Evidence map›Paper›PMID 38544161›Full record

ArticleSensors (Basel, Switzerland)2024

Embodimetrics: A Principal Component Analysis Study of the Combined Assessment of Cardiac, Cognitive and Mobility Parameters.

Andrea Chellini, Katia Salmaso, Michele Di Domenico, Nicola Gerbi, Luigi Grillo, Marco Donati, Marco Iosa

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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
0.4field-weighted citation impact, top 39% 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 citations in OpenAlex.

  1. Article
  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

7 authors at 2 institutions in 1 country.

Andrea ChelliniBehaviour & Movement, 50142 Firenze, Italy.
Katia SalmasoBehaviour & Movement, 50142 Firenze, Italy.
Michele Di DomenicoEmbodimetria, 65121 Pescara, Italy.
Nicola GerbiEmbodimetria, 56038 Ponsacco, Italy.
Luigi GrilloSmart Lab, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.
Marco DonatiMotustech, 00012 Guidonia, Italy.
Marco IosaSmart Lab, IRCCS Santa Lucia Foundation, 00179 Rome, Italy.ORCID 0000-0003-2434-3887
Fondazione Santa Lucia · ITSigno Motus (Italy) · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a growing body of literature investigating the relationship between the frequency domain analysis of heart rate variability (HRV) and cognitive Stroop task performance. We proposed a combined assessment integrating trunk mobility in 72 healthy women to investigate the relationship between cognitive, cardiac, and motor variables using principal component analysis (PCA). Additionally, we assessed changes in the relationships among these variables after a two-month intervention aimed at improving the perception-action link. At baseline, PCA correctly identified three components: one related to cardiac variables, one to trunk motion, and one to Stroop task performance. After the intervention, only two components were found, with trunk symmetry and range of motion, accuracy, time to complete the Stroop task, and low-frequency heart rate variability aggregated into a single component using PCA. Artificial neural network analysis confirmed the effects of both HRV and motor behavior on cognitive Stroop task performance. This analysis suggested that this protocol was effective in investigating embodied cognition, and we defined this approach as "embodimetrics".

Indexed as

CognitionTask Performance and AnalysisFemaleHeartHumansPrincipal Component AnalysisStroop Testartificial intelligenceembodimentheart rate variabilitymotor controlStroop task

Identifiers

PMID38544161
PMCPMC10976222
OpenAlexW4392845077

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.