Experimental study demonstrates automated bicycle fitting using dynamic joint tracking and physiological monitoring, highlighting real-time ergonomic personalization for product design.
Differences in anthropometry and physiology can be recorded and turned into design requirements using an automated decision-support system. Industry 4.0 technologies have enabled mass personalization, placing greater importance on studying user-product interactions. This work seeks to enable the study of human-product interactions in real time by creating an automated bicycle fitting system called the Personalized Automated Velo Experience (PAVE). The system compares dynamic joint angles to optimal ranges via an automated Response Surface Method (RSM) experiment. PAVE is validated using a Functional Threshold Power (FTP) test and a steady state test. At 2 min intervals heart rate and power are recorded and the rider rates their overall comfort, localized discomfort, and perceived exertion. During the FTP test sEMG signals are recorded and used to calculate fatigue. This study shows that Industry 4.0 can be leveraged to explore the physical interaction with a product before the design phase.
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Robison et al. (2026) studied this question.
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