Surface Electrode Placement and Upper Trapezius

2002 ◽  
Vol 4 (2) ◽  
pp. 50-53 ◽  
Author(s):  
Susan R. Mercer
1987 ◽  
Vol 64 (3) ◽  
pp. 719-724 ◽  
Author(s):  
Herbert F. Schliesser

Changes in electromyography (EMG) accompanying changes in voice quality are reported. Audio recordings were obtained from four normal speakers during production of sustained vowels, counting and reading. These were uttered first in a normal voice and then in a voluntarily produced harsh voice. Perceptual ratings of voice quality of these utterances were made and compared to averaged EMG values obtained during the productions. The surface electrode placement remained unchanged over each of the cricothyroid areas for both normal and harsh voice. For one of the speakers, changes in EMG paralleled changes in vocal quality. For the other three, changes in EMG were variable, and sometimes minimal, in comparison to changes in voice. The results are discussed in relation to the clinical use of EMG for voice disorders.


2011 ◽  
Vol 44 (4) ◽  
pp. 525-530 ◽  
Author(s):  
Andrea J. Boon ◽  
Peter W. Bailey ◽  
Jay Smith ◽  
Eric J. Sorenson ◽  
C. Michel Harper ◽  
...  

Author(s):  
Hendrik Adriaan Dewald ◽  
Platon Lukyanenko ◽  
Joris M. Lambrecht ◽  
James Robert Anderson ◽  
Dustin J. Tyler ◽  
...  

Abstract Background Modern prosthetic hands are typically controlled using skin surface electromyographic signals (EMG) from remaining muscles in the residual limb. However, surface electrode performance is limited by changes in skin impedance over time, day-to-day variations in electrode placement, and relative motion between the electrodes and underlying muscles during movement: these limitations require frequent retraining of controllers. In the presented study, we used chronically implanted intramuscular electrodes to minimize these effects and thus create a more robust prosthetic controller. Methods A study participant with a transradial amputation was chronically implanted with 8 intramuscular EMG electrodes. A K Nearest Neighbor (KNN) regression velocity controller was trained to predict intended joint movement direction using EMG data collected during a single training session. The resulting KNN was evaluated over 12 weeks and in multiple arm posture configurations, with the participant controlling a 3 Degree-of-Freedom (DOF) virtual reality (VR) hand to match target VR hand postures. The performance of this EMG-based controller was compared to a position-based controller that used movement measured from the participant’s opposite (intact) hand. Surface EMG was also collected for signal quality comparisons. Results Signals from the implanted intramuscular electrodes exhibited less crosstalk between the various channels and had a higher Signal-to-Noise Ratio than surface electrode signals. The performance of the intramuscular EMG-based KNN controller in the VR control task showed no degradation over time, and was stable over the 6 different arm postures. Both the EMG-based KNN controller and the intact hand-based controller had 100% hand posture matching success rates, but the intact hand-based controller was slightly superior in regards to speed (trial time used) and directness of the VR hand control (path efficiency). Conclusions Chronically implanted intramuscular electrodes provide negligible crosstalk, high SNR, and substantial VR control performance, including the ability to use a fixed controller over 12 weeks and under different arm positions. This approach can thus be a highly effective platform for advanced, multi-DOF prosthetic control.


1989 ◽  
Vol 32 (4) ◽  
pp. 849-856 ◽  
Author(s):  
John P. Preece ◽  
Richard S. Tyler

Minimum-detectable gaps for sinusoidal stimuli were measured for three users of a multi electrode cochlear prosthesis as functions of stimulus level, frequency, and electrode place within the cochlea. Stimulus level was scaled by sensation level and by growth-of-loudness functions generated for each condition by direct magnitude estimation. Minimum-detectable gaps decreased with increase in either sensation level or loudness, up to a plateau. When compared at equal sensation levels, the minimum-detectable gaps decreased with frequency increases. The frequency effect on minimum-detectable gaps is reduced if the data are considered at equal loudness. Comparison across place of stimulation within the cochlea showed minimum-detectable gaps to be shorter for more basal electrode placement at low stimulus levels. No differences in minimum-detectable gap as a function of place were found at higher stimulus levels.


2002 ◽  
Vol 16 (2) ◽  
pp. 92-96
Author(s):  
Tiina Ritvanen ◽  
Reijo Koskelo ◽  
Osmo H„nninen

Abstract This study follows muscle activity in three different learning sessions (computer, language laboratory, and normal classroom) while students were studying foreign languages. Myoelectric activity was measured in 21 high school students (10 girls, 11 boys, age range 17-20 years) by surface electromyography (sEMG) from the upper trapezius and frontalis muscles during three 45-min sessions. Root mean square (RMS) average from both investigated muscles was calculated. The EMG activity was highest in both muscle groups in the computer-aided session and lowest in the language laboratory. The girls had higher EMG activity in both investigated muscle groups in all three learning situations. The measured blood pressure was highest at the beginning of the sessions, decreased within 10 min, but increased again toward the end of the sessions. Our results indicate that the use of a computer as a teaching-aid evokes more constant muscle activity than the traditional learning situations. Since muscle tension can have adverse health consequences, more research is needed to determine optimal classroom conditions, especially when technical aids are used in teaching.


Author(s):  
Selma Büyükgöze

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.


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