Evidence map›Paper›PMID 42244815›Full record

ArticleArXiv2026

Cross-Modal Characterization of Infant Cry: Validation of a Chest-Surface Accelerometer in Extracting Acoustic Vocal Function Measures.

Winko W An, Saketh Sundar, Lisa Yankowitz, Daryush D Mehta, Carol L Wilkinson

Abstract readPreprint
In one paragraph

Article in ArXiv, 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

5 authors.

Winko W AnDivision of Developmental Medicine, Boston Children's Hospital, Boston, MA 02115 USA, and also with Harvard Medical School, Boston, MA 02115 USA.
Saketh SundarDivision of Developmental Medicine, Boston Children's Hospital, Boston, MA 02115 USA, and also with Harvard University, Cambridge, MA 02138 USA.
Lisa YankowitzChildren's Hospital of Philadelphia, Philadelphia, PA 19104 USA.
Daryush D MehtaHarvard Medical School, Boston, MA 02115 USA, and also with the Center for Laryngeal Surgery and Voice Rehabilitation, Massachusetts General Hospital, Boston, MA 02114 USA.
Carol L WilkinsonDivision of Developmental Medicine, Boston Children's Hospital, Boston, MA 02115 USA, and also with Harvard Medical School, Boston, MA 02115 USA.

Funding

Use of ambulatory biofeedback to improve behavioral treatment of vocal hyperfunctionP50DC015446 · NIDCD · MASSACHUSETTS GENERAL HOSPITAL · PI Robert E Hillman · 2017 to 2026
$25.5M
Predicting ASD and Other Developmental Outcomes in the First Year of Life Using EEG in a Diverse Community-Based Sample (Revision)R01NS120986 · NINDS · BOSTON CHILDREN'S HOSPITAL · PI CHARLES Alexander NELSON, Helen Tager-Flusberg · 2022 to 2026
$4.9M
NIDCD NIH HHS P50 DC015446NINDS NIH HHS R01 NS120986
6 · The paper itself

Abstract

Infant cry acoustics provide a promising window into early neurodevelopment and may serve as scalable biomarkers for neurodevelopmental disorders. However, conventional microphone-based recordings are highly susceptible to environmental noise and raise privacy concerns in real-world clinical settings. Chest-surface accelerometers may offer a robust alternative by capturing vibrations directly from the larynx. We evaluated the validity of a chest-mounted accelerometer (ACC) for infant cry analysis by comparing acoustic features derived from ACC and simultaneously recorded microphone (MIC) signals during routine vaccination visits. The final sample included 85 infants (41 at 4 months; 44 at 12 months) from a diverse pediatric population. Seven vocal measures were extracted from both modalities, including fundamental frequency (F0), jitter, shimmer, cepstral peak prominence (CPP), and harmonics-to-noise ratio (HNR). Agreement and consistency between modalities were assessed using intraclass correlation coefficients (ICCs). F0 demonstrated excellent agreement between ACC and MIC recordings (ICC > 0.94). Jitter measures also showed good-to-excellent agreement, while CPP demonstrated moderate agreement. Shimmer and HNR showed lower absolute agreement and systematic bias between modalities, reflecting possible differences in signal transmission and noise sensitivity. In summary, chest-surface accelerometers can reliably capture several clinically relevant acoustic features of infant cry, particularly temporal measures of F0 and jitter. This approach offers a noise-robust and privacy-preserving alternative to microphone-based recordings, supporting its potential use in scalable clinical and developmental research applications.

Indexed as

acousticschest-surface accelerometerInfant crymulti-modality agreement

Identifiers

PMID42244815
PMCPMC13232432

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LicenceCC BY-NC-ND
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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.