基于9轴传感器的个人训练运动精度决定因子提取程序的开发

Hyeong-Seok Kim, Seung-Taek Oh, Jae-Hyun Lim
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引用次数: 0

摘要

最近,为保持和改善健康而坚持锻炼的人越来越多。特别是,人们对没有空间限制、可以在短期内最大化锻炼效果的个人训练(PT)非常感兴趣。然而,在进行PT运动时,保持准确的运动姿势对于预防损伤和提高运动效果至关重要。本研究设计并实现了一个运动提取程序,该程序通过附着在用户身体上的多个9轴运动传感器来获取和分析运动数据,并支持对每次运动的准确性判断。该程序通过将9-aix运动传感器连接到人体的各个部位,收集每个x、y和z轴的加速度、陀螺仪和磁力计数据。然后选择运动中伴随多个动作的预备、中间和结束姿势的特定间隔,计算基于四元数数据的欧拉角。欧拉角是从重要角度保持的运动中提取的主要身体部位的欧拉角,并将其计算为每个运动因子,用于PT运动精度判断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of 9-Axis Sensor-Based Motion Extraction Program for Generating a Motion Accuracy Determination Factor of the Personal Training
People steadily exercising for health maintenance and improvement are recently on the rise. Especially, people are highly interested in personal training (PT) that has no spatial restriction and that can maximize exercise effects for the short-term. However, it is important to maintain accurate exercise postures to prevent injuries and improve exercise effects in doing PT exercise. This study designs and implements a motion extraction program in which motion data can be acquired and analyzed through multi 9-axis motion sensors attached to user's body and accuracy judgement can be supported for each exercise. The proposed program collects the acceleration, gyro, and magnetometer data of each x, y, and z axis by attaching 9-aix motion sensors to various parts of human body. And Then selects specific intervals on preparatory, intermediate, and finishing postures accompanied using many movements in exercise, and calculates quaternion data-based Euler angles. Euler angles are extracted from major body parts in terms of exercises in which angle maintenance is important, and they are calculated as each exercise factor that can be used for PT exercise accuracy judgment.
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