Physiological responses to ergometer and on-water incremental rowing tests

Assessment of Angular and Straight Linear Rowing Ergometers at Different Intensities of Exercise

We aimed to conduct a biophysical comparison of angular (Biorower) and linear (Concept2) rowing ergometers across a wide spectrum of exercise intensities. Sixteen (eleven male) skilled rowers, aged 29.8 ± 8.6 and 23.6 ± 1.5 years, with international competitive experience, performed 7 × 3 min bouts with 30 W increments and 60 s intervals, plus 1 min of all-out rowing on both machines with 48 h in between. The ventilatory and kinematical variables were measured breath-by-breath using a telemetric portable gas analyzer and determined using a full-body markerless system, respectively. Similar values of oxygen uptake were observed between ergometers across all intensity domains (e.g., 60.36 ± 8.40 vs. 58.14 ± 7.55 mL/min/kg for the Biorower and Concept2 at severe intensity). The rowing rate was higher on the Biorower vs. Concept2 at heavy and severe intensities (27.88 ± 3.22 vs. 25.69 ± 1.99 and 30.63 ± 3.18 vs. 28.94 ± 2.29). Other differences in kinematics were observed across all intensity domains, particularly in the thorax angle at the finish (e.g., 19.44 ± 4.49 vs. 27.51 ± 7.59° for the Biorower compared to Concep2 at heavy intensity), likely due to closer alignment of the Biorower with an on-water rowing technique. The overall perceived effort was lower on the Biorower when compared to the Concept2 (14.38 ± 1.76 vs. 15.88 ± 1.88). Rowers presented similar cardiorespiratory function on both rowing ergometers, while important biomechanical differences were observed, possibly due to the Biorower's closer alignment with an on-water rowing technique.

Morphological and hand grip strength characteristics and differences between participants of the 2022 world rowing championship

Introduction

Rowing is a strength endurance type of sport, and morphology and mass are undoubtedly performance-related factors. Precisely identifying these morphological factors associated with performance, can assist the exercise scientists and coaches in selecting and developing talented athletes. There is however, a lack of anthropometric data collected at either World Championship or Olympic Games level. The aims of this study were to describe and compare the morphology and basic strength characteristic of male and female heavyweight and lightweight rowers competing at 2022 World Championship (18.–25. September, Račice, Czech Republic).

Methods

A total of 68 athletes (of 46 male competitors: 15 competed in the lightweight category and 31 in the heavyweight category; of 22 female athletes: 6 competed in the lightweight category and 16 in the heavyweight category) were assessed using anthropometric methods, bioimpedance analysis and performed a hand-grip test.

Results

Between heavyweight and lightweight male rowers there were a statistically and practically significant differences in all monitored aspects except the sport age, sitting height/body height ratio and arm span/body height ratio. Between heavyweight and lightweight female rowers there were also statistically and practically significant differences in all monitored aspects except the identical indicators as in male.

Discussion

Within this research it can be argued that female rowers are in many anthropometric aspects more similar to their male counterparts than to female rowers in the lightweight category. In some anthropometric aspects (BMI, thigh girth, calf girth), female rowers are even more similar to male heavyweight than to male lightweight rowers. The physical characteristics of elite male and female lightweight rowers differ radically from those of heavyweight. From a practical point of view, this research can be used to determine what type of athletes should be recruited or selected for heavy category and what type for lightweight category in male and female rowing based on the somatotype.

Can the 20 and 60 s All-Out Test Predict the 2000 m Indoor Rowing Performance in Athletes?

Purpose: The purpose of this study was to look for a new, simple, and fast method of assessing and monitoring indoor race performance and to assess the relationship between 20 s, 60 s, and 2000 m indoor rowing performances of youth rowers to evaluate their anaerobic profile.

Methods: For three consecutive days, 17 young able-bodied male rowers (15.8 ± 2.0 years), performed three tests (20 s, 60 s, and 2000 m) on a rowing ergometer. Mean power (W₂₀, W₆₀, and W₂₀₀₀) and 2000 m time (t₂₀₀₀) were considered for the analysis. In addition, 14 athletes (15–18 years) performed a 20 s, 60 s, and 2000 m tests and used this as a control group. To define the anaerobic profile of the athletes, W₂₀ and W₆₀ were normalized as percentages of W₂₀₀₀. Associations between variables were determined by means of the Pearson correlation coefficient (r).

Results: Mean power decreased with increasing test duration (W₂₀ = 525.1 ± 113.7 W; W₆₀ = 476.1 ± 91.0 W; W₂₀₀₀₌312.9 ± 56.0 W) and negative correlations emerged between t₂₀₀₀ (418.5 ± 23.1 s) and W₂₀ (r = −0.952, p < 0.0001) and W₆₀ (r = −0.930, p < 0.0001).

Conclusion: These findings indicate that W₂₀ and W₆₀ are significant predictors of 2000 m rowing ergometer performances. Furthermore, normalized W₂₀ and W₆₀ can be used to evaluate athletes and as a reference for planning anaerobic training sessions, on a rowing ergometer.

High Energetic Demand of Elite Rowing - Implications for Training and Nutrition

Purpose: Elite rowers have large body dimensions, a high metabolic capacity, and they realize high training loads. These factors suggest a high total energy requirement (TER), due to high exercise energy expenditure (EEE) and additional energetic needs. We aimed to study EEE and intensity related substrate utilization (SU) of elite rowers during rowing (EEE_ROW) and other (EEE_NON-ROW) training.

Methods: We obtained indirect calorimetry data during incremental (N = 174) and ramp test (N = 42) ergometer rowing in 14 elite open-class male rowers (body mass 91.8 kg, 95% CI [87.7, 95.9]). Then we calculated EEE_ROW and SU within a three-intensity-zone model. To estimate EEE_NON-ROW, appropriate estimates of metabolic equivalents of task were applied. Based on these data, EEE, SU, and TER were approximated for prototypical high-volume, high-intensity, and tapering training weeks. Data are arithmetic mean and 95% confidence interval (95% CI).

Results: EEE_ROW for zone 1 to 3 ranged from 15.6 kcal·min⁻¹, 95% CI [14.8, 16.3] to 49.8 kcal·min⁻¹, 95% CI [48.1, 51.6], with carbohydrate utilization contributing from 46.4%, 95% CI [42.0, 50.8] to 100.0%, 95% CI [100.0, 100.0]. During a high-volume, a high-intensity, or a taper week, TER was estimated to 6,775 kcal·day⁻¹, 95% CI [6,651, 6,898], 5,772 kcal·day⁻¹, 95% CI [5,644, 5,900], or 4,626 kcal∙day⁻¹, 95% CI [4,481, 4,771], respectively.

Conclusion: EEE in elite open-class male rowers is remarkably high already during zone 1 training and carbohydrates are dominantly utilized, indicating relatively high metabolic stress even during low intensity rowing training. In high-volume training weeks, TER is presumably at the upper end of the sustainable total energy expenditure. Periodized nutrition seems warranted for rowers to avoid low energy availability, which might negatively impact performance, training, and health.

Is the Energy Cost of Rowing a Determinant Factor of Performance in Elite Oarsmen?

In elite oarsmen, the rowing ergometer is a valuable tool for both training and studying rowing performance determinants. However, the energy cost of rowing, often reported as a determinant of performance, has never been described for ergometer rowing. Therefore, this study aimed to characterize the energy cost of ergometer rowing (ECR) in elite oarsmen, its contribution to 2,000 m performance, and its determinants. This study was conducted on 21 elite oarsmen from the French national team. It included an incremental exercise test up to exhaustion and an all-out performance test over 2,000 m, both conducted on a rowing ergometer. Gas exchange analysis was performed to calculate oxygen uptake and substrate utilization rate. Whole blood lactate concentrations during the incremental test were obtained from the earlobe. During the incremental test, ECR displayed a significant linear increase up to a plateau that reached a mean rowing speed of 5.23 ± 0.02 m⋅s^–1. The ECR values at 300, 350, and 400 W were positively correlated with performance expressed as the time required to perform the 2,000 m distance on the rowing ergometer. The same ECR values were found to be significantly related to fat oxidation (expressed in percentage of total energy supply) and blood lactate concentrations. This study provides the first description of ECR and of its relationship to exercise intensity on the rowing ergometer in elite oarsmen. ECR appeared to be a factor of performance and interestingly was related to energy supply from fat and blood lactate concentrations.

A Comparison of Physiological Response to Incremental Testing on Stationary and Dynamic Rowing Ergometers

PURPOSE

The purpose of the current study was to compare responses to graded exercise testing (GXT) on 2 popular commercial rowing ergometers.

METHODS

A cohort of 23 subelite male rowers (age 20 [2] y, height 1.88 [0.06] m, body mass 82.0 [8.8] kg) performed a GXT on both stationary (Concept2 [C2]) and dynamic (RowPerfect3 [RP3]) rowing ergometers. Physiological responses including oxygen consumption (VO2), heart rate (HR), blood lactate concentration (BLa), stroke rate (SR), and minute ventilation (VE) were recorded. BLa data were plotted graphically and anaerobic threshold was identified using the Dmax method. Workload, HR, and VO2 at Dmax were interpolated. Physiological responses at maximal exercise and at Dmax were compared, along with response across a discrete range of submaximal workloads.

RESULTS

At maximal exercise, no significant differences in HR, VO2, or BLa were observed (P > .05); however, VEpeak was significantly higher during RP3 tests (T = 2.943, P < .05). No significant differences in HR, VO2, or BLa at Dmax were observed (P > .05). When comparing across submaximal workloads, HR was significantly higher with the RP3 at 2 distinct workloads (210 and 240 W; P < .05), while SR was higher during RP3 testing at all workloads (F = 56.7, P < .05). When SR was fixed as a covariate, the effect of ergometer on HR response was not significant. A significant workload by ergometer interaction effect was observed for SR with higher data recorded on the RP3 (F = 3.48, P < .01). Levels of agreement for GXT-derived measures of anaerobic threshold (Dmax) were deemed unacceptable.

CONCLUSIONS

These results indicate that while some differences in HR and VE response were observed between ergometers, these differences were a result of SR alterations between ergometer type. While no differences in response at Dmax were observed, the poor levels of agreement between ergometers suggests that prescription of GXT-derived threshold for training should ideally be specific to the rowing ergometer upon which the test was performed.

Concurrent Validity of Power From Three On-Water Rowing Instrumentation Systems and a Concept2 Ergometer

Purpose: Instrumentation systems are increasingly used in rowing to measure training intensity and performance but have not been validated for measures of power. In this study, the concurrent validity of Peach PowerLine (six units), Nielsen-Kellerman EmPower (five units), Weba OarPowerMeter (three units), Concept2 model D ergometer (one unit), and a custom-built reference instrumentation system (Reference System; one unit) were investigated.

Methods: Eight female and seven male rowers [age, 21 ± 2.5 years; rowing experience, 7.1 ± 2.6 years, mean ± standard deviation (SD)] performed a 30-s maximal test and a 7 × 4-min incremental test once per week for 5 weeks. Power per stroke was extracted concurrently from the Reference System (via chain force and velocity), the Concept2 itself, Weba (oar shaft-based), and either Peach or EmPower (oarlock-based). Differences from the Reference System in the mean (representing potential error) and the stroke-to-stroke variability (represented by its SD) of power per stroke for each stage and device, and between-unit differences, were estimated using general linear mixed modeling and interpreted using rejection of non-substantial and substantial hypotheses.

Results: Potential error in mean power was decisively substantial for all devices (Concept2, –11 to –15%; Peach, −7.9 to −17%; EmPower, −32 to −48%; and Weba, −7.9 to −16%). Between-unit differences (as SD) in mean power lacked statistical precision but were substantial and consistent across stages (Peach, ∼5%; EmPower, ∼7%; and Weba, ∼2%). Most differences from the Reference System in stroke-to-stroke variability of power were possibly or likely trivial or small for Peach (−3.0 to −16%), and likely or decisively substantial for EmPower (9.7–57%), and mostly decisively substantial for Weba (61–139%) and the Concept2 (−28 to 177%).

Conclusion: Potential negative error in mean power was evident for all devices and units, particularly EmPower. Stroke-to-stroke variation in power showed a lack of measurement sensitivity (apparent smoothing) that was minor for Peach but larger for the Concept2, whereas EmPower and Weba added random error. Peach is therefore recommended for measurement of mean and stroke power.

Heart rate and stroke rate misrepresent supramaximal sprint kayak training as quantified by power

This study examined the utility of novel measures of power output (PO) compared to traditional measures of heart rate (HR) and stroke rate (SR) for quantifying high-intensity sprint kayak training. Twelve well-trained, male and female sprint kayakers (21.3 ± 6.8 y) completed an on-water graded exercise test (GXT) and a 200-, 500- and 1000-m time-trial for the delineation of individualised training zones (T) for HR (5-zone model, T1-T5), SR and PO (8-zone model, T1-T8). Subsequently, athletes completed two repeat trials of a high-intensity interval (HIIT) and a sprint interval (SIT) training session, where intensity was prescribed using individualised PO-zones. Time-in-zone (minutes) using PO, SR and HR was then compared for both HIIT and SIT. Compared to PO, time-in-zone using HR was higher for T1 in HIIT and SIT (P < 0.001, d ≥ 0.90) and lower for T5 in HIIT (P < 0.001, d = 1.76). Average and peak HR were not different between HIIT (160 ± 9 and 173 ± 11 bpm, respectively) and SIT (157 ± 13 and 174 ± 10 bpm, respectively) (P ≥ 0.274). In HIIT, time-in-zone using SR was higher for T4 (P < 0.001, d = 0.85) and was lower for T5 (P = 0.005, d = 0.43) and T6 (P < 0.001, d = 0.94) compared to PO. In SIT, time-in-zone using SR was lower for T7 (P = 0.001, d = 0.66) and was higher for T8 (P = 0.004, d = 0.70), compared to PO. Heart rate measures were unable to differentiate training demands across different high-intensity sessions, and could therefore misrepresent the training load in such instances. Furthermore, SR may not provide a sensitive measure for detecting changes in intensity due to fatigue, whereas PO may be more suitable.

Development of an On-Water Graded Exercise Test for Flat-Water Sprint Kayak Athletes

PURPOSE

To determine the reliability and validity of a power-prescribed on-water (OW) graded exercise test (GXT) for flat-water sprint kayak athletes.

METHODS

Nine well-trained sprint kayak athletes performed 3 GXTs in a repeated-measures design. The initial GXT was performed on a stationary kayak ergometer in the laboratory (LAB). The subsequent 2 GXTs were performed OW (OW1 and OW2) in an individual kayak. Power output (PWR), stroke rate, blood lactate, heart rate, oxygen consumption, and rating of perceived exertion were measured throughout each test.

RESULTS

Both PWR and oxygen consumption showed excellent test-retest reliability between OW1 and OW2 for all 7 stages (intraclass correlation coefficient > .90). The mean results from the 2 OW GXTs (OWAVE) were then compared with LAB, and no differences in oxygen consumption across stages were evident (P ≥ .159). PWR was higher for OWAVE than for LAB in all stages (P ≤ .021) except stage 7 (P = .070). Conversely, stroke rate was lower for OWAVE than for LAB in all stages (P < .010) except stage 2 (P = .120).

CONCLUSIONS

The OW GXT appears to be a reliable test in well-trained sprint kayak athletes. Given the differences in PWR and stroke rate between the LAB and OW tests, an OW GXT may provide more specific outcomes for OW training.

New approaches to determine fatigue in elite athletes during intensified training: Resting metabolic rate and pacing profile

Background

Elite rowers complete a high volume of training across a number of modalities to prepare for competition, including periods of intensified load, which may lead to fatigue and short-term performance decrements. As yet, the influence of substantial fatigue on resting metabolic rate (RMR) and exercise regulation (pacing), and their subsequent utility as monitoring parameters, has not been explicitly investigated in elite endurance athletes.

Method

Ten National-level rowers completed a four-week period of intensified training. RMR, body composition and energy intake were assessed PRE and POST the four-week period using indirect calorimetry, Dual-Energy X-Ray Densitometry (DXA), and three-day food diary, respectively. On-water rowing performance and pacing strategy was evaluated from 5 km time trials. Wellness was assessed weekly using the Multicomponent Training Distress Scale (MTDS).

Results

Significant decreases in absolute (mean ± SD of difference, p-value: -466 ± 488 kJ.day^-1, p = 0.01) and relative RMR (-8.0 ± 8.1 kJ.kg.FFM^-1, p = 0.01) were observed. Significant reductions in body mass (-1.6 ± 1.3 kg, p = 0.003) and fat mass (-2.2 ± 1.2 kg, p = 0.0001) were detected, while energy intake was unchanged. On-water 5 km rowing performance worsened (p < 0.05) and an altered pacing strategy was evident. Fatigue and total mood disturbance significantly increased across the cycle (p < 0.05), and trends were observed for reduced vigour and increased sleep disturbance (p < 0.1).

Conclusion

Four weeks of heavy training decreased RMR and body composition variables in elite rowers and induced substantial fatigue, likely related to an imbalance between energy intake and output. This study demonstrates that highly experienced athletes do not necessarily select the correct energy intake during periods of intensified training, and this can be assessed by reductions in RMR and body composition. The shortfall in energy availability likely affected recovery from training and altered 5 km time trial pacing strategy, resulting in reduced performance.

Convergent validity of a novel method for quantifying rowing training loads

Elite rowers complete rowing-specific and non-specific training, incorporating continuous and interval-like efforts spanning the intensity spectrum. However, established training load measures are unsuitable for use in some modes and intensities. Consequently, a new measure known as the T2minute method was created. The method quantifies load as the time spent in a range of training zones (time-in-zone), multiplied by intensity- and mode-specific weighting factors that scale the relative stress of different intensities and modes to the demands of on-water rowing. The purpose of this study was to examine the convergent validity of the T2minute method with Banister's training impulse (TRIMP), Lucia's TRIMP and Session-RPE when quantifying elite rowing training. Fourteen elite rowers (12 males, 2 females) were monitored during four weeks of routine training. Unadjusted T2minute loads (using coaches' estimates of time-in-zone) demonstrated moderate-to-strong correlations with Banister's TRIMP, Lucia's TRIMP and Session-RPE (rho: 0.58, 0.55 and 0.42, respectively). Adjusting T2minute loads by using actual time-in-zone data resulted in stronger correlations between the T2minute method and Banister's TRIMP and Lucia's TRIMP (rho: 0.85 and 0.81, respectively). The T2minute method is an appropriate in-field measure of elite rowing training loads, particularly when actual time-in-zone values are used to quantify load.

Prediction of rowing ergometer performance from functional anaerobic power, strength and anthropometric components

The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years) participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE). Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s). Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s). As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.

A comparison of electromyography and stroke kinematics during ergometer and on-water rowing

This study assessed muscle recruitment patterns and stroke kinematics during ergometer and on-water rowing to validate the accuracy of rowing ergometry. Male rowers (n = 10; age 21 ± 2 years, height 1.90 ± 0.05 m and body mass 83.3 ± 4.8 kg) performed 3 × 3 min exercise bouts, at heart and stroke rates equivalent to 75, 85 and 95% VO2peak, on both dynamic and stationary rowing ergometers, and on water. During exercise, synchronised data for surface electromyography (EMG) and 2D kinematics were recorded. Overall muscle activity was quantified by the integration of rmsEMG and averaged for each 10% interval of the stroke cycle. Muscle activity significantly increased in rectus femoris (RF) and vastus medialis (VM) (P <0.01), as exercise intensity increased. Comparing EMG data across conditions revealed significantly (P <0.05) greater RF and VM activity during on-water rowing at discrete 10% intervals of stroke cycle. In addition, the drive/recovery ratio was significantly lower during dynamic ergometry compared to on-water (40 ± 1 vs. 44 ± 1% at 95%, P <0.01). Results suggest that significant differences exist while comparing recruitment and kinematic patterns between on-water and ergometer rowing. These differences may be due to altered acceleration and deceleration of moving masses on-ergometer not perfectly simulating the on-water scenario.

Cardio-respiratory and electromyographic responses to ergometer and on-water rowing in elite rowers

The aim of this study was to compare muscle activation and cardio-respiratory response during ergometer and on-water rowing. Nine internationally competitive rowers (five Olympic Games medal winners, age 25.6 ± 4.8 years) were requested to perform a 1,000 m race simulation test in the two conditions. Surface electromyographic (sEMG) signals from trapezius superior (TRS), latissimus dorsi (LD), biceps brachii (BB), rectus femoris (RF), vastus medialis (VAM), vastus lateralis (VAL), biceps femoris (BF) and tibialis anterior (TA) muscles were recorded continuously during the tests together with other cardio-respiratory parameters: heart rate (HR), ventilation (VE), oxygen consumption (VO₂). On-water, subjects covered the same distance in a longer time (218.4 ± 3.8 s vs. 178.1 ± 5.6 s during ergometer test). TRS, LD, BB, RF, VAM and VAL muscle activation on-water was lower than off-water during the rowing race. VO₂ and VE responses were similar between the two conditions even if the time to complete the 1,000 m race simulation test was higher on-water. The results indicate that for most of the analyzed muscles EMG activation on the ergometer is higher than on-water with the maximal activity at the beginning of the on-water test due reasonably to overcome the forces opposing the forward motion, while the ergometer task elicited increasing muscle activation over time. The present data may be considered by coaches when choosing a rowing ergometer in substitution for the training on-water or when relying on the indoor tests to select the crew.

Reliability and Effect of Sodium Bicarbonate: Buffering and 2000-m Rowing Performance

Purpose:

The aim of this study was to determine the effect and reliability of acute and chronic sodium bicarbonate ingestion for 2000-m rowing ergometer performance (watts) and blood bicarbonate concentration [HCO3−].

Methods:

In a crossover study, 7 well-trained rowers performed paired 2000-m rowing ergometer trials under 3 double-blinded conditions: (1) 0.3 grams per kilogram of body mass (g/kg BM) acute bicarbonate; (2) 0.5 g/kg BM daily chronic bicarbonate for 3 d; and (3) calcium carbonate placebo, in semi-counterbalanced order. For 2000-m performance and [HCO3−], we examined differences in effects between conditions via pairwise comparisons, with differences interpreted in relation to the likelihood of exceeding smallest worthwhile change thresholds for each variable. We also calculated the within-subject variation (percent typical error).

Results:

There were only trivial differences in 2000-m performance between placebo (277 ± 60 W), acute bicarbonate (280 ± 65 W) and chronic bicarbonate (282 ± 65 W); however, [HCO3−] was substantially greater after acute bicarbonate, than with chronic loading and placebo. Typical error for 2000-m mean power was 2.1% (90% confidence interval 1.4 to 4.0%) for acute bicarbonate, 3.6% (2.5 to 7.0%) for chronic bicarbonate, and 1.6% (1.1 to 3.0%) for placebo. Postsupplementation [HCO3−] typical error was 7.3% (5.0 to 14.5%) for acute bicarbonate, 2.9% (2.0 to 5.7%) for chronic bicarbonate and 6.0% (1.4 to 11.9%) for placebo.

Conclusion:

Performance in 2000-m rowing ergometer trials may not substantially improve after acute or chronic bicarbonate loading. However, performances will be reliable with both acute and chronic bicarbonate loading protocols.

Differences in spinopelvic kinematics in sweep and scull ergometer rowing

OBJECTIVE

The spinopelvic kinematics of sweep and scull have yet to be investigated, despite evidence suggesting that sweep rowing may be provocative for low back pain (LBP). The aim of this study was to determine whether differences existed in spinopelvic kinematics in high-level rowers without LBP in sweep and scull ergometer rowing.

DESIGN

Repeated measures study.

SETTING

Institute of Sport Laboratory.

PARTICIPANTS

Ten high-level rowers.

INTERVENTIONS

Kinematics of the pelvis, lower lumbar, upper lumbar, and lower thoracic regions during the drive phase of the rowing stroke were measured while rowing on an interchangeable sweep/scull ergometer.

MAIN OUTCOME MEASURES

Total and segmental spinopelvic kinematics.

RESULTS

Sweep rowing showed greater lateral bend (P < 0.05) throughout the stroke, which was predominately due to movement of the upper lumbar and lower thoracic regions. Furthermore, sweep rowing displayed a greater magnitude (P < 0.05) of axial rotation at the catch (created at the pelvis). Both sweep and scull rowing showed values close to end range flexion for the lower lumbar spine at the catch and early drive phases. No difference (P > 0.05) was evident in lateral bend or axial rotation values for the lower lumbar region.

CONCLUSIONS

Some differences exist in spinopelvic kinematics between sweep and scull ergometer rowing. However, it may be speculated that the lack of differences in lateral bend and axial rotation at the lower lumbar spine in sweep rowing may represent an adaptive and protective approach of experienced rowers. This may be the focus of future research studies.