Inertial Measurement Unit Sensor-to-Segment Calibration Comparison for Sport-Specific Motion Analysis

Abstract

Wearable inertial measurement units (IMUs) can be utilized as an alternative to optical motion capture as a method of measuring joint angles. These sensors require functional calibration prior to data collection, known as sensor-to-segment calibration. This study aims to evaluate previously described sensor-to-segment calibration methods to measure joint angle range of motion (ROM) during highly dynamic sports-related movements. Seven calibration methods were selected to compare lower extremity ROM measured using IMUs to an optical motion capture system. The accuracy of ROM measurements for each calibration method varied across joints and sport-specific tasks, with absolute mean differences between IMU measurement and motion capture measurement ranging from <0.1° to 24.1°. Fewer significant differences were observed at the pelvis than at the hip, knee, or ankle across all tasks. For each task, one or more calibration movements demonstrated non-significant differences in ROM for at least nine out of the twelve ROM variables. These results suggest that IMUs may be a viable alternative to optical motion capture for sport-specific lower-extremity ROM measurement, although the sensor-to-segment calibration methods used should be selected based on the specific tasks and variables of interest for a given application.

Relationship of Knee Abduction Moment to Trunk and Lower Extremity Segment Acceleration during Sport-Specific Movements

“…Acceleration data were collected using eight wireless Delsys Trigno Avanti IMU sensors (Delsys Inc., Natick, MA, USA) placed directly on the skin on the body segments of interest, as displayed in Figure 1 , and secured with elastic wrap and athletic tape to minimize skin artifact noise in the IMU signal. Specifically, placements included the sternum (midpoint between xiphoid process and jugular notch), sacrum (midpoint between posterior superior iliac spines), anterior thighs (rectus femoris muscle bellies), and the anterior shanks (tibialis anterior muscle bellies) as shown in prior work [ 28 ]. Two sensors were also placed on the dorsal side of the feet (along the shoelaces); however, these were primarily used to measure ankle joint kinematics for a separate study [ 28 ].…”

“…Specifically, placements included the sternum (midpoint between xiphoid process and jugular notch), sacrum (midpoint between posterior superior iliac spines), anterior thighs (rectus femoris muscle bellies), and the anterior shanks (tibialis anterior muscle bellies) as shown in prior work [ 28 ]. Two sensors were also placed on the dorsal side of the feet (along the shoelaces); however, these were primarily used to measure ankle joint kinematics for a separate study [ 28 ]. Additionally, the acceleration data were determined to contain excessive noise, likely due to motion artifacts during foot strikes, and were therefore not included in the analyses of this current study.…”

“…minimize skin artifact noise in the IMU signal. Specifically, placements included the sternum (midpoint between xiphoid process and jugular notch), sacrum (midpoint between posterior superior iliac spines), anterior thighs (rectus femoris muscle bellies), and the anterior shanks (tibialis anterior muscle bellies) as shown in prior work [28]. Two sensors were also placed on the dorsal side of the feet (along the shoelaces); however, these were primarily used to measure ankle joint kinematics for a separate study [28].…”

“…Although angular velocity has been shown to be a useful measure for assessing injury risk, gyroscopes are highly susceptible to constant bias, noise, and bias instability during high-impact and high range-of-motion movements [ 26 ]. As a result, angular velocity measurements often require the implementation of compensation or calibration techniques to improve measurement accuracy [ 27 , 28 ]. By contrast, accelerometer signals are only affected by noise during highly dynamic movements and therefore require a simple lowpass filter for accurate measurement.…”