Evaluating corticokinematic coherence using electroencephalography and human pose estimation

Objective.While peripheral mechanisms of proprioception are well understood, the cortical processing of its feedback during dynamic and complex movements remains less clear. Corticokinematic coherence (CKC), which quantifies the coupling between limb movements and sensorimotor cortex activity, offers a way to investigate this cortical processing. However, ecologically valid CKC assessment poses technical challenges. Thus, by integrating Electroencephalography (EEG) with Human Pose Estimation (HPE), this study validates the feasibility and validity of a novel methodology for measuring CKC during upper-limb movements in real-world and virtual reality (VR) settings.Approach.Nine healthy adults performed repetitive finger-tapping (1 Hz) and reaching (0.5 Hz) tasks in real and VR settings. Their execution was recorded temporally synchronized using a 64-channel EEG, optical marker-based motion capture, and monocular deep-learning-based HPE via Mediapipe. Alongside the CKC, the kinematic agreement between both systems was assessed.Main results.CKC was detected using both marker-based and HPE-based kinematics across tasks and environments, with significant coherence observed in most participants. HPE-derived CKC closely matched marker-based measurements for most joints, exhibiting strong reliability and equivalent coherence magnitudes between real and VR conditions.Significance.This study validates a noninvasive and portable EEG-HPE approach for assessing cortical proprioceptive processing in ecologically valid settings, enabling broader clinical and rehabilitation applications.