Motor learning improvement by matching visual-haptic error modulation to individual skill level and motivation

Motor learning plays a critical role in psychology, sports science, and neurorehabilitation. However, translating its principles into effective rehabilitation strategies remains a significant challenge. This study established a psychologically informed framework based on the Challenge Point Hypothesis to guide the design of personalized visual-haptic feedback in robot-assisted rehabilitation. We proposed the MISLM algorithm, which matches visual-haptic error modulation to individual skill levels and motivation to determine the optimal difficulty level. In Session 2, eleven participants were recruited to determine the MISLM algorithm threshold using multiple linear regression. Session 1 and Session 3 involved sixty participants and aimed to compare the effectiveness of five non-matching visual-haptic error modulation strategies with the MISLM algorithm in a trajectory-tracking task. Motor learning and motivation were assessed using average tracking error and the Intrinsic Motivation Inventory (IMI). Results showed that all groups demonstrated significant improvements in motor learning and skill transfer in the long-term assessment. However, only the VRHA, VAHA, and MISLM groups showed significant enhancements in perceived competence, with the VRHA group showing a significantly greater improvement than the VAHR group. These findings highlight the importance of psychological mechanisms in the process of motor learning, and demonstrate the potential of MISLM algorithm in optimizing motor learning and engagement. This study establishes an adaptive training framework that integrates motor learning and psychological theory with practical applications in rehabilitation and sports training.