| An Algorithm for the Estimation of the Signal-To-Noise Ratio in Surface Myoelectric Signals Generated During Cyclic Movements. | |
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MedLine Citation:
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PMID: 21984489 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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In many applications requiring the study of the surface myoelectric signal (SMES) acquired in dynamic conditions, it is essential to have a quantitative evaluation of the quality of the collected signals. When the activation pattern of a muscle has to be obtained by means of single- or double-threshold statistical detectors, the background noise level (enoise) of the signal is a necessary input parameter. Moreover, the detection strategy of double-threshold detectors may be properly tuned when the signal-to-noise ratio (SNR) and the duty cycle (DC) of the signal are known. The aim of this work is to present an algorithm for the estimation of enoise, SNR and DC of a SMES collected during cyclic movements. The algorithm is validated on synthetic signals with statistical properties similar to those of SMES, as well as on more than a hundred real signals. |
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Authors:
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V Agostini; M Knaflitz |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-10-06 |
Journal Detail:
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Title: IEEE transactions on bio-medical engineering Volume: - ISSN: 1558-2531 ISO Abbreviation: - Publication Date: 2011 Oct |
Date Detail:
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Created Date: 2011-10-10 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0012737 Medline TA: IEEE Trans Biomed Eng Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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