Abstract
Introduction: Gait changes could occur after thoracic to pelvic long-segment corrective fusion surgery, a common procedure for adult spinal deformity (ASD), potentially affecting the occurrence and progression of postoperative hip osteoarthritis. We aimed to clarify postoperative pelvic kinematics in patients with ASD by performing gait analysis using a system based on a smartphone-integrated inertial measurement unit (IMU).
Methods: A total of 21 consecutive outpatients (73.6±4.6 years old, 2 men, 19 women) were enrolled. All had undergone long-segment fusion from the thoracic spine to the pelvis for ASD more than 1 year previously and could walk unassisted. A control group comprised 20 healthy volunteers. The IMU was fixed on the sacrum, and data were collected when subjects walked forward on a flat indoor floor. Acceleration in three axial directions and angular velocity around the three axes were recorded simultaneously during gait, and data were cut out for each gait cycle. Of 1043 features obtained, the top 20 features with the smallest p-value in a statistical comparison were selected. These features, plus gender and age, were classified using gradient boosting machine learning based on the decision tree algorithm. The classification accuracy and relative importance of the feature items were calculated.
Results: The accuracy rate for gait classification between groups was 96.7% and the F1-score was 0.968. The factor that contributed most to the classification of gait in both groups was "y-angular,_change_quantiles,_f_agg=" var",_isabs=True,_qh=0.6,_ql=0.2," which means the variance of the change of the absolute value in the pelvic rotation angular velocity in the horizontal plane in the range of 20%-60% of the gait cycle. Its relative importance was 0.351, which was smaller in the group with fusion.
Conclusions: Patients with ASD following long-segment fusion from the thoracic spine to the pelvis apparently have a gait style characterized by suppressed pelvic rotation in the horizontal plane.
