Evidence map›Paper›PMID 40807741›Full record

ArticleSensors (Basel, Switzerland)2025

Medical Data over Sound-CardiaWhisper Concept.

Radovan Stojanović, Jovan Đurković, Mihailo Vukmirović, Blagoje Babić, Vesna Miranović, Andrej Škraba

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

6 authors.

Radovan StojanovićFaculty of Electrical Engineering, University of Montenegro, 81000 Podgorica, Montenegro.ORCID 0000-0003-0906-2198
Jovan ĐurkovićMECOnet Ltd., 81000 Podgorica, Montenegro.ORCID 0009-0007-3962-7328
Mihailo VukmirovićDepartment of Cardiology, Faculty of Medicine, University of Montenegro, 81000 Podgorica, Montenegro.ORCID 0000-0001-9724-9184
Blagoje BabićDepartment of Cardiology, Faculty of Medicine, University of Montenegro, 81000 Podgorica, Montenegro.ORCID 0009-0003-2293-6643
Vesna MiranovićDepartment of Cardiology, Faculty of Medicine, University of Montenegro, 81000 Podgorica, Montenegro.ORCID 0000-0002-8783-9751
Andrej ŠkrabaCybernetics & Decision Support Systems Laboratory, Faculty of Organizational Sciences, University of Maribor, Kidričeva cesta 55a, 4000 Kranj, Slovenia.ORCID 0000-0002-4471-6743

Funding

European Union Interreg VI ARCAMinistry of Higher Education, Science and Innovation of the Republic of Slovenia C3330-22-953012Ministry of Higher Education, Science, and Innovation of the Republic of Slovenia 3330-22-3515The Slovenian Research and Innovation Agency P5-0018
6 · The paper itself

Abstract

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver-typically a smartphone, tablet, or other gadget-and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications.

Indexed as

Signal Processing, Computer-AssistedWearable Electronic DevicesAlgorithmsElectrocardiographyHumansPhotoplethysmographyData Over Sound (DoS)edge computingIoT in healthcareJavaScriptmedical wearablesmodulation and demodulationnear-ultrasound communicationreal-time signal processing

Identifiers

PMID40807741
PMCPMC12349044

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.