Health Indicator Estimation by Video-Based Gait Analysis

Abstract

In this study, we propose a method to estimate body composition-related health indicators (e.g., ratio of body fat, body water, and muscle, etc.) using video-based gait analysis. This method is more efficient than individual measurement using a conventional body composition meter. Specifically, we designed a deep-learning framework with a convolutional neural network (CNN), where the input is a gait energy image (GEI) and the output consists of the health indicators. Although a vast amount of training data is typically required to train network parameters, it is unfeasible to collect sufficient ground-truth data, i.e., pairs consisting of the gait video and the health indicators measured using a body composition meter for each subject. We therefore use a two-step approach to exploit an auxiliary gait dataset that contains a large number of subjects but lacks the ground-truth health indicators. At the first step, we pre-train a backbone network using the auxiliary dataset to output gait primitives such as arm swing, stride, the degree of stoop, and the body width -considered to be relevant to the health indicators. At the second step, we add some layers to the backbone network and fine-tune the entire network to output the health indicators even with a limited number of ground-truth data points of the health indicators. Experimental results show that the proposed method outperforms the other methods when training from scratch as well as when using an auto-encoder-based pre-training and fine-tuning approach; it achieves relatively high estimation accuracy for the body composition-related health indicators except for body fat-relevant ones.

Impact of Achilles Tendon taping on parameters of gait in asymptomatic-overweight and obese individuals

“…O peso e a altura de cada paciente serão medidos para o cálculo do IMC. 10 • Critérios de inclusão: Tanto os homens como as mulheres 11 em boa saúde, da faixa etária 18-35 anos 12 com IMC >25 13 , acima do peso com IMC >25 a 29,9, obesos com IMC > 30 e nível cognitivo suficiente para entender os procedimentos e seguir as instruções.…”

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