Human Digital Biomechanical Twin-Driven Ergonomic Optimization of Bass-Guitar Support Systems: Predictive Design and Experimental Validation

Playing-related musculoskeletal disorders (PRMDs) are highly prevalent among bass-guitar players due to sustained asymmetrical postures, repetitive finger movements, and prolonged support of instrument weight. This study proposes a Human Digital Biomechanical Twin-driven, simulation-based approach to optimize bass-guitar support systems, integrating biomechanical modelling, motion capture, and musculoskeletal simulation. A preliminary survey among 63 Italian bass-guitar players was performed to define the experimental conditions regarding posture, instrument type, and session duration. Fifteen experienced bassists participated in laboratory trials using motion capture and postural assessment tools, including MediaPipe Pose, RULA, and AnyBody Modelling System. Baseline results highlighted significant activation of the trapezius and spinal extensor muscles (19–26% MVC), confirming high ergonomic risk. Three alternative support configurations were digitally simulated, revealing that a three-point harness system (bilateral shoulder straps plus thoracic anchoring) reduced spinal stabilizer activation by 15–25% across four anthropometric percentiles. Experimental validation confirmed enhanced comfort, reduced fatigue, and improved instrument stability, with the majority of participants preferring the ergonomic configuration. These findings demonstrate the feasibility of a simulation-based, prospective, and human-centred ergonomic design framework, offering a scalable methodology to compare and optimize adaptive instrument-support systems before physical prototyping.