A model-based human walking speed estimation using body acceleration data

Abstract

This study aims at estimating the human walking speed using wearable accelerometers by proposing a novel virtual inverted pendulum model. This model not only keeps the important characteristic in biped rolling-foot model, but also makes the speed estimation feasible using human body acceleration. Rather than the statistical methods, the proposed kinematic walking model enables calibration of the parameters during walking using only one tri-axial accelerometer on waist that reflects the user's inertia information during walking. In addition, this model also includes the effect of rotation of waist within a walking cycle that improves the estimation accuracy. Experimental results on a group of humans show a 1.22% error mean and 2.78% deviation, which is far better than other known studies.