Uslab Published a Paper Recently in Sensors (USLab近期在期刊Sensors发表学术论文) [2017-05-05]

A paper entitled 'Selection of Sensors Suitable for Integration into Smart Sport Equipment' has been published recently in Sensors (MDPI). This paper is a joint work with colleagues of University of Ljubljana, Slovenia, and Dr Yuan Zhang is the corresponding author. This paper can be accessed here.
Abstract: Wearable devices and smart sport equipment are being increasingly used in amateur and professional sports. Smart sport equipment employs various sensors for detecting its state and actions. The correct choice of the most appropriate sensor(s) is of paramount importance for efficient and successful operation of sport equipment. When integrated into the sport equipment, ideal sensors are unobstructive, and do not change the functionality of the equipment. The article focuses on experiments for identification and selection of sensors that are suitable for the integration into a golf club with the final goal of their use in real time biofeedback applications. We tested two orthogonally affixed strain gage (SG) sensors, a 3-axis accelerometer, and a 3-axis gyroscope. The strain gage sensors are calibrated and validated in the laboratory environment by a highly accurate Qualisys Track Manager (QTM) optical tracking system. Field test results show that different types of golf swing and improper movement in early phases of golf swing can be detected with strain gage sensors attached to the shaft of the golf club. Thus they are suitable for biofeedback applications to help golfers to learn repetitive golf swings. It is suggested that the use of strain gage sensors can improve the golf swing technical error detection accuracy and that strain gage sensors alone are enough for basic golf swing analysis. Our final goal is to be able to acquire and analyze as many parameters of a smart golf club in real time during the entire duration of the swing. This would give us the ability to design mobile and cloud biofeedback applications with terminal or concurrent feedback that will enable us to speed-up motor skill learning in golf.
  最近,USLab与斯洛文尼亚University of Ljubljana的三位同行合作,在MDPI期刊Sensors发表了论文“Selection of Sensors Suitable for Integration into Smart Sport Equipment”。张远博士是该论文通讯作者,论文提出了将合适的传感器嵌入智能球杆,以辅助高尔夫球手挥杆训练的新方法,全文可以在此处获取。
摘要:可穿戴设备和智能运动设备越来越多地用于业余和职业运动,智能运动设备采用各种传感器来检测其状态和动作,最合适传感器的正确选择对于运动器材的有效和成功运行至关重要。当整合进运动器材时,理想的传感器是无妨碍的,而且不会改变设备的功能。本文着重于识别和选择适合于整合进高尔夫球杆的传感器的实验,最终目标是实时生物反馈应用的使用。我们测试了两个正交贴片应变计(SG)传感器、一个3轴加速计和一个3轴陀螺仪。应变计传感器通过高精度的Qualisys Track Manager(QTM)光学跟踪系统在实验室环境中被校准和验证。现场测试结果表明,在高尔夫挥杆的早期阶段,不同类型的高尔夫挥杆和不正确的移动可以用连接到高尔夫球杆轴上的应变计传感器来检测。因此,它们适用于生物反馈应用,以帮助高尔夫球手学习重复的高尔夫挥杆。建议使用应变计传感器可以提高高尔夫挥杆技术误差检测精度,一个应变计传感器足以用于基本的高尔夫挥杆分析。我们的最终目标是能够在整个挥杆期间实时获取和分析智能高尔夫球杆的更多参数。这会使我们能够设计具有终端或并发反馈的移动和生物反馈云的应用程序,这将使我们能够加快高尔夫动作技能的学习。