Literature DB >> 28829950

Analysis of gait patterns pre- and post- Single Event Multilevel Surgery in children with Cerebral Palsy by means of Offset-Wise Movement Analysis Profile and Linear Fit Method.

Andrea Ancillao1, Marjolein M van der Krogt2, Annemieke I Buizer3, Melinda M Witbreuk4, Paolo Cappa5, Jaap Harlaar6.   

Abstract

Gait analysis is used for the assessment of walking ability of children with cerebral palsy (CP), to inform clinical decision making and to quantify changes after treatment. To simplify gait analysis interpretation and to quantify deviations from normality, some quantitative synthetic descriptors were developed over the years, such as the Movement Analysis Profile (MAP) and the Linear Fit Method (LFM), but their interpretation is not always straightforward. The aims of this work were to: (i) study gait changes, by means of synthetic descriptors, in children with CP that underwent Single Event Multilevel Surgery; (ii) compare the MAP and the LFM on these patients; (iii) design a new index that may overcome the limitations of the previous methods, i.e. the lack of information about the direction of deviation or its source. Gait analysis exams of 10 children with CP, pre- and post-surgery, were collected and MAP and LFM were computed. A new index was designed asa modified version of the MAP by separating out changes in offset (named OC-MAP). MAP documented an improvement in the gait pattern after surgery. The highest effect was observed for the knee flexion/extension angle. However, a worsening was observed as an increase in anterior pelvic tilt. An important source of gait deviation was recognized in the offset between observed tracks and reference. OC-MAP allowed the assessment of the offset component versus the shape component of deviation. LFM provided results similar to OC-MAP offset analysis but could not be considered reliable due to intrinsic limitations. As offset in gait features played an important role in gait deviation, OC-MAP synthetic analysis was proposed as a novel approach to a meaningful parameterisation of global deviations in gait patterns of subjects with CP and gait changes after treatment.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cerebral Palsy; GPS; Gait analysis; Movement Analysis Profile; SEMLS; Synthetic indices

Mesh:

Year:  2017        PMID: 28829950     DOI: 10.1016/j.humov.2017.08.005

Source DB:  PubMed          Journal:  Hum Mov Sci        ISSN: 0167-9457            Impact factor:   2.161


  4 in total

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Authors:  Andrea Ancillao
Journal:  Med Biol Eng Comput       Date:  2022-05-12       Impact factor: 2.602

2.  Gait Characteristics of Children with Spastic Cerebral Palsy during Inclined Treadmill Walking under a Virtual Reality Environment.

Authors:  Ye Ma; Yali Liang; Xiaodong Kang; Ming Shao; Lilja Siemelink; Yanxin Zhang
Journal:  Appl Bionics Biomech       Date:  2019-08-19       Impact factor: 1.781

Review 3.  Indirect Measurement of Ground Reaction Forces and Moments by Means of Wearable Inertial Sensors: A Systematic Review.

Authors:  Andrea Ancillao; Salvatore Tedesco; John Barton; Brendan O'Flynn
Journal:  Sensors (Basel)       Date:  2018-08-05       Impact factor: 3.576

4.  Robust Stride Detector from Ankle-Mounted Inertial Sensors for Pedestrian Navigation and Activity Recognition with Machine Learning Approaches.

Authors:  Bertrand Beaufils; Frédéric Chazal; Marc Grelet; Bertrand Michel
Journal:  Sensors (Basel)       Date:  2019-10-16       Impact factor: 3.576

  4 in total

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