Validation of the physical working capacity at the fatigue threshold treadmill test

Abstract

The purposes of the present study were twofold: 1) to determine the physical working capacity at the fatigue threshold (PWC FT ) during an incremental treadmill test, and 2) to examine the validity of this fatigue threshold through constant-velocity runs to exhaustion at 90, 100, and 110% of the estimated PWC FT . Twelve aerobically-trained males (mean age±SD=24.6±5.4 years, running volume=69.9±46.0 km·wk -1 , n=9) and females (22.3±2.3 years, 45.6±4.6 km·wk -1 , n=3) volunteered to perform a treadmill test to exhaustion with electromyographic (EMG) signals recorded from the m. vastus lateralis on four separate visits. The first visit required each subject to complete an incremental treadmill test to exhaustion for determination of their PWC FT . During the second, third, and fourth visit, the subjects completed a treadmill run to exhaustion at a constant velocity that corresponded to 90, 100, or 110% of their PWC FT in random order. The linear regression analyses indicated there were no significant (p>.05) changes in muscle activation (i.e. EMG amplitude) across time to exhaustion during the constant velocity runs at 90% (60.00±0.00 min) and 100% (48.86±14.59 min) PWC FT , but significant (p<.05) increases occurred at 110% PWC FT (19.44±10.26 min). Thus, the findings of the present study indicated that the PWC FT treadmill test was able to accurately estimate the fastest running velocity that could be maintained for an extended period of time without evidence of neuromuscular fatigue.

A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation

“…Previous studies have shown that features from an electromyography (EMG) signal can be used to detect fatigue thresholds both during cycling and running [3,4]. The features that have most frequently been used to calculate the fatigue thresholds are amplitude-based measures, such as the root mean square and integrated EMG, and frequency-based measures, such as mean power frequency or median frequency [3].…”