Evidence map›Paper›PMID 34434848›Full record

ArticleMethodsX2021

The use of Horizon graphs to visualize bilateral biomechanical time-series of multiple joints.

Liria Akie Okai-Nobrega, Thiago Ribeiro Teles Santos, Milton Hirokazu Shimabukuro, Renan Alves Resende, Thales Rezende de Souza, Sérgio Teixeira da Fonseca

Abstract read
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Article in MethodsX, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Liria Akie Okai-NobregaGraduate Program in Rehabilitation Science, Department of Physical Therapy, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
Thiago Ribeiro Teles SantosGraduate Program in Rehabilitation Science, Department of Physical Therapy, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
Milton Hirokazu ShimabukuroDepartment of Mathematics and Computer Science, School of Technology and Applied Sciences, Universidade Estadual Paulista, Presidente Prudente, SP, Brazil.
Renan Alves ResendeGraduate Program in Rehabilitation Science, Department of Physical Therapy, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
Thales Rezende de SouzaDepartment of Mathematics and Computer Science, School of Technology and Applied Sciences, Universidade Estadual Paulista, Presidente Prudente, SP, Brazil.
Sérgio Teixeira da FonsecaGraduate Program in Rehabilitation Science, Department of Physical Therapy, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Movement analysis provides a vast amount of data, which, frequently, are not used in the clinical decision-making process. For example, traditional gait data visualization is based on a time-based display of joint angles, but part of the information is lost when these time-series are averaged across different gait strides. Horizon graph is a data display method that increases the density of time-series data by horizontally dividing and layering multiple filled line graphs. This higher data density increases the amount of information displayed in the same graph and, consequently, enables visual data comparisons between multiple time series. Horizon graph of kinematic data allows displaying several cycles of different joints and their respective continuous symmetry ratio between sides. The aim of this work is to introduce the Horizon graph as a method to analyze kinematic gait data and help to characterize its symmetry. Examples of Horizon graph application to running is offered. Horizon graph may prove to be a useful clinical tool to visualize kinematic time-series and facilitate their clinical interpretation.•Continuous gait time series is a powerful tool for clinical analysis.•Horizon graph, higher data density graph, increases the information displayed.•Horizon graph is a clinical tool to visualize kinematic curves.

Indexed as

ClinicalData visualizationMovement analysisRunning

Identifiers

PMID34434848
PMCPMC8374341

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.