EMG assessment of back muscle function during cyclical lifting.
A new approach to estimating the frequency compression of the surface EMG signal during cyclical dynamic exercise is described. The basic properties of the method are first developed using simulated EMG signals. Spectral compression is measured by defining the instantaneous median frequency from time-frequency representations of the signal derived from a transformation of the Cohen class. The technique is then used to process real EMG signals from paraspinal muscles during repetitive lifting. Our purpose was to use this new procedure to identify (a) whether changes in the instantaneous median frequency among concurrently active paraspinal muscles during repetitive trunk extension produces a 'fatigue pattern' that is indicative of normal functioning, and (b) whether this pattern is different when the subject produces a sustained isometric trunk extension. Four healthy subjects (26 +/- 4 years; 3 males, 1 female) were tested in both a Back Analysis System, for the production of a sustained static isometric contraction, and a LIDO-Lift Controller (Loredan), for repetitive lifting and lowering of a weighted box. EMG signals were recorded concurrently from six bilateral lumbar paraspinal regions during these tasks. The results demonstrate that static and dynamic tasks result in very different patterns of EMG spectral changes, suggestive of differences in load-sharing and underlying metabolic fatigue processes. Unlike the linear decrease in median frequency observed for static contractions, during dynamic contractions instantaneous median frequency behavior is non-linear and more complex. Examples are provided in which distinct periods of instantaneous median frequency decay are followed by periods of recovery during a single trial of repetitive lifting. It is hypothesized that this difference reflects a complex strategy of utilizing muscle load-sharing during strenuous dynamic exercise to provide periods of metabolic recovery that limit localized fatigue. New analysis procedures to characterize this complex behavior are needed to enhance the technique for assessment of impairment in patients with lower back pain.
NeuroMuscular Research Center, Boston University, MA 02215, USA. sroy@bu.edu
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Roy
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Bonato
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Knaflitz
D000328:Adult; D004576:Electromyography; D005260:Female; D006801:Humans; D008161:Lumbosacral Region / Q000502:physiology*; D008297:Male; D008432:Mathematical Computing; D009119:Muscle Contraction / Q000502:physiology*; D018763:Muscle Fatigue / Q000502:physiology; D018482:Muscle, Skeletal / Q000502:physiology*; D014891:Weight Lifting / Q000502:physiology*