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Research Report |
CT Candotti, PhD, is Professor, Curso de Educação Física, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil.
JF Loss, PhD, is Professor, Escola de Educação Física, Universidade Federal do Rio Grande do Sul, Rua Fernando Osório, 1887, CEP 91720-330, Porto Alegre, Brazil.
AMS Pressi, MSc, is Research Assistant, Curso de Educação Física, Universidade do Vale do Rio dos Sinos.
FAS Castro, PhD, is Professor, Escola de Educação Física, Universidade Federal do Rio Grande do Sul.
M La Torre is Physical Education Teacher and an MSc student in the Curso de Educação Física, Universidade do Vale do Rio dos Sinos.
MO Melo is Physical Education Teacher and an MSc student in the Curso de Educação Física, Universidade do Vale do Rio dos Sinos.
LD Araújo is Physical Education Teacher and an MSc student in the Curso de Educação Física, Universidade do Vale do Rio dos Sinos.
M Pasini is Physical Education Teacher and an MSc student in the Curso de Educação Física, Universidade do Vale do Rio dos Sinos.
Background and Purpose: Pain is currently evaluated with "subjective" methods (eg, patient self-report). This study aimed to test whether fatigue indexes are able to accurately discriminate between subjects with and subjects without low back pain.
Subjects: Sixty subjects separated into 2 groups—a group with low back pain (n=30) and a group without low back pain (n=0)—participated in this study.
Methods: Electromyographic (EMG) and force data were obtained during a muscle fatigue test. The same test was repeated to monitor recovery. Linear regression analysis was used to obtain fatigue indexes.
Results: Subjects with pain produced significantly lower force values than those without pain. The use of fatigue indexes and force values permitted accurate classification in 89.5% of cases.
Discussion and Conclusion: The results confirm that subjects with pain show early myoelectrical manifestations of muscle fatigue and that EMG can be a useful tool in the evaluation of low back pain.
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