A Proof-of-Concept Framework for Upper-Limb Segment Definition and Joint Angle Computation Using Marker-Based Motion Capture

Marker-based motion capture systems are widely used to estimate joint kinematics, yet their accuracy depends strongly on how anatomical segments and coordinate systems are defined. This proof-of-concept study aimed to describe and technically evaluate a structured and reproducible framework for upper-limb segment definition and joint-angle computation. Reflective markers were placed on anatomical landmarks of the trunk and upper limbs, and joint angles were computed using custom-developed MATLAB R2022b (MathWorks, Natick, MA, USA) routines. Baseline-corrected model-derived joint angles were compared with composite reference measurements obtained using a universal manual goniometer and a twin-axis biosignalsplux goniometer under predefined static conditions in two adult participants. Side-specific mean absolute error values ranged from 0.80° to 5.24°, while root mean square error values ranged from 0.86° to 5.24°. The largest discrepancies were observed during maximum wrist extension and left maximum radial deviation. The evaluated static observations showed close correspondence in several joint positions, although larger discrepancies occurred in selected end-range wrist positions. Given the limited sample, single recordings, and controlled static conditions, these findings should be interpreted as an initial demonstration of technical feasibility rather than evidence of generalisable validity or repeatability. The explicit framework provides a basis for further evaluation using larger samples, repeated marker applications, repeated trials, and dynamic multi-planar upper-limb tasks.