title: Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing.
abstract: 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.
authors.affiliation: Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Department of Surgery, University of Arizona College of Medicine , Tucson, Arizona, USA.
authors.forename: Bijan
authors.initials: B
authors.lastname: Najafi
authors.affiliation: Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Department of Surgery, University of Arizona College of Medicine , Tucson, Arizona, USA.
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Lee-Eng
authors.affiliation: Metabolism, Endocrinology and Diabetes Division, University of Michigan , Medical School, Ann Arbor, MI, USA.
authors.forename: James S
authors.initials: JS
authors.lastname: Wrobel
authors.affiliation: Sport Science Program, Qatar University , Doha, Qatar.
authors.forename: Ruben
authors.initials: R
authors.lastname: Goebel
keywords: Wearable technology; balance; center of mass; dynamic postural control; golf swing; simplified biomechanical model of human body