PhD Defence Aswin Balasubramaniam | Disentangling Runner Drone Interaction Potentialities

Disentangling Runner Drone Interaction Potentialities

Aswin Balasubramaniam is a PhD student in the department Human Media Interaction. (Co)Promotors are prof.dr. D.K.J. Heylen and dr.ir. D. Reidsma from the faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), University of Twente.

This dissertation is part of a larger project that aims to build a novel interactive platform for monitoring runners and providing feedback capable of transformatively impacting running practices to improve performance and prevent injuries. To realize this goal, I reviewed the existing landscape of running interaction technology, which revealed that drones remain a largely underexplored opportunity within this field. While prior research highlights the technical promise of drones, little work has substantiated their use or examined their specific utility and limitations for supporting runners. To address this gap, I systematically disentangle the potential of runner-drone interaction, focusing on user-centered design principles to uncover how drones can support runners’ goals and expectations, and to identify effective strategies for their integration.

Structured in four parts, this dissertation investigates these potentialities from the perspectives of the drone, the runner, and their interaction. In the first part, I examined the technical feasibility of using an off-the-shelf drone to accompany runners in user studies, which included battery load tests and benchmark studies comparing key running parameters estimated using drone-captured video with established running monitoring systems.

In the second part, I investigated runners’ expectations and requirements when running with a drone. An experiential study showed that most runners prefer drones as coaching companions providing actionable feedback and identified the factors influencing their experience. To further analyze this preference, I introduced a dedicated framework to guide a bodystorming study, enabling runners to reflect on their feedback needs. These insights informed ideation sessions in which runners proposed how drones could deliver feedback that aligns with their reflections and preferences. Together, these studies shaped the design considerations for effective runner-drone interaction, highlighting instructive auditory feedback as one of the most popular preferences.

The third part presents the design and validation of interactive auditory feedback. A systematic review of audio use in running research informed the exploration of movement error sonification and reinforcement learning techniques to guide feedback design. Building on these foundations, I designed an interactive system where stride length error modulates the volume of characteristic drone noises overlaid with music. Empirical validation in a controlled treadmill setting demonstrated that this feedback enables real-time adjustment of stride length, laying the foundation for further research on drone-mediated running feedback in naturalistic settings.

In the final part, I reflect on broader future research directions for runner-drone interaction. The concluding chapter outlines research avenues for advancing interactive drone platforms to support runners and discusses the practical and ethical challenges of real-world deployment. Taken together, this dissertation establishes a foundation for continued research on integrating drone technologies into running and highlights new opportunities for employing interactive aerial systems within the broader sphere of sports