Emerging Role of gait analysis in the Diagnosis of post-stroke hemiparesis

Abstract

Background: Hemiparesis after stroke disrupts nearly every measurable feature of walking, and visual bedside description of "hemiplegic gait" is too coarse to reliably guide targeted rehabilitation or to track recovery over time.

Objective: This review synthesizes the published evidence on gait analysis as a diagnostic and classification tool in post-stroke hemiparesis, spanning kinematic, kinetic, electromyographic, spatiotemporal, and wearable sensor-based methods.

Methods: We reviewed laboratory-based motion capture and force-plate studies, electromyographic investigations, wearable and accelerometer-based monitoring studies, and cluster-analysis classification work addressing hemiparetic gait after stroke.

Findings: Kinematic analysis consistently identifies reduced ankle dorsiflexion, diminished knee and hip motion, and compensatory circumduction on the paretic side; spatiotemporal asymmetry and reduced paretic propulsion measured by ground reaction force each carry independent diagnostic information beyond gait speed alone; cluster-based classification of kinematic and kinetic data separates patients into clinically distinct subgroups; and wearable inertial sensors extend assessment from brief laboratory sessions into everyday community walking.

Conclusions: Quantitative gait analysis has matured from a descriptive research tool into a genuinely diagnostic one, capable of identifying specific, targetable impairments underlying post-stroke hemiparesis, and continued integration of wearable sensing with laboratory-derived classification schemes is likely to bring this capability into routine clinical use.