Evidence map›Paper›PMID 34804462›Full record

ArticleJournal of healthcare engineering2021

A Low-Cost, Autonomous Gait Detection and Estimation System for Analyzing Gait Impairments in Mice.

Pranav U Damale, Edwin K P Chong, Sean L Hammond, Ronald B Tjalkens

Open access · hybridAbstract read
In one paragraph

Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 60% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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

4 authors at 2 institutions in 1 country.

Pranav U DamaleDepartment of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO 80523-1373, USA.ORCID 0000-0002-9817-3895
Edwin K P ChongDepartment of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO 80523-1373, USA.ORCID 0000-0002-7622-4815
Sean L HammondDivision of Clinical Pharmacology and Toxicology, University of Colorado, Anschutz, CO 80045-2608, USA.
Ronald B TjalkensDepartment of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523-1601, USA.ORCID 0000-0002-6848-4115
Colorado State University · USUniversity of Colorado Anschutz Medical Campus · US

Funding

Neuroinflammation and developmental vulnerability to manganese toxicityR01ES021656 · NIEHS · COLORADO STATE UNIVERSITY · PI TJALKENS, RONALD · 2013 to 2022
$4.2M
Encephalitic viral infection and susceptibility to dopaminergic neurotoxinsR01ES030937 · NIEHS · COLORADO STATE UNIVERSITY · PI TJALKENS, RONALD · 2019 to 2021
$1.9M
NIEHS NIH HHS R01 ES021656NIEHS NIH HHS R01 ES030937
6 · The paper itself

Abstract

With the advancement in imaging technology, many commercial systems have been developed for performing motion analysis in mice. However, available commercial systems are expensive and use proprietary software. In this paper, we describe a low-cost, camera-based design of an autonomous gait acquisition and analysis system for inspecting gait deficits in C57BL/6 mice. Our system includes video acquisition, autonomous gait-event detection, gait-parameter extraction, and result visualization. We provide a simple, user-friendly, step-by-step detailed methodology to apply well-known image processing techniques for detecting mice footfalls and calculating various gait parameters for analyzing gait abnormalities in healthy and neurotraumatic mice. The system was used in a live animal study for assessing recovery in a mouse model of Parkinson's disease. Using the videos acquired in the study, we validate the performance of our system with receiver operating characteristic (ROC) and Hit : Miss : False (H : M : F) detection analyses. Our system correctly detected the mice footfalls with an average H : M : F score of 92.1 : 2.3 : 5.6. The values for the area under an ROC curve for all the ROC plots are above 0.95, which indicates an almost perfect detection model. The ROC and H : M : F analyses show that our system produces accurate gait detection. The results observed from the gait assessment study are in agreement with the known literature. This demonstrates the practical viability of our system as a gait analysis tool.

Indexed as

GaitGait AnalysisAnimalsHumansImage Processing, Computer-AssistedMiceMice, Inbred C57BLSoftware

Identifiers

PMID34804462
PMCPMC8604610
OpenAlexW3213371258

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.