Concurrent Validation of 3D Joint Angles during Gymnastics Techniques Using Inertial Measurement Units

Abstract

There are advantages in using inertial measurement unit systems (IMUS) for biomechanical analysis when compared to 2D/3D video-based analysis. The main advantage is the ability to analyze movement in the natural performance environment, preserving the ecological validity of the task. Coaches can access accurate and detailed data in real time and use it to optimize feedback and performance. Efforts are needed to validate the accuracy of IMUS. We assess the accuracy of the IMUS Xsens MVN Link system using an optoelectronic system (OS) as a reference when measuring 3D joint angles during the gymnastics round-off back handspring technique. We collected movement kinematics from 10 participants. The coefficient of multiple correlation (CMC) results showed very good and excellent values for the majority of the joint angles, except for neck flexion/extension (F/E). Root mean square errors (RMSE) were below/near 10°, with slightly higher values for shoulder (12.571°), ankle (11.068°), thorax-thigh F/E (21.416°), and thorax–thigh internal/external rotation (I/E) (16.312°). Significant SPM-1D {t} differences for thorax–thigh abduction/adduction (A/A), neck, thorax–thigh, knee, shoulder and ankle F/E were demonstrated during small temporal periods. Our findings suggest that the Xsens MVN Link system provides valid data that can be used to provide feedback in training.

Conversion of Upper-Limb Inertial Measurement Unit Data to Joint Angles: A Systematic Review

“…Sensor placement on the body is often chosen to minimize soft tissue or skin motion artifacts and includes the flat portion of the sternum, the lateral distal aspect of the upper arm, and the dorsal distal aspect of the forearm. For the simultaneous collection of IMU and optoelectronic data, retro-reflective markers and IMUs have been placed independently on anatomical landmarks [ 36 , 52 , 60 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 ], retro-reflective markers placed directly on IMUs [ 30 , 41 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 ], or a combination of both approaches [ 61 , 107 , 108 ,…”

“…To establish a relationship between IMU orientation and that of an underlying anatomical coordinate system, a sensor-to-segment calibration process is typically employed. Common calibration methods include predefined sensor alignment with a segment [ 66 , 94 , 103 , 104 ], static pose alignment [ 67 , 69 , 70 , 71 , 72 , 73 , 74 , 83 , 84 , 88 , 98 , 99 , 100 , 102 , 105 , 109 ], functional joint movements [ 92 , 107 ], or their combinations [ 30 , 36 , 41 , 61 , 68 , 79 , 81 , 91 , 96 , 97 , 106 , 108 , 110 , 112 , 113 , 114 ], as well as use of IMU palpation calipers [ 90 , 93 ] ( Figure 4 ). Predefined sensor alignment involves the placement of an IMU on the body to align with a bone-fixed reference frame.…”

“…To convert IMU orientation data to joint angles, definitions of anatomical joint coordinate systems have been established using the Denavit–Hartenberg representation [ 61 , 67 , 89 ], orthonormal [ 30 , 41 , 66 , 68 , 70 , 71 , 73 , 79 , 83 , 86 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 101 , 106 , 107 , 108 , 109 , 110 ], and non-orthonormal segment coordinate systems [ 36 , 52 , 75 , 113 ] ( Figure 5 ). The orientation of one segment relative to another is computed using 3D Euler angle decomposition [ 30 , 36 , 41 , 52 , 66 , 68 , 77 , 78 , 79 , 80 , 84 , 85 , 86 , 88 , 90 , 91 , 92 , 93 , 95 ,…”

Movement Prototypes in a Complex Teamgym Gymnastics Technique on the Vaulting Table and Their Relationship with Judges’ Scores

“…We recorded biomechanical data using a system of seventeen inertial measurement sensors (Xsens MVN Link; Xsens Technologies, Enschede, The Netherlands) at a rate of 240 Hz. This system was previously validated against an optoelectronic system to measure kinematic variables during the performance of gymnastics tasks in an ecological environment [ 21 ]. The study revealed a very good to excellent coefficient of multiple correlation values, as well as acceptable errors (root mean square errors) for the joint angles considered in the present study.…”

Gait Recognition for Lower Limb Exoskeletons Based on Interactive Information Fusion

“…Moreover, the upcoming and popular commercial motion capture systems such as Xsens MVN [ 32 , 33 ] and Xsens MTw Awinda have brought greater convenience to gait information acquisition, which not only overcome some of above limitations but also eliminate the errors caused by the external interference of the wearable sensors. It can be predicted that motion capture system will become the first choice for researchers to obtain gait information in the future because of its ease of use and analysis.…”