimation.

Authors:  Gelareh Hajian; Ali Etemad; Evelyn Morin
Journal:  Sensors (Basel)       Date:  2020-08-27       Impact factor: 3.576

  8 in total

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