Literature DB >> 29198369

A practical step length algorithm using lower limb angular velocities.

E Allseits1, V Agrawal2, J Lučarević3, R Gailey3, I Gaunaurd4, C Bennett5.   

Abstract

The use of Inertial Measurement Units (IMUs) for spatial gait analysis has opened the door to unconstrained measurements within the home and community. Bandwidth, cost limitations, and ease of use has historically restricted the number and location of sensors worn on the body. In this paper, we describe a four-sensor configuration of IMUs placed on the shanks and thighs that is sufficient to provide an accurate measure of temporal gait parameters, spatial gait parameters, and joint angle dynamics during ambulation. Estimating spatial gait parameters solely from gyroscope data is preferred because gyroscopes are less susceptible to sensor noise and a system comprised of only gyroscopes uses decreased bandwidth compared to a typical 9 degree-of-freedom IMU. The purpose of this study was to determine the validity of a novel method of step length estimation using gyroscopes attached to the shanks and thighs. An Inverted Pendulum Model algorithm (IPM) was proposed to calculate step length, stride length, and gait speed. The algorithm incorporates heel-strike events and average forward velocity per step to make these assessments. IMU algorithm accuracy was determined via concurrent validity with an instrumented walkway and results explained via the collision model of gait. The IPM produced accurate estimates of step length, stride length, and gait speed with a mean difference of 3 cm and an RMSE of 6.6 cm for step length, thus establishing a new approach for spatial gait parameter calculation. The lack of numerical integration in IPM makes it well suited for use in continuous monitoring applications where sensor sampling rates are restricted.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Clinical gait analysis; Gait speed; IMU; Step length; Stride length

Mesh:

Year:  2017        PMID: 29198369     DOI: 10.1016/j.jbiomech.2017.11.010

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  6 in total

1.  RNN-Aided Human Velocity Estimation from a Single IMU.

Authors:  Tobias Feigl; Sebastian Kram; Philipp Woller; Ramiz H Siddiqui; Michael Philippsen; Christopher Mutschler
Journal:  Sensors (Basel)       Date:  2020-06-29       Impact factor: 3.576

2.  A Novel Method for Estimating Knee Angle Using Two Leg-Mounted Gyroscopes for Continuous Monitoring with Mobile Health Devices.

Authors:  Eric Allseits; Kyoung Jae Kim; Christopher Bennett; Robert Gailey; Ignacio Gaunaurd; Vibhor Agrawal
Journal:  Sensors (Basel)       Date:  2018-08-22       Impact factor: 3.576

3.  Walking-speed estimation using a single inertial measurement unit for the older adults.

Authors:  Seonjeong Byun; Hyang Jun Lee; Ji Won Han; Jun Sung Kim; Euna Choi; Ki Woong Kim
Journal:  PLoS One       Date:  2019-12-26       Impact factor: 3.240

4.  A Wearable Sensor System to Measure Step-Based Gait Parameters for Parkinson's Disease Rehabilitation.

Authors:  Niveditha Muthukrishnan; James J Abbas; Narayanan Krishnamurthi
Journal:  Sensors (Basel)       Date:  2020-11-10       Impact factor: 3.576

Review 5.  Validity and reliability of wearable inertial sensors in healthy adult walking: a systematic review and meta-analysis.

Authors:  Dylan Kobsar; Jesse M Charlton; Calvin T F Tse; Jean-Francois Esculier; Angelo Graffos; Natasha M Krowchuk; Daniel Thatcher; Michael A Hunt
Journal:  J Neuroeng Rehabil       Date:  2020-05-11       Impact factor: 4.262

6.  A new method of measuring the thumb pronation and palmar abduction angles during opposition movement using a three-axis gyroscope.

Authors:  Tomoyuki Kuroiwa; Koji Fujita; Akimoto Nimura; Takashi Miyamoto; Toru Sasaki; Atsushi Okawa
Journal:  J Orthop Surg Res       Date:  2018-11-16       Impact factor: 2.359

  6 in total

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