Prediction of walking Asymmetry using Spatiotemporal Gait Parameters and Guidance for fall risk Prediction or Geriatric Care: Experimental Study for Indian Population

Abstract

Gait analysis allows the quantitative assessment of gait to recognize its associated variation and disorders. The reliability of analysis gets augmented when being compared with standard documented normative dataset. The purpose of this study is to establish the spatiotemporal gait parameters for the normative dataset for Indian Population. Eighty healthy subjects aged between 20 and 70 years with no impairments affecting gait, recorded their Footfall on self-selected walking speed on GAITRite® Electronic walkway. Successive ten iteration of Barefoot and Comfortable (specific to person) shoe wear walk are Considered to generate one record. Mean, standard deviation, coefficient of correlation, 95% Confidence Interval, and 95% Prediction Interval are calculated using descriptive statistics. Healthy Gait is often characterized as symmetric to verify, bilateral spatiotemporal parameters are considered and mean, standard Deviation, Variance, and Min-Max ranges are obtained. Chosen Spatial and temporal characteristics are taken into consideration separately to demonstrate role in diverse test cases to get the result. Obtained singular and bilateral ranges are recorded for classification of Symmetry and Asymmetry and based on that algorithm is proposed for identifying Gait Asymmetry. Study of these ranges provides the guideline for geriatric care.