2019
DOI: 10.3390/healthcare7040150
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Study on the Recognition of Exercise Intensity and Fatigue on Runners Based on Subjective and Objective Information

Abstract: A running exhaustion experiment was used to explore the correlations between the time-frequency domain indexes extracted from the surface electromyography (EMG) signals of targeted muscles, heart rate and exercise intensity, and subjective fatigue. The study made further inquiry into the feasibility of reflecting and evaluating the exercise intensity and fatigue effectively during running using physiological indexes, thus providing individualized guidance for running fitness. Twelve healthy men participated in… Show more

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Cited by 14 publications
(15 citation statements)
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“…The time from running to exhaustion is a common indicator reflecting exercise ability, and improvement of exercise ability is the most powerful macro-reflection of anti-fatigue ability. 33 Our study confirmed that the CQPC08 significantly prolongs the time from running to exhaustion.…”
Section: Discussionsupporting
confidence: 77%
“…The time from running to exhaustion is a common indicator reflecting exercise ability, and improvement of exercise ability is the most powerful macro-reflection of anti-fatigue ability. 33 Our study confirmed that the CQPC08 significantly prolongs the time from running to exhaustion.…”
Section: Discussionsupporting
confidence: 77%
“…To facilitate the experiment, the mean treadmill speed was adjusted according to the %HRR interval to explore the relationship between %HRR and exercise intensity and determine the treadmill speed to use for the running experiment [ 27 ]. Half of the subjects (7 in total) were randomly selected to participate in the treadmill speed determination experiment.…”
Section: Methodsmentioning
confidence: 99%
“…Both MF and MDF can represent the frequency of measured muscle CV, but in practical application, MDF is more sensitive than MF in reflecting muscle activity and functional state. MF can also get good results in muscle fatigue detection ( Chai et al, 2019 ). Significant changes in the PS indicate muscle fatigue, and the PS drifts from high frequency to low frequency.…”
Section: Frequency-domain Feature Analysismentioning
confidence: 99%