5 accepted papers
Current passive or semi-active shoulder exoskeletons for overhead work provide fixed assistive torque for all participants and tasks, which lacks adaptability. In addition, due to the need to store energy at low elevation angles, they may increase physical demand on the user when assistance is not r
Current passive or semi-active shoulder exoskeletons for overhead work provide fixed assistive torque for all participants and tasks, which lacks adaptability. In addition, due to the need to store energy at low elevation angles, they may increase physical demand on the user when assistance is not r…
Graph Neural Network (GNN) has been widely applied in multivariate time series forecasting due to its excellent relationship modeling capabilities. However, current methods still face limitations in computational efficiency or time series expression capabilities. To address these issues, we propose…
Human-in-the-loop optimization (HILO) has been used to identify subject-specific assistive strategies and improve the performance of wearable exoskeletons. However, there is still a gap in research on HILO regarding knee exoskeleton flexion assistance. We present a HILO methodology that optimizes th
Trust prediction is a key issue in human-robot collaboration, especially in construction scenarios where maintaining appropriate trust calibration is critical for safety and efficiency. This paper introduces the Performance-guided Physiological signal-based Trust Prediction (PPTP), a novel framework