Riding a bicycle requires simultaneous balance and navigation, which may be difficult or even impossible for persons with disabilities. This may be partly alleviated by providing active balance and steering assistance to the rider. To achieve this assistance while still providing free maneuverability, it is necessary to know the position and intent of the rider on the bicycle. A human-bicycle contact force sensing system was developed to collect real-world data in a motion capture environment. Applying the newly obtained force and motion data to existing human-bicycle interaction models will grant additional insight for developing a human-in-the loop bicycle control system.