Abstract
Proper stroke posture and rhythm are crucial for kayakers to achieve perfect performance and avoid the occurrence of sport injuries. The traditional video-based analysis method has numerous limitations (e.g., site and occlusion). In this study, we propose a systematic approach for evaluating the training performance of kayakers based on the multiple sensors fusion technology. Kayakers’ motion information is collected by miniature inertial sensor nodes attached on the body. The extend Kalman filter (EKF) method is used for data fusion and updating human posture. After sensor calibration, the kayakers’ actions are reconstructed by rigid-body model. The quantitative kinematic analysis is carried out based on joint angles. Machine learning algorithms are used for differentiating the stroke cycle into different phases, including entry, pull, exit and recovery. The experiment shows that our method can provide comprehensive motion evaluation information under real on-water scenario, and the phase identification of kayaker’s motions is up to 98% validated by videography method. The proposed approach can provide quantitative information for coaches and athletes, which can be used to improve the training effects.
Highlights
DominguesAs a multi-cycle high-intensity water sports project, kayak includes single boat, double boat, four-person boat and obstacle slalom formats
We present a systematic method for athlete’s motion capture and kinematic analysis
The customizable rigid model is used to demonstrate the kayaker’s posture, and each segment attitude of the whole-body is iteratively calculated by the quaternization vector multiplication
Summary
DominguesAs a multi-cycle high-intensity water sports project, kayak includes single boat, double boat, four-person boat and obstacle slalom formats. The athlete sits in the boat, facing forward, holding the paddle with oar handle on the middle position, relying on the feet to steer the rudder to control the course. Professional teams and amateur clubs are constantly looking for advanced methods to help athletes improve their athletic performance [1,2,3]. Other studies have been devoted to the creation of instrumented boats to assess rowers’ performance by measuring oar’s power and motion [5]. Henry et al used strain gauges and potentiometers to measure the forces on the oars and their angular positions to assess rowing performance by power output [7]. Stroke frequency, stroke force and power output of athletes are evaluated, the standardization and normalization of rowing motion are not studied to fundamentally improve the kayaker’s technique
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