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Pilot study reveals improved breathing regularity and tracking accuracy with real-time visual guidance in healthy volunteers, indicating feasibility for upright particle therapy.
OBJECTIVE: To develop and evaluate a real-time optical respiratory guidance framework for upright particle therapy, focusing on respiratory regularity, guided-task performance, posture-dependent effects, and participant-specific task fit. Approach: A real-time guidance platform was implemented using optical motion tracking as the primary analytic channel, integrated with a Unity-based visual guidance interface and auxiliary pressure-belt and Anzai reference signals. After phantom-based assessment of cross-system consistency, eleven healthy volunteers completed breathing tasks under guided feedback, guided no-feedback, and no-target conditions in upright and supine postures. Outcomes included target-following performance, respiratory regularity, and posture-related respiratory organization. Main results: Phantom-based validation showed low residual bias and sub-millimetre error between reference-aligned optical tracking systems. In the volunteer study, real-time feedback improved guided-task performance relative to guided no-feedback, with lower follow error and greater time spent within the acceptable green band. Guided breathing improved respiratory regularity relative to no-target condition breathing, with lower period variability and higher cycle similarity. Posture did not produce a simple global performance difference, but it reshaped thoracoabdominal organization, with greater abdominal dominance in supine than in upright posture. Significance: The proposed framework supports synchronized, human-in-the-loop respiratory guidance for upright particle-therapy workflows. By combining real-time motion-derived feedback with posture-aware task execution, this pilot study provides evidence that respiratory guidance can be designed not only as a monitoring tool, but also as an interactive support strategy for clinically relevant motion-management workflows. These findings motivate future work on external--internal motion mapping, gating efficiency, treatment-session robustness, and prospective personalization of both target definition and interface design.
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Chen et al. (2026) studied this question.
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