[2603.21825] BadminSense: Enabling Fine-Grained Badminton Stroke Evaluation on a Single Smartwatch

Computer Science > Human-Computer Interaction arXiv:2603.21825 (cs) [Submitted on 23 Mar 2026] Title:BadminSense: Enabling Fine-Grained Badminton Stroke Evaluation on a Single Smartwatch Authors:Taizhou Chen, Kai Chen, Xingyu Liu, Pingchuan Ke, Zhida Sun View a PDF of the paper titled BadminSense: Enabling Fine-Grained Badminton Stroke Evaluation on a Single Smartwatch, by Taizhou Chen and 4 other authors View PDF HTML (experimental) Abstract:Evaluating badminton performance often requires expert coaching, which is rarely accessible for amateur players. We present adminSense, a smartwatch-based system for fine-grained badminton performance analysis using wearable sensing. Through interviews with experienced badminton players, we identified four system design requirements with three implementation insights that guide the development of BadminSense. We then collected a badminton strokes dataset on 12 experienced badminton amateurs and annotated it with fine-grained labels, including stroke type, expert-assessed stroke rating, and shuttle impact location. Built on this dataset, BadminSense segments and classifies strokes, predicts stroke quality, and estimates shuttle impact location using vibration signal from an off-the-shelf smartwatch. Our evaluations show that Subjects: Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI) Cite as: arXiv:2603.21825 [cs.HC]   (or arXiv:2603.21825v1 [cs.HC] for this version)   https://doi.org/10.48550/arXiv.2603.21825 Focus t...