Evidence mapPaperPMID 39759110Full record

ArticleFrontiers in physiology2024

Exploring the potential of electrical bioimpedance technique for analyzing physical activity.

Abdelakram Hafid, Samaneh Zolfaghari, Annica Kristoffersson, Mia Folke

Abstract read
In one paragraph

Article in Frontiers in physiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Abdelakram HafidDivision of Intelligent Future Technologies, School of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.
Samaneh ZolfaghariDivision of Intelligent Future Technologies, School of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.
Annica KristofferssonDivision of Intelligent Future Technologies, School of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.
Mia FolkeDivision of Intelligent Future Technologies, School of Innovation, Design and Technology, Mälardalen University, Västerås, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Exercise physiology investigates the complex and multifaceted human body responses to physical activity (PA). The integration of electrical bioimpedance (EBI) has emerged as a valuable tool for deepening our understanding of muscle activity during exercise. Method: In this study, we investigate the potential of using the EBI technique for human motion recognition. We analyze EBI signals from the quadriceps muscle and extensor digitorum longus muscle acquired when healthy participants in the range 20-30 years of age performed four lower body PAs, namely squats, lunges, balance walk, and short jumps. Results: The characteristics of EBI signals are promising for analyzing PAs. Each evaluated PA exhibited unique EBI signal characteristics. Discussion: The variability in how PAs are executed leads to variations in the EBI signal characteristics, which, in turn, can provide insights into individual differences in how a person executes a specific PA.

Indexed as

electrical bioimpedancehuman motion recognitionlower body movementmuscle activityphysical activitiessignal characterization

Identifiers

PMID39759110
PMCPMC11696282

What Socratic 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 Socratic graph.