Proceedings of The Physiological Society

University College Dublin (2009) Proc Physiol Soc 15, C39

Oral Communications

Identification of aerobic-anaerobic transition in male rowers using surface electromyography during graded incremental exercise

N. Fleming1, B. Donne1, N. Mahony2

1. Physiology, Trinity College Dublin, Dublin 2, Ireland. 2. Anatomy, Trinity College, Dublin, Ireland.


It has recently been shown that non-linear changes in myoelectric data relative to exercise intensity can be used to identify the aerobic-anaerobic threshold (Condotti et al. 2008, Farina et al. 2007. However these studies restricted their analysis to cycling tasks. The aim of this study was to assess the use of surface electromyography (EMG) as a non-invasive determinant of the metabolic response to incremental rowing exercise. The relationships between EMG threshold (TEMG) and more commonly used variables for detection of the aerobic-anaerobic threshold namely; blood lactate threshold (TLac) and onset of blood lactate accumulation (OBLA) were assessed. Eleven male club-level rowers (age 21±4yr, height 1.88±0.04m, mass 84±7kg, VO2max 60.9±5.8mL.kg-1.min-1) performed graded tests to volitional exhaustion on a Concept II ergometer. This ethically approved study involved intermittent exercise bouts at fixed workloads (start load 120W, duration 3 min, rest 1 min, increment 40W) during which EMG data were recorded from Rectus Femoris (RF), Vastus Lateralis (VL), Biceps Femoris (BF) and upper portion of Trapezius (UT). The rest period between increments facilitated earlobe blood sampling for lactate determination. Root mean square EMG (rms-EMG) for each muscle were calculated using a 50ms averaging window over 10 consecutive stroke cycles during the final minute of each exercise increment. Individual loads at EMG threshold were identified using the V-slope method and compared against load at TLac and OBLA using a repeated measures ANOVA. Pearson’s correlation analysis showed strong association between blood lactate and rms-EMG activity in RF (r=0.81), VL (r=0.63) and BF (r=0.70), and lower association in UT (r=0.47). Analysis revealed no significant differences between TLac (256±10W) and TEMG in RF (265±8W) and VL (267±7W), however TEMG occurred at significantly higher workloads (P<0.01) for BF (273±9W) and UT (275±11W). No significant differences were observed comparing TEMG and OBLA (276±12W) in any of the muscles investigated. Our results suggest that TEMG is strongly associated to both OBLA and TLac (r=0.75 to 0.94) and that there are differing recruitment strategies relative to increasing exercise intensity between the muscles analysed in the current study. Our data showed comparible levels of correlation with previously published literature (Farina et al. 2007), however further examination of TEMG in other muscles and in other dynamic tasks is necessary in order to better assess the potential use of EMG as a non-invasive determinant of the aerobic anaerobic threshold.

Where applicable, experiments conform with Society ethical requirements