Analysis of Kinetic and Kinematic Gait Deviation Using Gaiton Software in Healthy Young Adults- A Cross Sectional Study

Abstract

Background: Walking is a fundamental human locomotor activity essential for independent mobility and overall health. Gait deviations, even when subtle, can impair walking efficiency and predispose individuals to musculoskeletal complications. Comprehensive kinematic assessment is therefore vital for early identification and targeted intervention.

Objective: To analyze kinetics and kinematics of gait and categorize major and minor gait deviations in young adults using GaitOn, with the aim of informing personalized rehabilitation strategies.
Methods: A cross-sectional study was conducted among 200 healthy young adults (18–25 years) recruited from an institutional campus via convenience sampling. Inclusion criteria required normal ambulation, while exclusions included recent lower limb surgery, musculoskeletal injuries, or neurological impairments. Anthropometric data were collected, and gait was recorded using a 6-meter walkway with a dual-camera GaitOn setup. Deviations in joint kinematics were identified and classified as major (clinically significant) or minor (clinician’s discretion).

Results: Major deviations were predominantly observed at the ankle, including increased plantarflexion and reduced dorsiflexion bilaterally, as well as altered knee extension/flexion patterns and hip flexion/extension asymmetries. Minor deviations included subtle joint angle changes, pelvic tilt variations, and patellar tracking abnormalities. These findings reflected both asymmetries and compensatory mechanisms.
Conclusion: GaitOn effectively identified clinically relevant and subtle gait deviations in young adults, underscoring its utility in early detection of biomechanical imbalances. Targeted interventions addressing these deviations may enhance walking efficiency and prevent future musculoskeletal complications..
Future Scope: Expanding to longer walkways, multi-camera or motion capture systems, and integrating force plates, EMG, and automated deviation detection could improve clinical applicability and accuracy.