Evidence map›Paper›PMID 34345739›Full record

ArticleHeliyon2021

Judgement of valence of musical sounds by hand and by heart, a machine learning paradigm for reading the heart.

Ennio Idrobo-Ávila, Humberto Loaiza-Correa, Flavio Muñoz-Bolaños, Leon van Noorden, Rubiel Vargas-Cañas

Abstract read
In one paragraph

Article in Heliyon, 2021. 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

5 authors.

Ennio Idrobo-ÁvilaPSI - Intelligent Systems and Perception, Universidad del Valle, Cali, Colombia.
Humberto Loaiza-CorreaPSI - Intelligent Systems and Perception, Universidad del Valle, Cali, Colombia.
Flavio Muñoz-BolañosCIFIEX - Experimental Physiological Sciences, Universidad del Cauca, Popayán, Colombia.
Leon van NoordenIPEM - Institute for Systematic Musicology, Ghent University, Ghent, Belgium.
Rubiel Vargas-CañasSIDICO - Dynamic Systems Instrumentation and Control, Universidad del Cauca, Popayán, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The intention of the experiment is to investigate whether different sounds have influence on heart signal features in the situation the observer is judging the different sounds as positive or negative. As the heart is under (para)sympathetic control of the nervous system this experiment could give information about the processing of sound stimuli beyond the conscious processing of the subject. As the nature of the influence on the heart signal is not known these signals are to be analysed with AI/machine learning techniques. Heart rate variability (HRV) is a variable derived from the R-R interval peaks of electrocardiogram which exposes the interplay between the sympathetic and parasympathetic nervous system. In addition to its uses as a diagnostic tool and an active part in the clinic and research domain, the HRV has been used to study the effects of sound and music on the heart response; among others, it was observed that heart rate is higher in response to exciting music compared with tranquilizing music while heart rate variability and its low-frequency and high-frequency power are reduced. Nevertheless, it is still unclear which musical element is related to the observed changes. Thus, this study assesses the effects of harmonic intervals and noise stimuli on the heart response by using machine learning. The results show that noises and harmonic intervals change heart activity in a distinct way; e.g., the ratio between the axis of the ellipse fitted in the Poincaré plot increased between harmonic intervals and noise exposition. Moreover, the frequency content of the stimuli produces different heart responses, both with noise and harmonic intervals. In the case of harmonic intervals, it is also interesting to note how the effect of consonance quality could be found in the heart response.

Indexed as

Acoustic noiseHarmonic music intervalsHeart rate variabilityMachine learningMusic

Identifiers

PMID34345739
PMCPMC8319012

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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.