Evidence map›Paper›PMID 36833815›Full record

ArticleInternational journal of environmental research and public health2023

Inertial Sensor Location for Ground Reaction Force and Gait Event Detection Using Reservoir Computing in Gait.

Sara Havashinezhadian, Laurent Chiasson-Poirier, Julien Sylvestre, Katia Turcot

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 28% 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, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Review
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.

Sara HavashinezhadianInterdisciplinary Center for Research in Rehabilitation and Social Integration (CIRRIS), Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC G1V 0A6, Canada.
Laurent Chiasson-PoirierDepartment of Mechanical Engineering, Interdisciplinary Institute for Technological Innovation, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada.
Julien SylvestreDepartment of Mechanical Engineering, Interdisciplinary Institute for Technological Innovation, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada.ORCID 0000-0002-9390-7052
Katia TurcotInterdisciplinary Center for Research in Rehabilitation and Social Integration (CIRRIS), Department of Kinesiology, Faculty of Medicine, Université Laval, Quebec, QC G1V 0A6, Canada.ORCID 0000-0003-2649-3459
Centre for Interdisciplinary Research in Rehabilitation · CAUniversité de Sherbrooke · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inertial measurement units (IMUs) have shown promising outcomes for estimating gait event detection (GED) and ground reaction force (GRF). This study aims to determine the best sensor location for GED and GRF prediction in gait using data from IMUs for healthy and medial knee osteoarthritis (MKOA) individuals. In this study, 27 healthy and 18 MKOA individuals participated. Participants walked at different speeds on an instrumented treadmill. Five synchronized IMUs (Physilog

Indexed as

GaitOsteoarthritis, KneeBiomechanical PhenomenaHumansLower ExtremityMechanical PhenomenaWalkinggait event detectionground reaction forceinertial measurement unitreservoir computingsensor location

Identifiers

PMID36833815
PMCPMC9962509
OpenAlexW4319970260

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.