Pattern identification of different human joints for different human walking styles using inertial measurement unit (IMU) sensor

Standard clinical gait analysis protocols usually limit to test self-selected speed gait: this approach is generally valid and permits time and cost saving. Yet, the literature evidences suggest that some pathologies (especially at onset or subclinical level) may not primarily affect plain gait, but more demanding locomotor tasks. In the present study we therefore propose a multiple-task gait analysis protocol including: self-selected, increased and decreased speed gait; walking on toes; walking on heels; step ascending and step descending, and apply it to 40 healthy subjects (20 aged 6-17, 20 aged 22-72) thus building extensive reference data set. Published studies already report normative data for some of these tasks, but inhomogeneously (due to different collecting methods and biomechanical models, population characteristics, nature of data). We verify a good correlation between our results and those presented by Schwartz et al. (2008) [12] in their study providing extensive data on the effect of walking speed on the gait of healthy children. In discussing the results, the rationale and effectiveness of each task is confirmed, and we supply an electronic addendum with comprehensive kinematic, kinetic and electromyographic normative data for the considered population, along with a set of reference parameters and related statistical analysis, as a premise for further applications on pathological subjects. Copyright © 2010 Elsevier B.V. All rights reserved.