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

翻译：羽毛球运动表现评估通常依赖专业教练指导，而业余爱好者鲜少能获得此类资源。本文提出BadminSense——基于可穿戴感知的智能手表系统，用于实现精细化的羽毛球运动表现分析。通过对经验丰富的羽毛球运动员进行访谈，我们确定了四项系统设计需求及其三项实施要点，以指导BadminSense的开发。随后，我们采集了12名经验丰富的羽毛球业余爱好者的击球数据集，并标注了精细标签，包括击球类型、专家评定的击球等级以及击球落点。基于该数据集，BadminSense利用商用智能手表的振动信号，实现击球动作的分割与分类、击球质量预测及击球落点估计。实验评估表明，该系统在击球分类准确率、击球质量评分与专家评分的一致性，以及落点定位精度方面均表现优异。