Najafi Bijan, Lee-Eng Jacqueline, Wrobel James S, Goebel Ruben
Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Department of Surgery, University of Arizona College of Medicine , Tucson, Arizona, USA.
Metabolism, Endocrinology and Diabetes Division, University of Michigan , Medical School, Ann Arbor, MI, USA.
J Sports Sci Med. 2015 May 8;14(2):354-63. eCollection 2015 Jun.
This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete's movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key pointsThis study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing)This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements.Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support.
本研究提出了一种可穿戴传感器技术,用于估计高尔夫挥杆过程中的质心(CoM)轨迹。分别招募了3名、4名和18名参与者组成小组,以进行三项验证研究。研究1将该系统与基于摄像头的运动分析仪(Vicon®)进行比较,检验其估计三维身体节段角度的准确性。研究2评估了三种简化的CoM轨迹模型的准确性。最后,研究3评估了所提出的CoM模型在多次高尔夫挥杆过程中的准确性。在角度测量方面,可穿戴传感器与参考设备(Vicon®)之间观察到较高的一致性(r>0.99,前后方向的随机误差<1.2°(1.5%);内外方向的随机误差<0.9°(2%);内外方向的随机误差<3.6°(2.5%))。与单连杆模型相比,双连杆模型与参考系统的一致性更好(r分别为>0.93和r = 0.52)。同样,所提出的双连杆模型在估计高尔夫挥杆过程中的CoM轨迹时具有相对较高的准确性(r>0.9,前后方向的随机误差<1cm(7.7%),内外方向的随机误差<2cm(10.4%))。所提出的系统似乎能够准确地量化CoM轨迹的运动学,作为运动员运动过程中动态姿势控制的替代指标,并且其便携性使得在不限制表面类型的情况下适应竞争环境成为可能。关键点本研究表明,基于惯性传感器的可穿戴技术在估计复杂体育任务(如高尔夫挥杆)中的质心轨迹方面是准确的。本研究表明,人体的双连杆模型在准确性和用于估计质心轨迹的最少传感器模块数量之间提供了最佳平衡,特别是在快速运动期间。基于惯性传感器的可穿戴技术是在步态实验室之外的复杂任务中评估动态姿势控制的可行选择,不受摄像头、表面和支撑基础的限制。