PubMed · 14802193
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A MAHLO. 1950. [The controlled electrogastrogram].. https://pubmed.ncbi.nlm.nih.gov/14802193/
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This study was designed to evaluate the suitability of nonlinear recurrence quantification analysis (RQA) in assessing electromyograph (EMG) signals during dynamic exercise. RQA has been proven to be effective in analyzing nonstationary signals. The subject group consisted of 19 male patients diagnosed with low back pain. EMG signals were recorded from left and right paraspinal muscles during isoinertial exercise both before and after 12 weeks of regimented physical therapy. Autorecurrence analysis was performed between the left and right EMG signals individually, and cross-recurrence analysis was performed on the left-right EMG pairs. Spectral analysis of the EMG signals was employed as an independent, objective measure of fatigue. Increase in the RQA variable % determinism during the 90-s dynamic tests was found to be a good marker for fatigue. Before physical therapy, this nonlinear marker revealed simultaneous increases in motor unit recruitment within each pool and between left and right pools. After physical therapy, the motor unit recruitment was less within and between pools, indicative of increased fatigue resistance. Finally, fatigue resistance (less increase in % determinism) correlated well with subjective scores of pain relief. Taken together, these latter results indicate that recurrence analysis may be useful in charting the efficacy of a specific exercise therapy program in reducing low back pain by elevating the fatigue threshold.
STUDY OBJECTIVES: The study presents an automatic method for scoring leg movements in polysomnographic recordings and describes an empirical investigation of its validity. DESIGN: Leg movements measured by means of the surface electromyogram activation of the right and left tibialis anterior muscle contained in 24 digitally recorded all-night polysomnograms were analyzed visually according to the American Sleep Disorders Association guidelines by 2 experienced raters and automatically scored using a newly developed electromyogram-based analytical method. Two visual scorings and the automatic scoring were compared in pairs using descriptive and confirmative statistical methods. SETTING: N/A. PARTICIPANTS: All-night polysomnograms of adaptation nights at the sleep laboratory of 10 patients with idiopathic restless legs syndrome (RLS) according to the International RLS Study Group. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Agreement rates between the 2 well-trained scorers and the automatic method were comparable. Based on the first scorer's results (100%) 92.5% of the movements were detected by the second scorer and 94.3% by the automatic method. When the visual scorings were compared, the rate of false-positive and false-negative errors were 7% and 3%, respectively. Comparing both visual scorings with the results of the automatic scoring yielded false-positive and false-negative rates in the range from 3% to 8%. CONCLUSIONS: The degree of accordance between the 2 visual scorings and between the visual and the automatic scorings were comparable. Therefore, this method is valid and may be used for the automatic detection of leg movements in future studies.