Affiliations: [a] Institut Nacional d'Activitat Física de Catalunya Barcelona, Barcelona, Spain | [b] Fundació Universitària del Bages, Barcelona, Spain | [c] Department of Kinesiology, California State University, Northridge, CA, USA
Correspondence:
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Corresponding author: Júlia Jubany, Institut Nacional d'Activitat Física de Catalunya Barcelona, Av. de l'Estadi 12-22, Anella Olímpica, 08038 Barcelona, Spain. Tel.: +34 93 425 54 45, +34 606522496; E-mail:jjubany@fub.edu
Abstract: BACKGROUND: Most of the EMG analysis algorithms developed
to date don't detect the whole sequence of rhythmic and subtle changes that
take place during the process of trunk stabilization. Indeed, the few recent
methods that are capable of assessing these important EMG characteristics
are highly complex and not accessible in most applied clinic contexts. OBJECTIVE: To validate and disseminate a software program suitable
for detecting multiple and relatively small EMG bursts during a trunk
stabilization response. METHODS: Ninety EMG recordings randomly selected from 50
individuals (24 with chronic low back pain) were analysed by our algorithm
based on means and standard deviations and an experienced examiner (as a
gold standard). Concordance, sensitivity, specificity, positive predictive
value and negative predictive value were considered to analyse reliability. RESULTS: Results showed a high degree of concordance between the
two methods (87.2%), high sensitivity and specificity rates (79.5 and
89.2%), a moderate-low positive predicted value (66.9%) and a high
negative predicted value (94.4%). CONCLUSION: The program provided is flexible and useful to detect
EMG activity. The selected parameters of the program were able to detect
onset/offset EMG bursts and were valid for the purpose of this study with a
small tendency to over-detect bursts.
