Evidence map›Paper›PMID 40170412›Full record

ArticleJournal of Yeungnam medical science2025

Emerging technologies in the field of medicine presented at the Consumer Electronics Show 2025.

Jong-Ryul Yang, Min Cheol Chang

Abstract read
In one paragraph

Article in Journal of Yeungnam medical science, 2025. 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

2 authors.

Jong-Ryul YangDepartment of Electrical and Electronics Engineering, Konkuk University, Seoul, Korea.
Min Cheol ChangDepartment of Physical Medicine and Rehabilitation, Yeungnam University College of Medicine, Daegu, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Consumer Electronics Show 2025 highlighted innovative technologies with considerable potential for healthcare, particularly artificial intelligence (AI) and sensor technologies. Notable advances that were showcased included products that leverage AI to personalize health management, such as devices capable of recommending binaural beat stimulation, analyzing speech patterns to detect language impairment, and predicting blood pressure through sleep data analysis. AI applications to enhance sleep quality, reduce snoring, and assess the caloric content of children's meals were presented. However, the accuracy of these products remains inadequate for clinical use, which limits their applications in community settings. This showcase also featured advances in both contact and noncontact sensor technologies. Contact-type sensors, such as wearable rings and sensors designed to measure vital signs, including pulse rate, blood glucose, and blood pressure, have been developed to mitigate discomfort while maintaining high accuracy. Noncontact sensors employing radar and remote photoplethysmography technologies have further demonstrated promise for vital sign monitoring without physical contact, although maintaining accuracy during movement remains a challenge. AI integration with sensors was further demonstrated by the development of an electronic stethoscope utilizing microelectromechanical systems and deep learning algorithms to facilitate the perception of heart and breath sounds, emulating the functionality of conventional stethoscopes. Furthermore, advances in laser-based blood glucose monitoring and wearable robotic belts designed to assist gait have underscored the progress in devices aimed at enhancing patient care and daily living. These technologies hold considerable potential to profoundly transform healthcare systems, particularly in home and community settings.

Indexed as

Artificial intelligenceConsumer electronicsMedicineSensorTechnology

Identifiers

PMID40170412
PMCPMC12303779

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.