Evidence map›Paper›PMID 38076417›Full record

ArticleFrontiers in bioengineering and biotechnology2023

Integrated software for multi-dimensional analysis of motion using tracking, electrophysiology, and sensor signals.

Eis Annavini, Jean-Luc Boulland

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Eis AnnaviniDivision of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
Jean-Luc BoullandDivision of Physiology, Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tracking followed by analysis of specific point-of-interest from conventional or high-speed video recordings have been widely used for decades in various scientific disciplines such as sport, physiotherapy, and behavioral science. Another method used to characterize movement in 3D involves the use of motion capture systems, which produce files containing a collection of 3D-coordinates and corresponding timestamps. When studying animal or human movement, combining motion tracking with other recording methods-like monitoring muscle activity or sensor signals-can yield valuable insights. However, manual analysis of data from these diverse sources can be time-consuming and prone to errors. To address this issue, this article introduces a new, free, and open-source software developed in MATLAB. This software can be used as-is, or developed further to meet specific requirements. Once the coordinates are imported, multiple tools can be used for data preprocessing, such as to correct mistakes that may have occurred during tracking because of software errors or suboptimal video quality. In addition, the software can import coordinates from multiple cameras and combine them into a unified data series. With these inputs, the software can automatically calculate kinematic parameters and descriptive statistics, generate 2D and 3D animations, and analyze gait cycles, enabling swift and accurate analysis of multidimensional motion data. Moreover, the software can import electrophysiology traces and sensor signals, which can be filtered, rectified, smoothed, and correlated with the kinematic data in various ways. Thanks to its user-friendly graphical user interface, the software is easy to navigate and can be used to analyze complex movements without any need for coding skills. This versatile tool is well-suited for a wide range of experimental contexts, making it a valuable resource for researchers across diverse scientific disciplines.

Indexed as

analysiselectrophysiologyintegratedmotionopen sourcesensorssoftware

Identifiers

PMID38076417
PMCPMC10703477

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.