Correlation of Smartphone-based, In-Clinic, Spatiotemporal Gait Analysis and self-reported mJOA scores for Cervical Myelopathy Patients

Introduction: Cervical myelopathy (CM) frequently resulting from spinal stenosis, manifests as gait disturbances, poor balance, and reduced hand dexterity. Diagnosis relies on clinical assessments and radiographic interpretation, can be subjective. Spatiotemporal gait metrics collected with smartphone-based 3D Motion capture offer objective measurements of gait parameters that quantify functional impairment and improvement in CM patients.

Methods: We aim to track longitudinal changes in CM patients undergoing cervical spine surgery by using video data captured by a smartphone-based 3D motion capture technology and wearable sensors to quantitate changes in gait and coordination and correlate with CM patients’ modified Japanese Orthopedic Association (mJOA) score at specified perioperative timepoints.
24 (including 9 operated) CM patients were recorded walking using a smartphone video camera and wearable sensors preoperatively and postoperatively at 6-weeks, 3-months and 6-months. The video was processed using PosePipe. Spatiotemporal gait parameters were extracted, including step length, pelvis velocity, cadence, smoothness of movement, and double support phase of gait percentage (DSP). We tested the correlation between the mJOA score and the median of these spatiotemporal variables across all subjects using Spearman’s r correlation coefficient.

Results: Spearman’s r was 0.77 (p=0.0159) for pelvis velocity, 0.82 (p=0.007) for cadence, -0.83 (p=0.005) for DSP, indicating a statistically significant association with mJOA scores measured at multiple timepoints; and 0.43 (p=0.205) for step length demonstrating no association. This indicates that as mJOA increased (less clinically symptomatic myelopathy), the patients moved their pelvis faster, took faster steps, and spent less time in the double support phase of gait.

Conclusion : There is a correlation between mJOA score and spatiotemporal gait parameters extracted from a smartphone video like pelvic velocity, cadence/smoothness of motion, and DSP. These parameters can be used to objectively quantify preoperative functional loss and postoperative functional improvements in CM patients undergoing spine surgery.