A Quaternion-Based Method to IMU-to-Body Alignment for Gait Analysis

  • Fabián NarváezEmail author
  • Fernando Árbito
  • Ricardo Proaño
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10917)


Human gait analysis based on inertial measurement units (IMUs) is still considered a challenging task. This is because the accurate capture of human body movements depends on an initial sensor-to-body calibration and alignment process. In this paper, a novel sensor-to-body alignment method based on sequences of quaternions is presented, which allows to accurately estimate the joint angles from the hip, knee and ankle of the lower limbs. The proposed method involves two main stages, a sensors calibration and an alignment process for the body segments, respectively. For doing that, two different sequences of rotation based on Euler angle-axis factors are developed. The first rotational sequence is used to calibrate sensor’s frame under a new general body frame by estimating the initial orientation based on its quaternion information. Then, a correction process is applied by factorizing the captured quaternions. Once the general body frame is defined, a second rotational sequence is implemented, which aligns each sensor frame to body frames, allowing to define the anatomic frames for obtaining clinical measurements of the joint angles. The proposed method was two-fold validated using both strategies, a goniometer-based measure system and a camera-based motion system, respectively. The obtained results demonstrate that the estimated joint angles are equal to the expected values and consistent with values obtained by the strategies widely used in real clinical scenarios, the goniometers and optical motion system. Therefore, the proposed method could be used in clinical applications and motion analysis of impaired persons.


Inertial sensors Quaternion-based calibration Human motion analysis Joint angular kinematics 



This work was partially funded by the Ecuadorian Consortium for Advanced Internet Development (CEDIA) through the CEPRA projects. Specifically, under grants CEPRA-X-2016 project; “Tele-rehabilitation platform for elderly with dementia disorders, based on emerging technologies”. [Grant number: X-2016-02].


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Fabián Narváez
    • 1
    Email author
  • Fernando Árbito
    • 2
  • Ricardo Proaño
    • 3
  1. 1.GIByB Research Group, Department of Mechatronic EngineeringUniversidad Politéctica SalesianaQuitoEcuador
  2. 2.Faculty of Science and TechnologyUniversidad del AzuayCuencaEcuador
  3. 3.Faculty of Health SciencesUniversidad Técnica de AmbatoAmbatoEcuador

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