Endurance is a clinically relevant muscle parameter. It would be desirable to be able to estimate it without the need for a contraction sustained to exhaustion. The purpose of this work was to investigate the capability of the initial rate of spectral compression of the surface electromyographic (EMG) signal to predict mechanical endurance during sustained voluntary contractions of the human tibialis anterior muscle. Six healthy subjects performed voluntary isometric contractions of the tibialis anterior at 80, 70, 60, and 50% of the maximal voluntary contraction level. The contractions were sustained for 90, 120, 150, and 170 seconds, respectively. These intervals exceed the normal endurance time for this muscle and allow for a decrease of torque output. The slope of the median frequency, computed over the first 30 seconds of the contraction, was used to describe the initial spectral compression of the EMG signal. Significant correlations were found: 1) between contraction level and endurance time (p < 0.05 for each subject) and 2) between median (or mean) frequency slope and endurance time (p < 0.0001 for all subjects pooled together). The regression between median frequency slope and endurance time showed intersubject variations possibly related to the tibialis anterior muscle fiber type content. It is concluded that clinical use of the EMG spectral technique in assessing muscle fatigue may enable the clinician to estimate the endurance time without having the subject sustain a contraction until the point of contractile failure. This could be an advantage for some patient populations, such as the severely disabled, arthritic, or frail elderly that might not be able to tolerate long duration contractions.

J Orthop Sports Phys Ther. 1996;24(6):342-353.

Key Words: electromyography, muscle fatigue, conduction velocity

Studies that evaluate effectiveness of physical therapy can be problematic because frequently several treatment techniques are used during an episode of care. Methods that categorize treatment techniques into discrete categories may be useful in studying treatment outcomes. The purpose of this study was to describe a method to create treatment categories used for patients with low back pain. We surveyed physical therapists in Virginia to identify frequently used treatments for patients with low back pain. One hundred fifty-five surveys were completed. Twenty-eight treatments, used frequently or very frequently by 50% or more of the respondents, were retained for analysis. Factor analysis was used to identify treatment categories. Seven categories were identified: McKenzie approach, manual therapy, exercise with equipment, active and stretching exercise, physical agents, aerobic exercise and walking, and ergonomic activities. Indices for the categories were created. Confirmatory factor analyses should be performed on a different sample to validate these findings.

J Orthop Sports Phys Ther. 1996;24(6):359-364.

Key Words: low back pain, physical therapy, factor analysis

Index by subject of all manuscripts published by the Journal from July through December 1996.

J Orthop Sports Phys Ther. 1996;24(6):376-381.