Posture Tracking Meets Fitness Coaching: A Two-Phase Optimization Approach with Wearable Devices

Han Zhou, Yi Gao, Wenxin Liu, Yuefang Jiang, Wei Dong
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引用次数: 6

Abstract

Fitness training is becoming an increasingly popular way of maintaining overall health and preventing illness. However, in some cases the training could be risky and fitness-related injuries have increased by 48% in the USA. The training itself will not cause hurt, but if it is performed in a crucial-improper form (using the wrong technique), it will injure the exerciser. Research has explored the potential of using wearables to monitor fitness training, but the consideration of proper/improper form is not included. In this paper, we propose WearCoach, a wearable based fitness training assistant, which acquires the user’s fitness form information and generates real-time feedback during training. WearCoach differs from previous work of training assistant in 1) it employs a two-phase tracking algorithm to achieve accurate and real-time tracking of body motion, 2) it analyzes the captured arm posture and generates training guidance based on the user’s form, 3) it uses joint orientation as an exercise classification feature to improve recognition accuracy. We conducted experiments with eight participants and nine exercises. Three kinds of feedback are generated, including injury alert, movement correction and symmetry analysis.
姿势跟踪与健身指导:可穿戴设备的两阶段优化方法
健身训练正成为一种越来越受欢迎的保持整体健康和预防疾病的方式。然而,在某些情况下,这种训练可能是有风险的,在美国,与健身相关的伤害增加了48%。训练本身不会造成伤害,但如果以一种关键的不正确的形式进行(使用错误的技术),就会伤害锻炼者。研究已经探索了使用可穿戴设备监控健身训练的潜力,但没有考虑到合适/不合适的形式。在本文中,我们提出了WearCoach,一款基于可穿戴的健身训练助手,它可以获取用户的健身表单信息,并在训练过程中产生实时反馈。WearCoach与以往训练助手的不同之处在于:1)采用两阶段跟踪算法,实现对身体运动的准确实时跟踪;2)分析捕捉到的手臂姿势,并根据用户的形态生成训练指导;3)使用关节方向作为运动分类特征,提高识别精度。我们进行了8人实验和9个练习。产生三种反馈,包括损伤预警、运动修正和对称性分析。
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