Literature DB >> 24780202

Consistency of gait characteristics as determined from acceleration data collected at different trunk locations.

Sietse M Rispens1, Mirjam Pijnappels2, Kimberley S van Schooten1, Peter J Beek3, Andreas Daffertshofer1, Jaap H van Dieën4.   

Abstract

Estimates of gait characteristics may suffer from errors due to discrepancies in accelerometer location. This is particularly problematic for gait measurements in daily life settings, where consistent sensor positioning is difficult to achieve. To address this problem, we equipped 21 healthy adults with tri-axial accelerometers (DynaPort MiniMod, McRoberts) at the mid and lower lumbar spine and anterior superior iliac spine (L2, L5 and ASIS) while continuously walking outdoors back and forth (20 times) over a distance of 20 m, including turns. We compared 35 gait characteristics between sensor locations by absolute agreement intra-class correlations (2, 1; ICC). We repeated these analyses after applying a new method for off-line sensor realignment providing a unique definition of the vertical and, by symmetry optimization, the two horizontal axes. Agreement between L2 and L5 after realignment was excellent (ICC>0.9) for stride time and frequency, speed and their corresponding variability and good (ICC>0.7) for stride regularity, movement intensity, gait symmetry and smoothness and for local dynamic stability. ICC values benefited from sensor realignment. Agreement between ASIS and the lumbar locations was less strong, in particular for gait characteristics like symmetry, smoothness, and local dynamic stability (ICC generally<0.7). Unfortunately, this lumbar-ASIS agreement did not benefit consistently from sensor realignment. Our findings show that gait characteristics are robust against limited repositioning error of sensors at the lumbar spine, in particular if our off-line realignment is applied. However, larger positioning differences (from lumbar positions to ASIS) yield less consistent estimates and should hence be avoided.
Copyright © 2014 Elsevier B.V. All rights reserved.

Keywords:  Agreement; Daily life activities; Inertial sensor; Realignment; Sensor positioning

Mesh:

Year:  2014        PMID: 24780202     DOI: 10.1016/j.gaitpost.2014.03.182

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  17 in total

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Authors:  Nancy T Nguyen; Jefferson W Streepey
Journal:  Telemed Rep       Date:  2022-06-28

2.  Do extreme values of daily-life gait characteristics provide more information about fall risk than median values?

Authors:  Sietse M Rispens; Kimberley S van Schooten; Mirjam Pijnappels; Andreas Daffertshofer; Peter J Beek; Jaap H van Dieën
Journal:  JMIR Res Protoc       Date:  2015-01-05

3.  Daily-Life Gait Quality as Predictor of Falls in Older People: A 1-Year Prospective Cohort Study.

Authors:  Kimberley S van Schooten; Mirjam Pijnappels; Sietse M Rispens; Petra J M Elders; Paul Lips; Andreas Daffertshofer; Peter J Beek; Jaap H van Dieën
Journal:  PLoS One       Date:  2016-07-07       Impact factor: 3.240

4.  On Gait Analysis Estimation Errors Using Force Sensors on a Smart Rollator.

Authors:  Joaquin Ballesteros; Cristina Urdiales; Antonio B Martinez; Jaap H van Dieën
Journal:  Sensors (Basel)       Date:  2016-11-10       Impact factor: 3.576

5.  Validation of a Step Detection Algorithm during Straight Walking and Turning in Patients with Parkinson's Disease and Older Adults Using an Inertial Measurement Unit at the Lower Back.

Authors:  Minh H Pham; Morad Elshehabi; Linda Haertner; Silvia Del Din; Karin Srulijes; Tanja Heger; Matthis Synofzik; Markus A Hobert; Gert S Faber; Clint Hansen; Dina Salkovic; Joaquim J Ferreira; Daniela Berg; Álvaro Sanchez-Ferro; Jaap H van Dieën; Clemens Becker; Lynn Rochester; Gerhard Schmidt; Walter Maetzler
Journal:  Front Neurol       Date:  2017-09-04       Impact factor: 4.003

6.  Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment.

Authors:  Lisette H J Kikkert; Nicolas Vuillerme; Jos P van Campen; Bregje A Appels; Tibor Hortobágyi; Claudine J C Lamoth
Journal:  J Neuroeng Rehabil       Date:  2017-08-15       Impact factor: 4.262

7.  Intra-Rater, Inter-Rater and Test-Retest Reliability of an Instrumented Timed Up and Go (iTUG) Test in Patients with Parkinson's Disease.

Authors:  Rob C van Lummel; Stefan Walgaard; Markus A Hobert; Walter Maetzler; Jaap H van Dieën; Francisca Galindo-Garre; Caroline B Terwee
Journal:  PLoS One       Date:  2016-03-21       Impact factor: 3.240

8.  Test-Retest Reliability of an Automated Infrared-Assisted Trunk Accelerometer-Based Gait Analysis System.

Authors:  Chia-Yu Hsu; Yuh-Show Tsai; Cheng-Shiang Yau; Hung-Hai Shie; Chu-Ming Wu
Journal:  Sensors (Basel)       Date:  2016-07-23       Impact factor: 3.576

9.  Characteristics of daily life gait in fall and non fall-prone stroke survivors and controls.

Authors:  Michiel Punt; Sjoerd M Bruijn; Kimberley S van Schooten; Mirjam Pijnappels; Ingrid G van de Port; Harriet Wittink; Jaap H van Dieën
Journal:  J Neuroeng Rehabil       Date:  2016-07-27       Impact factor: 4.262

10.  Fall-related gait characteristics on the treadmill and in daily life.

Authors:  Sietse M Rispens; Jaap H Van Dieën; Kimberley S Van Schooten; L Eduardo Cofré Lizama; Andreas Daffertshofer; Peter J Beek; Mirjam Pijnappels
Journal:  J Neuroeng Rehabil       Date:  2016-02-02       Impact factor: 4.262

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