Evidence map›Paper›PMID 38475162›Full record

ArticleSensors (Basel, Switzerland)2024

Breath Measurement Method for Synchronized Reproduction of Biological Tones in an Augmented Reality Auscultation Training System.

Yukiko Kono, Keiichiro Miura, Hajime Kasai, Shoichi Ito, Mayumi Asahina, Masahiro Tanabe, Yukihiro Nomura, Toshiya Nakaguchi

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

8 authors.

Yukiko KonoDepartment of Medical Engineering, Graduate School of Science and Engineering, Chiba University, 1-33 Yayoicho, Inage-ku, Chiba-shi 263-8522, Chiba, Japan.
Keiichiro MiuraDepartment of Cardiovascular Medicine, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba-shi 260-8670, Chiba, Japan.
Hajime KasaiDepartment of Respirology, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba-shi 260-8670, Chiba, Japan.
Shoichi ItoDepartment of Medical Education, Graduate School of Medicine, Chiba University, 1-8-1 Inohana, Chuo-ku, Chiba-shi 260-8670, Chiba, Japan.ORCID 0000-0003-3659-6152
Mayumi AsahinaChiba University Hospital, 1-8-1 Inohana, Chuo-ku, Chiba-shi 260-8677, Chiba, Japan.
Masahiro TanabeChiba University, 1-33 Yayoicho, Inage-ku, Chiba-shi 263-8522, Chiba, Japan.
Yukihiro NomuraCenter for Frontier Medical Engineering, Chiba University, 1-33 Yayoicho, Inage-ku, Chiba-shi 263-8522, Chiba, Japan.
Toshiya NakaguchiCenter for Frontier Medical Engineering, Chiba University, 1-33 Yayoicho, Inage-ku, Chiba-shi 263-8522, Chiba, Japan.ORCID 0000-0002-8348-6178

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An educational augmented reality auscultation system (EARS) is proposed to enhance the reality of auscultation training using a simulated patient. The conventional EARS cannot accurately reproduce breath sounds according to the breathing of a simulated patient because the system instructs the breathing rhythm. In this study, we propose breath measurement methods that can be integrated into the chest piece of a stethoscope. We investigate methods using the thoracic variations and frequency characteristics of breath sounds. An accelerometer, a magnetic sensor, a gyro sensor, a pressure sensor, and a microphone were selected as the sensors. For measurement with the magnetic sensor, we proposed a method by detecting the breathing waveform in terms of changes in the magnetic field accompanying the surface deformation of the stethoscope based on thoracic variations using a magnet. During breath sound measurement, the frequency spectra of the breath sounds acquired by the built-in microphone were calculated. The breathing waveforms were obtained from the difference in characteristics between the breath sounds during exhalation and inhalation. The result showed the average value of the correlation coefficient with the reference value reached 0.45, indicating the effectiveness of this method as a breath measurement method. And the evaluations suggest more accurate breathing waveforms can be obtained by selecting the measurement method according to breathing method and measurement point.

Indexed as

Augmented RealityStethoscopesAuscultationExhalationHumansRespirationRespiratory Soundsauscultation training simulationbreathing parametersdigital filteringinertial sensorthoracic variationwearable device

Identifiers

PMID38475162
PMCPMC10934352

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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.