Evidence map›Paper›PMID 36772674›Full record

ArticleSensors (Basel, Switzerland)2023

Using Wearable Inertial Sensors to Monitor Effectiveness of Different Types of Customized Orthoses during CrossFit

Lorenzo Brognara, Antonio Mazzotti, Federica Rossi, Francesca Lamia, Elena Artioli, Cesare Faldini, Francesco Traina

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

7 authors.

Lorenzo BrognaraDepartment of Biomedical and Neuromotor Sciences, University of Bologna, 40123 Bologna, Italy.
Antonio MazzottiDepartment of Biomedical and Neuromotor Sciences, University of Bologna, 40123 Bologna, Italy.ORCID 0000-0001-9974-4787
Federica RossiDepartment of Biomedical and Neuromotor Sciences, University of Bologna, 40123 Bologna, Italy.
Francesca LamiaData Analyst, Stat.Sci, University of Bologna, 40136 Bologna, Italy.
Elena Artioli1st Orthopaedic and Traumatologic Clinic, IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy.ORCID 0000-0001-9279-4722
Cesare FaldiniDepartment of Biomedical and Neuromotor Sciences, University of Bologna, 40123 Bologna, Italy.
Francesco TrainaDepartment of Biomedical and Neuromotor Sciences, University of Bologna, 40123 Bologna, Italy.ORCID 0000-0002-0196-101X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDynamic balance plays a key role in high-impact sports, such as CrossFit, where athletes are required to maintain balance in various weightlifting exercises. The loss of balance in these sport-specific movements may not only affect athlete performance, but also increase the risk of injuries.

objectivesThe aim of the study is to achieve greater insight into the balance and athlete position during the CrossFit training by means of inertial sensors, with a particular focus on the role of different custom foot orthoses (CFOs) in order to detect correlations with the role of the cavus foot.

methodsA total of 42 CrossFit

resultsWhen comparing the effects of CFOs with the respective balance basal level during the pistol squat exercise, we observed a significant (

conclusionNo significant positive effects of CFOs were observed in some static tests. On the contrary, positive effects of CFOs and, in particular, postural insoles, are relevant to dynamic balance.

Indexed as

Foot OrthosesWearable Electronic DevicesFootHumansMovementPostural Balancefoot orthosisinertial sensorinstabilitypostural balancerisk factorsstability

Identifiers

PMID36772674
PMCPMC9918956

What OpenQuestion holds

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Registered trials

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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.