Dexterous finger movements are critical for both everyday and specialized tasks. However, acquiring such skills is challenging, as it requires accurate sequence memory and fine finger coordination. Existing haptic training systems typically employ demonstration feedback, which physically guides correct movements, or post-error correction that intervenes after errors occur. While effective, these approaches can reduce learners’ autonomy or expose novices to repeated errors, which can harm motivation. We introduce FIXical I/O, a magnetic hand exoskeleton that enables three error feedback strategies by combining real-time motion sensing with electromagnet-based actuation: Preemptive Error Correction (nudging fingers away from incorrect actions), Preemptive Error Blocking (constraining erroneous movements before execution), and Post-Error Correction. We conducted a user study comparing these strategies in terms of learning performance and subjective experiences, such as perceived performance and sense of agency, thereby demonstrating the benefits of Preemptive Error Correction and providing design implications.
ACM CHI Conference on Human Factors in Computing Systems