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

Overview

Authors: Mattia Galanti1,2, Filippo Battaglia3, Giovanni Gugliandolo3, Petter M Omland4, Kristian B Nilsen5, Sarah Breevoort6, M Noreen Herring7, Jerome Kurent7,6, I-Hweii A Chen8, Tuan Vu8, Kyle Wuthrich8, Nicola Donato3, Mulugeta Gebregziabher7,2, Giuseppe Campobello3, Brian C Dean1, Jonathan J Halford7
ORCID iDs: Filippo Battaglia
  1. School of Computing, Clemson University, Clemson, 29631 SC USA
  2. Department of Public Health Sciences, Medical University of South Carolina, Charleston, 29425 SC USA
  3. Department of Engineering, University of Messina, Messina, 98166 Italy
  4. Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, N-7491 Norway
  5. Department of Neurology, Section of Clinical Neurophysiology, Oslo University Hospital, Oslo, Norway
  6. Department of Neurology, Medical University of South Carolina, Charleston, 29425 SC USA
  7. Ralph H. Johnson Veterans Affairs Medical Center, Charleston, 29401 SC USA
  8. Morsani College of Medicine, University of South Florida, Tampa, 33602 FL USA
Institutions: Medical University of South Carolina (United States); Clemson University (United States); University of Messina (Italy); Norwegian University of Science and Technology (Norway); Oslo University Hospital (Norway); Ralph H. Johnson VA Medical Center (United States); University of South Florida (United States)
Journal: Journal of medical systems, volume 50, issue 1, article 126
Dates: received 11 March 2025; accepted 9 August 2026; published online 26 August 2026; in print 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1007/s10916-026-02451-9 · PMID 42645603 · PMCID PMC13518441 · OpenAlex W7204267060
Open access: hybrid, a free copy (OpenAlex)
Status: data only
Categories: EEG (modality), other (modality), human (organism), epilepsy (population)
Methods: Spectral & time-frequency, Statistics, Machine learning, Physiology & signal measures
Keywords: Data compression, EEG, EMG, MPEG-4 AAC, Neurophysiology
MeSH: Data Compression*, Electroencephalography*, Electromyography*, Signal Processing, Computer-Assisted*, Humans (* major topic)
Topic: EEG and Brain-Computer Interfaces (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: Clemson University
Citations: not cited yet (Europe PMC); 58 references in the paper

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.

Supplementary Information: The online version contains supplementary material available at 10.1007/s10916-026-02451-9.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

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Data

Datasets cited

Data Availability Statement

De-identified data supporting the findings of this study are available upon reasonable request via email.

Not applicable.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

  • Publisher: n/a → Springer Science+Business Media

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 16 authors, 5 keywords, 5 MeSH terms, 1 funder, 45 references.

Cite

This paper

Galanti, M., Battaglia, F., Gugliandolo, G., Omland, P. M., Nilsen, K. B., Breevoort, S., Herring, M. N., Kurent, J., Chen, I.-H. A., Vu, T., Wuthrich, K., Donato, N., Gebregziabher, M., Campobello, G., Dean, B. C., & Halford, J. J. (2026). Evaluation of MPEG-4 AAC Audio Codec Using EEG and EMG Signals for Use with DICOM® Neurophysiology. Journal of medical systems, 50(1), 126. https://doi.org/10.1007/s10916-026-02451-9

BibTeX

@article{galanti2026evaluation,
author = {Galanti, Mattia and Battaglia, Filippo and Gugliandolo, Giovanni and Omland, Petter M and Nilsen, Kristian B and Breevoort, Sarah and Herring, M Noreen and Kurent, Jerome and Chen, I-Hweii A and Vu, Tuan and Wuthrich, Kyle and Donato, Nicola and Gebregziabher, Mulugeta and Campobello, Giuseppe and Dean, Brian C and Halford, Jonathan J},
title = {{Evaluation of MPEG-4 AAC Audio Codec Using EEG and EMG Signals for Use with DICOM® Neurophysiology}},
journal = {Journal of medical systems},
year = {2026},
month = aug,
volume = {50},
number = {1},
pages = {126},
publisher = {Springer Science+Business Media},
issn = {0148-5598},
doi = {10.1007/s10916-026-02451-9},
url = {https://doi.org/10.1007/s10916-026-02451-9},
pmid = {42645603},
pmcid = {PMC13518441}
}

RIS

TY - JOUR
AU - Galanti, Mattia
AU - Battaglia, Filippo
AU - Gugliandolo, Giovanni
AU - Omland, Petter M
AU - Nilsen, Kristian B
AU - Breevoort, Sarah
AU - Herring, M Noreen
AU - Kurent, Jerome
AU - Chen, I-Hweii A
AU - Vu, Tuan
AU - Wuthrich, Kyle
AU - Donato, Nicola
AU - Gebregziabher, Mulugeta
AU - Campobello, Giuseppe
AU - Dean, Brian C
AU - Halford, Jonathan J
TI - Evaluation of MPEG-4 AAC Audio Codec Using EEG and EMG Signals for Use with DICOM® Neurophysiology
T2 - Journal of medical systems
J2 - J Med Syst
PY - 2026
DA - 2026/08/26
VL - 50
IS - 1
SP - 126
SN - 0148-5598
PB - Springer Science+Business Media
DO - 10.1007/s10916-026-02451-9
UR - https://doi.org/10.1007/s10916-026-02451-9
LA - en
ER -

CSL-JSON

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