A Novel Training Bike and Camera System to Evaluate Pose of Cyclists

Abstract

Aerodynamic drag force can account for up to 90% of the opposing force experienced by a cyclist. Therefore, aerodynamic testing and efficiency is a priority in cycling. An inexpensive method to optimize performance is required. In this study, we evaluate a novel indoor setup as a tool for aerodynamic pose training. The setup consists of a bike, indoor home trainer, camera, and wearable inertial motion sensors. A camera calculates frontal area of the cyclist and the trainer varies resistance to the cyclist by using this as an input. To guide a cyclist to assume an optimal pose, joint angles of the body are an objective metric. To track joint angles, two methods were evaluated: optical (RGB camera for the two-dimensional angles in sagittal plane of 6 joints), and inertial sensors (wearable sensors for three-dimensional angles of 13 joints). One (1) male amateur cyclist was instructed to recreate certain static and dynamic poses on the bike. The inertial sensors provide excellent results (absolute error = 0.28°) for knee joint. Based on linear regression analysis, frontal area can be best predicted (correlation > 0.4) by chest anterior/posterior tilt, pelvis left/right rotation, neck flexion/extension, chest left/right rotation, and chest left/right lateral tilt (p < 0.01).

Opportunities and Current Obstacles to Use MOVE4D for Cycling Analysis

“…In this white paper, the opportunities and current obstacles to using the Move 4D markerless motion tracking system (Instituto de Biomecánica de Valencia-IBV), for capturing human product interactions are discussed. Three-dimensional real-time motion tracking using marker-based systems is currently used to evaluate cyclists': 1) upper body positioning, 2) trunk stability, and 3) lower limb symmetry and kinematics [1,4]. However, MOVE4D's markerless photogrammetry-based 4D scanning system creates new opportunities and increased flexibility for cyclists' performance assessments.…”