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Scaling, to remove the effects of body size, is an important methodological approach for enabling an equitable comparison of performance differences between individuals who vary in anthropometric characteristics. Many previous studies using scaling in sport have done so based on only one or two anthropometric characteristics, with only one study to date adopting a three‐dimensional approach. To apply a three‐dimensional allometric model to rowing ergometer performance (REP) in adolescents, and to detect whether key ‘scaling’ parameters remain stable when scaling REP both before and after a 6‐week training intervention. Novel three‐dimensional allometric models were used, incorporating body mass, stature and waist circumference (WC) to detect the most appropriate body size dimension(s) and scaling parameters associated with REP before and after a 6‐week training intervention. Using this more flexible and sensitive three‐dimensional allometry demonstrated that, following 6‐weeks of training, there was a change in the ideal body shape associated with REP. Before training, taller, but not heavier, adolescents performed better. After 6‐weeks of training, older participants with a greater body mass but smaller WC performed better. Scaling approaches are important for evaluating performance differences between individuals of differing body size. The findings from the current study (using a novel three‐dimensional allometry approach) emphasise that relatively subtle changes in individuals' behavioural characteristics, such as changes in their training/fitness status, can result in quite dramatic changes in the body dimension characteristics and scaling parameters deemed to be key for performance in activities such as REP. Highlights This study examined three‐dimensional allometric models of rowing ergometer performance (REP) before and after a 6‐week rowing training intervention. At baseline, stature was the most important determinant of REP. Following a 6‐week training intervention, the three‐dimensional allometric model revealed a positive effect of body mass and negative effect of waist circumference on REP. These findings highlight that allometric models are sensitive to changes over time, even in response to a relatively modest 6‐week training intervention.

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.

Objective. The purpose of the current study was to confirm the unexpected similarities among progressive oxygen uptake (VO 2), heart rate (HR), and lactate ( L a) responses between cycle and rowing ergometry. Design. Eight recreationally active adults performed two progressive submaximal testing protocols, separated by 2–7 days. Subjects completed 3-min stages at 50, 100, and 150 W on both a cycle and rowing ergometer. VO 2 and HR were recorded every 30 s. At the conclusion of each 3-min stage, blood lactate was measured. Main outcome measures. For each variable, a repeated measures two-way (mode by intensity) factorial ANOVA was used to determine main effects for mode, intensity, and interaction. Results. There was no significant main effect ( p>0.05) for mode on VO 2 (cycle M=25.88±2.96 ml kg −1 min −1, rowing M=25.94±2.74), HR (cycle M=136.75±10.27 b min −1, rowing M=135.30±9.08), or L a (cycle M=4.34±1.06 mmol l −1, rowing M=3.78±98). Conclusions. Results of the current study provide evidence that cycling and rowing exercise may be used interchangeably during rehabilitation.

The rowing technique is a key factor in the overall rowing performance. Nowadays the athletes’ performance is so advanced that even small differences in technique can have an impact on sport competitions. To further improve the athletes’ performance, individualized rowing is necessary. This can be achieved by intelligent measurement technology that provides direct feedback. To address this issue, we developed a novel wireless rowing measurement system (WiRMS) that acquires rowing movement and measures muscle activity using electromyography (EMG). Our measurement system is able to measure several parameters simultaneously: the rowing forces, the pressure distribution on the scull, the oar angles, the seat displacement and the boat acceleration. WiRMS was evaluated in a proof-of-concept study with seven experienced athletes performing a training on water. Evaluation results showed that WiRMS is able to assess the rower’s performance by recording the rower’s movement and force applied to the scull. We found significant correlations (p < 0.001) between stroke rate and drive-to-recovery ratio. By incorporating EMG data, a precise temporal assignment of the activated muscles and their contribution to the rowing motion was possible. Furthermore, we were able to show that the rower applies the force to the scull mainly with the index and middle fingers.

Analyzing performance in rowing, e.g., analyzing force and power output profiles produced either on ergometer or on boat, is a priority for trainers and athletes. The current state-of-the-art methodologies for rowing performance analysis involve the installation of dedicated instrumented equipment, with the most commonly employed systems being PowerLine and BioRow. This procedure can be both expensive and time-consuming, thus limiting trainers’ ability to monitor athletes. In this study, we developed an easier-to-install and cheaper method for estimating rowers’ forces and powers based only on cable position sensors for ergometer rowing and inertial measurement units (IMUs) and GPS for scull rowing. We used data from 12 and 11 rowers on ergometer and on boat, respectively, to train a long short-term memory (LSTM) network. The LSTM was able to reconstruct the forces and power at the gate with an overall mean absolute error of less than 5%. The reconstructed forces and power were able to reveal inter-subject differences in technique, with an accuracy of 93%. Performing leave-one-out validation showed a significant increase in error, confirming that more subjects are needed in order to develop a tool that could be generalizable to external athletes.

Despite the high prevalence of low back pain (LBP) in rowers, there are few studies investigating changes in lumbar muscle activation in rowers with a recent history of LBP. Such knowledge is relevant to understand potential mechanisms contributing to the maintenance and recurrence of LBP in rowers. For the first time, we evaluate the spatial distribution of erector spinae (ES) activity in rowers with and without a recent history of LBP, using a novel application of high-density surface electromyography (HDEMG). Cross-sectional study. Asymptomatic rowers (N=10) and rowers with a recent history of LBP (N=8) performed 7×4-min exercise bouts (rowing ergometer) until volitional exhaustion. HDEMG signals were acquired bilaterally over the lumbar ES and the root mean square (RMS) amplitude and entropy were analyzed. In addition, the y-axis coordinate of the barycentre (RMS-map) was used to assess changes in ES spatial activation. As the load increased, rowers with LBP showed higher amplitude (p<0.01) and less complexity (entropy) of the HDEMG signals (p<0.001). In addition, rowers with LBP showed opposite displacements of the barycentre, specifically showing a caudal shift of muscle activity at high intensities (p<0.001). Both the magnitude of activation and distribution of ES activity were altered in rowers with a recent history of LBP. The lower complexity of signals together with the caudal displacements of the barycentre suggest an inefficient recruitment of the ES as the load progressed. Modification of the rowing technique in conjunction with feedback from HDEMG might prove useful in future studies.

Rowing ergometers are popular tools for general fitness and competitive crew teams. The effect of the equipment set up on the rowing stroke has received limited attention. This study aimed to determine the effects of altering the foot-stretcher position on rowing kinematics across different stroke rates. Eleven college-level rowers took part in this study. A rowing ergometer was modified to allow the height and angle of the foot-stretcher to be adjusted. Seven foot-stretcher positions were tested, each at rates of 22, 26, and 32 strokes per minute. Sagittal plane kinematic waveforms were compared between conditions for all major joints using statistical parametric mapping, and temporal variables were assessed ( p < 0.05). Stroke rate was found to affect kinematic patterns for all joints. The effect of the foot-stretcher position was limited to the ankle and hip. Similarly, the timing of events during the rowing stroke was affected by the stroke rate, but not foot position. These results indicate that while some limited changes to the stroke technique can be caused by altering the foot-stretcher position, the changes were largely compensated for by the rowers and are generally smaller than differences between stroke rates.

Measuring brain activity in moving subjects is of great importance for investigating human behavior in ecological settings. For this purpose, EEG measures are applicable; however, technical modifications are required to reduce the typical massive movement artefacts. Four different approaches to measure EEG/ERPs during rowing were tested: (i) a purpose-built head-mounted preamplifier, (ii) a laboratory system with active electrodes, and a wireless headset combined with (iii) passive or (iv) active electrodes. A standard visual oddball task revealed very similar (within subjects) visual evoked potentials for rowing and rest (without movement). The small intraindividual differences between rowing and rest, in comparison to the typically larger interindividual differences in the ERP waveforms, revealed that ERPs can be measured reliably even in an athletic movement such as rowing. On the other hand, the expected modulation of the motor-related activity by force output was largely affected by movement artefacts. Therefore, for a successful application of ERP measures in movement research, further developments to differentiate between movement-related neuronal activity and movement-related artefacts are required. However, activities with small magnitudes related to motor learning and motor control may be difficult to detect because they are superimposed by the very large motor potential, which increases with force output.

In rowing, perfect synchronisation is important for optimal performance of a crew. Remarkably, a recent study on ergometers demonstrated that antiphase crew coordination might be mechanically more efficient by reducing the power lost to within-cycle velocity fluctuations of the boat. However, coupled oscillator dynamics predict the stability of the coordination to decrease with increasing stroke rate, which in case of antiphase may eventually yield breakdowns to in-phase. Therefore, this study examined the effects of increasing stroke rate on in- and antiphase crew coordination in rowing dyads. Eleven experienced dyads rowed on two mechanically coupled ergometers on slides, which allowed the ergometer system to move back and forth as one 'boat'. The dyads performed a ramp trial in both in- and antiphase pattern, in which stroke rates gradually increased from 30 strokes per minute (spm) to as fast as possible in steps of 2 spm. Kinematics of rowers, handles and ergometers were captured. Two dyads showed a breakdown of antiphase into in-phase coordination at the first stroke rate of the ramp trial. The other nine dyads reached between 34-42 spm in antiphase but achieved higher rates in in-phase. As expected, the coordinative accuracy in antiphase was worse than in in-phase crew coordination, while, somewhat surprisingly, the coordinative variability did not differ between the patterns. Whereas crew coordination did not substantially deteriorate with increasing stroke rate, stroke rate did affect the velocity fluctuations of the ergometers: fluctuations were clearly larger in the in-phase pattern than in the antiphase pattern, and this difference significantly increased with stroke rate. Together, these results suggest that although antiphase rowing is less stable (i.e., less resistant to perturbation), potential on-water benefits of antiphase over in-phase rowing may actually increase with stroke rate.

Wind braked rowing ergometers are used worldwide for training and testing of rowers, but data on validity and reliability of the calculated mechanical power output are scarce. Studies published so far are based on data generated by human rowers, inevitably adding biological variability without any option to clamp particular variables like stroke structure or force. To this end, we developed a test rig for rowing ergometers aiming to generate valid and reliable stroke structures (i.e. force–displacement curves). Briefly, the rig consists out of a frame connected to the ergometer. The handlebar of the rowing ergometer is attached to a sledge that can be displaced on a linear drive by a motor that is controlled by torque curves which are derived from elite rowers. A load cell between handlebar and chain and an incremental linear transducer allow criterion measures of force and distance of displacement to calculate mechanical power output. To evaluate the validity of the machine generated force–displacement curves, three different stroke structures were compared to the respective human reference curves. To evaluate reliability, series of 50 consecutive strokes were performed for 10 times. Validity of the curves was indicated by small differences in stroke-force, -distance, and -work (≤ |−7.8|%) between machine generated and human generated curves. Mean power output of the test series was 445 ± 1 W with a coefficient of variation of 0.53% between series. Hence, the test rig allows to generate valid and reliable rowing strokes on wind braked rowing ergometers.