The use of inertial measurement units (IMUs) to compute gait outputs, such as the 3D lower-limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences in amplitude. The mean RMSE and centered RMSE were, respectively, 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs > 0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance in our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use.

IntroductionThree-dimensional gait analysis is widely used for the clinical assessment of movement disorders. However, measurement error reduces the reliability of kinematic data and consequently assessment of gait deviations. The identification of high variability is associated with low reliability and those parameters should be ignored or excluded from gait data interpretation. Moreover, marker placement error has been demonstrated to be the biggest source of variability in gait analysis and may be affected by factors intrinsic to the evaluators such as the evaluator's expertise which could be appraised through his/her experience and confidence in marker placement.ObjectivesIn the present study, we hypothesized that confidence in marker placement is correlated with kinematic variability and could potentially be used as part of a score of reliability. Therefore, we have proposed a questionnaire to evaluate qualitatively the confidence of evaluators in lower-limb marker placement. The primary aim of this study was to evaluate the reliability and validity of the presented questionnaire. The secondary objective was to test a possible relationship between marker placement confidence and kinematics variability.MethodsTo do so, test-retest gait data were acquired from two different experimental protocols. One protocol included data from a cohort of 32 pathological and 24 asymptomatic subjects where gait analysis was repeated three times, involving two evaluators. A second protocol included data from a cohort of 8 asymptomatic adults with gait analysis repeated 12 times, per participant, and involving four evaluators with a wider range of experience.ResultsResults demonstrated that the questionnaire proposed is valid and reliable to evaluate qualitatively the confidence of evaluators in placing markers. Indeed, confidence scores were correlated with the actual variability of marker placement and revealed the evaluator's experience and the subjects' characteristics. However, no correlation was observed between confidence scores and kinematic variability and the formulated hypothesis was not supported.

The use of inertial measurement units (IMUs) to compute gait outputs such as the 3D lower limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences of amplitude. The mean RMSE and centered RMSE were respectively 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs>0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance of our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use.