Evidence map›Paper›PMID 42645603›Full record

ArticleJournal of medical systems2026

Evaluation of MPEG-4 AAC Audio Codec Using EEG and EMG Signals for Use with DICOM® Neurophysiology.

Mattia Galanti, Filippo Battaglia, Giovanni Gugliandolo, Petter M Omland, Kristian B Nilsen, Sarah Breevoort, M Noreen Herring, Jerome Kurent, I-Hweii A Chen, Tuan Vu and 6 more

Abstract read
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In one paragraph

Article in Journal of medical systems, 2026. 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

16 authors.

Mattia GalantiSchool of Computing, Clemson University, Clemson, 29631, SC, USA. mgalant@clemson.edu.
Filippo BattagliaDepartment of Engineering, University of Messina, Messina, 98166, Italy.
Giovanni GugliandoloDepartment of Engineering, University of Messina, Messina, 98166, Italy.
Petter M OmlandDepartment of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, N-7491, Norway.
Kristian B NilsenDepartment of Neurology, Section of Clinical Neurophysiology, Oslo University Hospital, Oslo, Norway.
Sarah BreevoortDepartment of Neurology, Medical University of South Carolina, Charleston, 29425, SC, USA.
M Noreen HerringRalph H. Johnson Veterans Affairs Medical Center, Charleston, 29401, SC, USA.
Jerome KurentRalph H. Johnson Veterans Affairs Medical Center, Charleston, 29401, SC, USA.
I-Hweii A ChenMorsani College of Medicine, University of South Florida, Tampa, 33602, FL, USA.
Tuan VuMorsani College of Medicine, University of South Florida, Tampa, 33602, FL, USA.
Kyle WuthrichMorsani College of Medicine, University of South Florida, Tampa, 33602, FL, USA.
Nicola DonatoDepartment of Engineering, University of Messina, Messina, 98166, Italy.
Mulugeta GebregziabherRalph H. Johnson Veterans Affairs Medical Center, Charleston, 29401, SC, USA.
Giuseppe CampobelloDepartment of Engineering, University of Messina, Messina, 98166, Italy.
Brian C DeanSchool of Computing, Clemson University, Clemson, 29631, SC, USA.
Jonathan J HalfordRalph H. Johnson Veterans Affairs Medical Center, Charleston, 29401, SC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern neurophysiological recording technologies are producing large volumes of data. This study investigates the use of the Moving Picture Experts Group version 4 Advanced Audio Coding (MPEG-4 AAC) for compressing electroencephalography (EEG) and electromyography (EMG) signals. All EEG signals contained either seizures or interictal epileptiform discharges (IEDs), which are nonstationary patterns characterized by sharp transients. Differences between pairs of original single-channel signals and compressed/decompressed signals were explored using the Percentage Root Mean Square Difference (PRD), power spectral density (PSD) features, and clinical expert opinion of waveform morphology. PRD was used as the primary error measure and PSD features were explored across different frequency bands. The results showed substantial decline in signal quality based on human expert opinion for compressed then reconstructed EEG signals with PRD error greater than 15% and EMG signals with PRD greater than 1%. PSD analysis showed significant changes in the gamma and beta bands for both EEG and EMG signals. This study provides further evidence that standard audio codecs which use psychoacoustic models, such as MPEG-4 AAC, do not sufficiently support compression of neurophysiology waveforms.

Indexed as

Data CompressionElectroencephalographyElectromyographySignal Processing, Computer-AssistedHumansData compressionEEGEMGMPEG-4 AACNeurophysiology

Identifiers

PMID42645603
PMCPMC13518441

What OpenQuestion holds

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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.