The Measurement of Surface Electromyographic Signal in Rest Position for the Correct Prescription of Eyeglasses
The study of activities of superficial muscles in rest positions is today an interesting research field for many clinical applications. The evaluation of human surface muscle activity and stress, such as face muscles, is important for the functional study, diagnosis, and prosthetic and orthodontic t...
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Published in | IEEE transactions on instrumentation and measurement Vol. 61; no. 2; pp. 419 - 428 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.02.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | The study of activities of superficial muscles in rest positions is today an interesting research field for many clinical applications. The evaluation of human surface muscle activity and stress, such as face muscles, is important for the functional study, diagnosis, and prosthetic and orthodontic therapy. The surface electromyography (SEMG) is a measurement technique widely adopted for evaluating the activity of body surface muscles in a noninvasive way, even if this is not a straightforward task, mainly because the signals present low signal-to-noise ( S / N ) ratios. To increase the S / N , traditional SEMG measurements are conducted during isometric activities, applying amplification and filtering of the low-frequency components; the final signal is not suitable for the evaluation of the muscular activity and stress in rest positions, as during the optometric examinations. The main goal of this paper is to propose a new measurement system capable of acquiring and processing surface electromyographic signals in rest position and of supplying a direct indication of the optimal eyeglass prescription. The main experimental results, obtained with a prototype of the proposed system, are presented and discussed. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 0018-9456 1557-9662 |
DOI: | 10.1109/TIM.2011.2164838 |