Biomechanical Gait Analysis Using a Smartphone-Based Motion Capture System (OpenCap) in Patients with Neurological Disorders

Abstract

This study evaluates the utility of OpenCap (v0.3), a smartphone-based motion capture system, for performing gait analysis in patients with neurological disorders. We compared kinematic and kinetic gait parameters between 10 healthy controls and 10 patients with neurological conditions, including stroke, Parkinson's disease, and cerebral palsy. OpenCap captured 3D movement dynamics using two smartphones, with data processed through musculoskeletal modeling. The key findings indicate that the patient group exhibited significantly slower gait speeds (0.67 m/s vs. 1.10 m/s, p = 0.002), shorter stride lengths (0.81 m vs. 1.29 m, p = 0.001), and greater step length asymmetry (107.43% vs. 91.23%, p = 0.023) compared to the controls. Joint kinematic analysis revealed increased variability in pelvic tilt, hip flexion, knee extension, and ankle dorsiflexion throughout the gait cycle in patients, indicating impaired motor control and compensatory strategies. These results indicate that OpenCap can effectively identify significant gait differences, which may serve as valuable biomarkers for neurological disorders, thereby enhancing its utility in clinical settings where traditional motion capture systems are impractical. OpenCap has the potential to improve access to biomechanical assessments, thereby enabling better monitoring of gait abnormalities and informing therapeutic interventions for individuals with neurological disorders.

Keywords: gait; kinematics; kinetics; motion capture; smartphone.

Figure 1

Joint-specific kinematic parameters during the gait cycle, normalized for a group of controls. Each subplot represents a specific joint movement across the gait cycle (%). The blue line indicates the mean kinematic angle, with shaded areas representing ±1 standard deviation (SD). The following movements are shown: pelvic tilt, list, and rotation; hip flexion/extension, adduction/abduction, and internal/external rotation (IR/ER); knee flexion/extension; ankle dorsiflexion/plantarflexion; and subtalar inversion/eversion.

Figure 2

Joint-specific kinematic parameters during the gait cycle, normalized for a group of patients. Each subplot represents a specific joint movement across the gait cycle (%). The blue line indicates the mean kinematic angle, with shaded areas representing ±1 standard deviation (SD). The following movements are shown: pelvic tilt, list, and rotation; hip flexion/extension, adduction/abduction, and internal/external rotation (IR/ER); knee flexion/extension; ankle dorsiflexion/plantarflexion; and subtalar inversion/eversion.

Figure 3

Bootstrap confidence bands and non-overlapping regions for hip, knee, and ankle parameters in patients and controls. This figure illustrates the bootstrap confidence intervals (CI) and regions of statistically significant differences between patients (blue) and controls (green) for key gait parameters. The shaded regions around each curve represent the 95% confidence intervals generated through 1000 bootstrap resamples. Red-highlighted vertical spans indicate areas where the confidence intervals of the two groups do not overlap, suggesting statistically significant differences in these regions.

Figure 4

Comparison of bootstrap confidence intervals and non-overlapping regions for hip flexion, hip adduction, knee angle, and ankle angle in stroke patients and normal controls. The blue and green lines represent the mean curves for stroke patients and healthy controls, respectively, while the shaded regions indicate the 95% bootstrap confidence intervals (CI) calculated across the gait cycle. Red-highlighted regions indicate statistically significant differences where the confidence intervals between the two groups do not overlap.

Figure 5

Comparison of bootstrap confidence intervals and non-overlapping regions for hip flexion, hip adduction, knee flexion, and ankle plantarflexion/dorsiflexion in the Parkinson’s patients and controls. The mean joint angle trajectories for Parkinson’s patients are shown in blue, while the green lines represent healthy controls. The shaded regions around each curve represent the 95% bootstrap confidence intervals (CIs). Red-highlighted areas indicate time points where the confidence intervals do not overlap, signifying statistically significant differences between the two groups.

Figure 6

Comparison of bootstrap confidence intervals and non-overlapping regions for hip, knee, and ankle joint kinematics in children and adults. This figure presents a comparison of lower limb joint kinematics between children and healthy adult controls throughout the gait cycle, focusing on the following key parameters: hip flexion/adduction, knee flexion, and ankle plantarflexion/dorsiflexion. The mean joint angle trajectories for children are shown in blue, while those for healthy adults are displayed in green. Shaded regions around each curve represent the 95% bootstrap confidence intervals (CIs). Red-highlighted areas indicate time points where the confidence intervals do not overlap, denoting statistically significant differences between the two groups.