Biomechanical analysis of the effectiveness of the stroke technique in athletes of different qualifications in rowing
Year: 2025
Type: article
Study design: Observational Study
Abstract: This study aims to analyze the biomechanical characteristics of the rowing stroke among athletes with different experience levels. Using motion analysis and inertial sensors, we examined key parameters such as joint angles, stroke synchronization, stroke length, and movement variability. The study involved two groups: experienced rowers (≥5 years of training) and novice rowers (≤2 years of training). High- speed video analysis (240 fps) and inertial measurement units (IMU) were used to collect data on knee and hip joint angles, stroke synchronization (ms), and stroke length (cm). Data were analyzed to compare the stability and effectiveness of the rowing technique between the two groups. The results showed that experienced rowers demonstrated a more stable technique with optimal knee and hip joint angles (47° and 90°, respectively) compared to novices (60° and 75°). Stroke synchronization was significantly better in experienced athletes (<50 ms delay), whereas novices had delays of up to 150 ms, indicating inefficient power transfer. The average stroke length was also longer in experienced rowers (170–190 cm) compared to novices (150–165 cm). Furthermore, movement variability was lower in experienced athletes (<5%) compared to novices (10–15%), suggesting better control and consistency. These findings highlight the importance of proper biomechanical training in rowing. Improving joint angles, optimizing stroke synchronization, and increasing stroke length can enhance performance. The study suggests that motion analysis tools can be effectively used to refine rowing technique, making training more precise and individualized. Future research should explore the impact of training interventions on technique stability and investigate muscle activation patterns during the rowing stroke.
Authors: M. V. Malikov, V.O. Tyshchenko, A. V. Symonik, D.O. Sylantiev
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409865859