Inertial Sensor-to-Segment Calibration for Accurate 3D Joint Angle Calculation for Use in OpenSim

Abstract

Inertial capture (InCap) systems combined with musculoskeletal (MSK) models are an attractive option for monitoring 3D joint kinematics in an ecological context. However, the primary limiting factor is the sensor-to-segment calibration, which is crucial to estimate the body segment orientations. Walking, running, and stair ascent and descent trials were measured in eleven healthy subjects with the Xsens InCap system and the Vicon 3D motion capture (MoCap) system at a self-selected speed. A novel integrated method that combines previous sensor-to-segment calibration approaches was developed for use in a MSK model with three degree of freedom (DOF) hip and knee joints. The following were compared: RMSE, range of motion (ROM), peaks, and R² between InCap kinematics estimated with different calibration methods and gold standard MoCap kinematics. The integrated method reduced the RSME for both the hip and the knee joints below 5°, and no statistically significant differences were found between MoCap and InCap kinematics. This was consistent across all the different analyzed movements. The developed method was integrated on an MSK model workflow, and it increased the sensor-to-segment calibration accuracy for an accurate estimate of 3D joint kinematics compared to MoCap, guaranteeing a clinical easy-to-use approach.

Keywords: 3D joint kinematics; IMU; biomechanical model; joint angles; lower-body kinematics; motion analysis; musculoskeletal; open-source; sensor-to-segment calibration; wearable sensors.

Figure 1

Method 0: One sensor (e.g., pelvis) aligned with the MSK model (MoCap derived pose) and with all the other sensors—static calibration approach [46]; Method 1: hip abduction–adduction motion to align thigh-shank-foot sensors—functional calibration [34]; Method 2: PCA-method based on sit-to-stand and walking to align torso-pelvis-thigh sensors—functional calibration [46]; Method 3: combination of Methods 1 and 2 for the alignment of all sensors—functional calibration [34,46].

Figure 2

Workflow scheme for the different methods: the green, orange, and yellow boxes are part of the functional calibration and sensors alignment.

Figure 3

3D knee joint angle comparison during walking, running, stair ascent, and stair descent over a cycle for a representative subject—in order sagittal, frontal, and transverse planes. InCap system (M0—green, M1—cyan, M2—red, M3—blue) and MoCap system (black). M0: OpenSense standard pipeline, M1: functional hip abd-adduction motion calibration, M2: functional PCA walking calibration, M3: functional hip abd-adduction and walking PCA calibration.

Figure 4

Subjects RMSE (mean ± SD) for InCap joint kinematics during walking compared to clinical threshold of 5.0 deg (red dotted line). Differences between the developed methods (M0—blue, M1—red, M2—green, M3—orange) across the joint-planes (a): Hip flexion/extension, hip abduction/adduction, hip internal/external rotation, knee flexion/extension, knee abduction/adduction, knee internal/external rotation, ankle dorsiflexion/plantarflexion, ankle pronation/supination; (b): pelvic tilt, pelvic list, pelvic rotation, lumbar extension, lumbar bending, lumbar rotation. * p ≤ 0.05. M0: OpenSense standard pipeline, M1: functional hip abd-adduction motion calibration, M2: functional PCA walking calibration, M3: functional hip abd-adduction and walking PCA calibration.