论文标题
为游戏化健身框架设计即时检测
Designing Just-in-Time Detection for Gamified Fitness Frameworks
论文作者
论文摘要
本文介绍了我们从多年的努力中提出的发现，以在现实环境中使用惯性传感器提早检测运动事件。我们认为，早期事件检测是推进运动跟踪的下一步，并且可以实现及时的干预措施，尤其是对于MHealth应用程序。我们的系统针对健身域中的力量训练锻炼，在佩戴惯性传感器的同时，用户为每次锻炼执行明确的运动。我们在26个月内收集了12个用户的20个练习的数据。我们提出了一种算法在结束之前检测重复的算法，以允许用户实时可视化移动派生的指标。我们进一步开发了一种游戏方法，以向用户显示此信息并鼓励他们执行一致的动作。一项可行性研究的参与者发现，游戏反馈有助于改善其形式。我们的系统可以在结束前500毫秒之前检测重复事件，比最新的跟踪器快2倍，更准确。我们认为，我们的方法将为健身框架的跟踪，检测和游戏化开辟令人兴奋的途径。
This paper presents our findings from a multi-year effort to detect motion events early using inertial sensors in real-world settings. We believe early event detection is the next step in advancing motion tracking, and can enable just-in-time interventions, particularly for mHealth applications. Our system targets strength training workouts in the fitness domain, where users perform well-defined movements for each exercise, while wearing an inertial sensor. We collect data for 20 exercises across 12 users over 26 months. We propose an algorithm to detect repetitions before they end, to allow a user to visualize movement derived metrics in real-time. We further develop a gamified approach to display this information to the user and encourage them to perform consistent movements. Participants in a feasibility study find the gamified feedback useful in improving their form. Our system can detect repetition events as early as 500 ms before it ends, which is 2x faster and more accurate than state-of-the-art trackers. We believe our approach will open exciting avenues for tracking, detection, and gamification for fitness frameworks.
