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一种用于实时运动监测和姿势矫正的便携式智能健身套件。

A Portable Smart Fitness Suite for Real-Time Exercise Monitoring and Posture Correction.

机构信息

Knowledge Unit of System and Technology, University of Management and Technology, Sialkot 51310, Pakistan.

Department of Computer Science and Engineering, Università di Bologna, 40126 Bologna, Italy.

出版信息

Sensors (Basel). 2021 Oct 8;21(19):6692. doi: 10.3390/s21196692.

Abstract

Fitness and sport have drawn significant attention in wearable and persuasive computing. Physical activities are worthwhile for health, well-being, improved fitness levels, lower mental pressure and tension levels. Nonetheless, during high-power and commanding workouts, there is a high likelihood that physical fitness is seriously influenced. Jarring motions and improper posture during workouts can lead to temporary or permanent disability. With the advent of technological advances, activity acknowledgment dependent on wearable sensors has pulled in countless studies. Still, a fully portable smart fitness suite is not industrialized, which is the central need of today's time, especially in the Covid-19 pandemic. Considering the effectiveness of this issue, we proposed a fully portable smart fitness suite for the household to carry on their routine exercises without any physical gym trainer and gym environment. The proposed system considers two exercises, i.e., T-bar and bicep curl with the assistance of the virtual real-time android application, acting as a gym trainer overall. The proposed fitness suite is embedded with a gyroscope and EMG sensory modules for performing the above two exercises. It provided alerts on unhealthy, wrong posture movements over an android app and is guided to the best possible posture based on sensor values. The KNN classification model is used for prediction and guidance for the user while performing a particular exercise with the help of an android application-based virtual gym trainer through a text-to-speech module. The proposed system attained 89% accuracy, which is quite effective with portability and a virtually assisted gym trainer feature.

摘要

健身和运动在可穿戴和劝导式计算中引起了广泛关注。体育活动对健康、幸福、提高健康水平、降低精神压力和紧张水平都很有价值。尽管如此,在高功率和指挥性的锻炼中,身体状况很可能会受到严重影响。锻炼过程中的剧烈运动和不当姿势可能导致暂时或永久性残疾。随着技术进步的出现,基于可穿戴传感器的活动识别吸引了无数的研究。然而,一个完全便携式的智能健身套件还没有工业化,这是当今时代的核心需求,尤其是在新冠疫情期间。考虑到这个问题的有效性,我们提出了一个完全便携式的智能健身套件,供家庭在没有任何物理健身教练和健身房环境的情况下进行日常锻炼。该系统考虑了两种运动,即 T 型杆和二头肌卷曲,借助虚拟实时安卓应用程序,总体上充当健身教练。所提出的健身套件嵌入了陀螺仪和 EMG 传感器模块,用于执行上述两种运动。它通过安卓应用程序提供关于不健康、错误姿势运动的警报,并根据传感器值引导到最佳姿势。该系统通过基于安卓应用程序的虚拟健身教练使用 KNN 分类模型为用户提供特定运动的预测和指导,通过文本到语音模块实现。该系统的准确率达到了 89%,具有便携性和虚拟辅助健身教练功能,非常有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5077/8512175/04f41066ae45/sensors-21-06692-g001.jpg

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