Accuracy and learning curves of inexperienced observers for manual segmentation of electromyograms

Fisioterapia em Movimento

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Field Value
 
Title Accuracy and learning curves of inexperienced observers for manual segmentation of electromyograms
 
Creator de Sá Ferreira, Arthur
Silva Guimarães, Fernando
Ribeiro Magalhães, Manuel Armando
Coeli Souza e Silva, Regina
 
Description Introduction:The shape-varying format of surface electromyograms introduces errors in the detection of contraction events. Objective: To investigate the accuracy and learning curves of inexperienced observers to detect the quantity of contraction events in surface electromyograms. Materials and methods: Six observers performed manual segmentation in 1200 shape-varying waveforms simulated using a phenomenological model with variable events, smooth changes in amplitude, marked on-off timing, and variable signal-to-noise ratio (0-39 dB). Segmentation was organized in four sessions with 15 blocks of 20 signals each. Accuracy and learning curves were modeled per block by linear and power regression models and tested for difference among sessions. Cut-off values of signal-to-noise ratio for optimal manual segmentation were also estimated. Results: The accuracy curve showed no significant linear trend throughout blocks and no difference among sessions 1-2-3-4 (87% [85; 89], 87% [85; 89], 87% [85; 89], 87% [81; 88]; p = 0.691). Accuracy was low for detection of 1 event (AUC = 0.40; sensitivity = 44%; specificity = 43%; cut-off = 12.9 dB) but was high and affected by the signal-to-noise ratio for detection of two events (AUC = 0.82; sensitivity = 77%; specificity = 76%; cut-off = 7.0 dB). The learning curve showed a significant power regression (p < 0.001) with decreasing values of learning percentages (time duration to complete the task) among sessions 1-2-3-4 (86.5% [68; 94], 76% [68; 91], 62% [38; 77], and 57% [52; 75]; p = 0.002). Conclusion: Inexperienced observers exhibit high, not trainable accuracy and a practice-dependent shortening in the time spent to detect the quantity of contraction events in simulated surface electromyograms.
 
Publisher Editora Universitária Champagnat - PUCPRESS
 
Contributor
 
Date 2017-09-15
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion


 
Format application/pdf
 
Identifier https://periodicos.pucpr.br/index.php/fisio/article/view/21584
10.1590/S0103-51502013000300009
 
Source Fisioterapia em Movimento (Physical Therapy in Movement); v. 26, n. 3 (2013)
Fisioterapia em Movimento; v. 26, n. 3 (2013)
1980-5918
0103-5150
 
Language por
 
Relation https://periodicos.pucpr.br/index.php/fisio/article/view/21584/20690
 
Rights Direitos autorais 2017 Fisioterapia em Movimento
 

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