Tac-Trainer: A Visual Analytics System for IoT-based Racket Sports Training

Jiachen Wang, Ji Ma, Kangping Hu, Zheng Zhou, Hui Zhang, Xiao Xie, Yingcai Wu

View presentation:2022-10-20T16:33:00ZGMT-0600Change your timezone on the schedule page
2022-10-20T16:33:00Z
Exemplar figure, described by caption below
Tac-Trainer contains a training view and a suggestion view. The training view visualizes the strokes in a training session through a customized flow (C) consisting of a metadata panel (A), a control panel (B), and a stroke flow (F). The suggestion view provides a list of optimization suggestions (J) for a poorly-performed stroke (G). Each suggestion can be explored in a 3-D coordinate (K). The interface presents the details of Case 1. E is the first training session and D is the second. G is the stroke chosen for optimization. L is the optimization suggestion chosen by the coach.

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Abstract

Conventional racket sports training highly relies on coaches' knowledge and experience, leading to biases in the guidance. To solve this problem, smart wearable devices based on Internet of Things technology (IoT) have been extensively investigated to support data-driven training. Considerable studies introduced methods to extract valuable information from the sensor data collected by IoT devices. However, the information cannot provide actionable insights for coaches due to the large data volume and high data dimensions. We proposed an IoT + VA framework, Tac-Trainer, to integrate the sensor data, the information, and coaches' knowledge to facilitate racket sports training. Tac-Trainer consists of four components: device configuration, data interpretation, training optimization, and result visualization. These components collect trainees' kinematic data through IoT devices, transform the data into attributes and indicators, generate training suggestions, and provide an interactive visualization interface for exploration, respectively. We further discuss new research opportunities and challenges inspired by our work from two perspectives, VA for IoT and IoT for VA.