Intelligent Tool Design and Creative Behavior Analysis in Dance Composition Enabled by Mobile Interaction Technologies - Jiang, Yanjun (International Journal of Interactive Mobile Technologies (iJIM), 2026)
To advance the transition of dance composition from experience-driven practices to data-augmented and cognition-coordinated processes, a triadic model of mobile-interactive dance composition was proposed. Guided by this framework, a mobile intelligent composition tool integrating multimodal sensing and lightweight artificial intelligence (AI) was designed and implemented. A heterogeneous data fusion strategy combining an MPU9250 inertial measurement unit (IMU) with MediaPipe-based visual capture was adopted, achieving a three-dimensional reconstruction error below 2 cm and an interaction latency under 50 ms. A prototype implementation was developed and validated experimentally. A mixed experimental design involving 60 professional and non-professional dancers was conducted, incorporating a short single-segment creation task and a four-week longitudinal project. A cognitive load scale, a creative flow state scale, and eye-tracking measurements were employed to systematically compare the tool’s performance with that of Kinect and professional motion capture systems. The findings reveal a three-stage evolutionary pattern in dance creative behavior under tool intervention, characterized by enhanced efficiency, cognitive restructuring, and expressive innovation, demonstrating the tool’s comparative advantages in multiscene adaptability and operational simplicity. This study establishes an interdisciplinary paradigm coupling theoretical modeling, tool development, experimental validation, and behavioral analysis, offering both conceptual foundations and a transparent methodological pathway for integrating mobile intelligent technologies into creative practices. The proposed tool effectively addresses critical challenges in dance education, digital heritage preservation, and real-time interaction in immersive performance, thereby providing essential support for the scalable digital transformation of dance art.