Heart Rate, Blood Lactate, And Accelerometer-based Activity Data During An Incremental Swim Test

Abstract

INTRODUCTION: Competitive swim coaches commonly use swim time observed from pace clocks and stopwatches and or direct verbal feedback from athletes as the primary means of gauging intensity during training. However, technological advances now permit the use of accelerometer-based monitors during aquatic activity. Recent studies suggest the use of activity monitors can provide an alternative, unobtrusive means of quantifying competitive swim activity (i.e. swim bout distance, speed, and energy expenditure; Wright & Stager, 2013, Wright, Brammer, & Stager, 2015). PURPOSE: The purpose of this study was to further examine the relationships between physiological measures (i.e. heart rate and blood lactate) and activity counts (from arm stroke and leg kick movement) during a progressive series of swim bouts. METHODS: Actical activity counts (from arm stroke and leg kick movement), swim speed, heart rate (HR), and blood lactate were collected during a series of seven progressive front crawl swim bouts each one 182.8m (200 yard) in distance. Subjects consisted of ten collegiate competitive swimmers (5 men & 5 women, Age 20.8 ± 1.1 years). The relationship between activity counts and physiological measures were modeled using linear and 2nd order polynomial fits for each subject. RESULTS: Linear regression analyses were significant in all models examining blood lactate (p < 0.05) and for eight of the ten subjects in models examining HR (p < 0.05). Polynomial regression analyses were significant for all subjects in models examining blood lactate (p < 0.05) and five of the ten subjects in models examining HR (p < 0.05). Mean values for individualized regression analyses R2 values ranged from 0.71-0.95 and 0.76-0.98 for linear and polynomial models respectively. Both linear and polynomial models examining the relationship between activity counts and swim speed were significant all in subjects (p < 0.05; R2 values ranged from 0.94-0.99). CONCLUSIONS : This study demonstrates that regression techniques using accelerometer-based activity counts recorded from arm stroke and leg kick movement may provide a non-invasive means of quantifying swim bout intensity within a group of collegiate swimmers.