Evidence map›Paper›PMID 39460209›Full record

ArticleSensors (Basel, Switzerland)2024

Quantifying Hand Motion Complexity in Simulated Sailing Using Inertial Sensors.

Gurdeep Sarai, Prem Prakash Jayaraman, Nilmini Wickramasinghe, Oren Tirosh

Abstract 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. 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.

Gurdeep SaraiSchool of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.
Prem Prakash JayaramanSchool of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0003-4500-3443
Nilmini WickramasingheSchool of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia.
Oren TiroshSchool of Health Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia.ORCID 0000-0002-2281-6399

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The control of hand movement during sailing is important for performance. To quantify the amount of regularity and the unpredictability of hand fluctuations during the task, the mathematical algorithm Approximate Entropy (ApEn) of the hand acceleration can be used. Approximate Entropy is a mathematical algorithm that depends on the combination of two input parameters including (1) the length of the sequences to be compared (m), and (2) the tolerance threshold for accepting similar patterns between two segments (r). The aim of this study is to identify the proper combinations of 'm' and 'r' parameter values for ApEn measurement in the hand movement acceleration data during sailing. Inertial Measurement Units (IMUs) recorded acceleration data for both the mainsail (non-dominant) and tiller (dominant) hands across the X-, Y-, and Z-axes, as well as vector magnitude. ApEn values were computed for 24 parameter combinations, with 'm' ranging from 2 to 5 and 'r' from 0.10 to 0.50. The analysis revealed significant differences in acceleration ApEn regularity between the two hands, particularly along the Z-axis, where the mainsail hand exhibited higher entropy values (

Indexed as

AccelerationAlgorithmsHandMovementAccelerometryAdultBiomechanical PhenomenaEntropyHumansMaleShipsYoung Adultapproximate entropy (ApEn)handednessinertial measurement units (IMUs)motion time-series analysissailing simulation

Identifiers

PMID39460209
PMCPMC11511208

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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.