Urban mobility increasingly prioritizes sustainable and user-friendly transportation solutions, driving the need for advancements in vehicle design that enhance both efficiency and rider comfort. This paper presents the methodological framework with empirical validation of the A-Mover project, which aims to develop a high-autonomy electric motorcycle optimized for comfortable, efficient, and eco-friendly urban mobility. As a part of a multidisciplinary network, this study focuses on research related to vehicle ergonomics. To assess ergonomic conditions, a single data collection was conducted with experience motorcycle in urban environments. The study integrates biomechanical sensors and artificial intelligence software to evaluate rider posture and emotional responses. Data collection includes: (a) kinematic measurements from high-precision accelerometers, (b) physiological indicators such as heart rate, (c) ergonomic analysis of both the motorcycle and rider, (d) subjective assessments of comfort and posture, and (e) facial emotion recognition. The collected data will offer preliminary insights to support future recommendations for improving rider comfort and safety, health, and well-being through multidisciplinary analysis and innovative technologies.