Evidence map›Paper›PMID 41755034›Full record

ArticleSensors (Basel, Switzerland)2026

A Testbed for the Development and Validation of Contactless Vital Signs Monitoring Systems.

Zaid Farooq Pitafi, He Yang, Jiayu Chen, Yingjian Song, Jin Ye, Zion Tse, Kenan Song, WenZhan Song

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

8 authors.

Zaid Farooq PitafiSchool of Electrical & Computer Engineering, University of Georgia, Athens, GA 30602, USA.ORCID 0009-0004-0126-9244
He YangSchool of Electrical & Computer Engineering, University of Georgia, Athens, GA 30602, USA.
Jiayu ChenSchool of Electrical & Computer Engineering, University of Georgia, Athens, GA 30602, USA.
Yingjian SongSchool of Electrical & Computer Engineering, University of Georgia, Athens, GA 30602, USA.
Jin YeSchool of Electrical & Computer Engineering, University of Georgia, Athens, GA 30602, USA.
Zion TseSchool of Engineering and Materials Science, Queen Mary University of London, 327 Mile End Rd, Bethnal Green, London E1 4NS, UK.
Kenan SongSchool of Electrical & Computer Engineering, University of Georgia, Athens, GA 30602, USA.
WenZhan SongSchool of Electrical & Computer Engineering, University of Georgia, Athens, GA 30602, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contactless monitoring of vital signs such as heart rate (HR) and respiratory rate (RR) has gained significant attention, with vibration-based sensors like geophones showing promise for accurate, non-invasive monitoring. However, most existing systems are developed with healthy subjects and may not generalize well to extreme physiological ranges, such as those observed in infants or patients with arrhythmia. Moreover, the underlying mechanisms of cardiorespiratory vibration dynamics remain insufficiently understood, limiting clinical adoption of these systems. To address these challenges, we present a programmable cardiorespiratory testbed capable of generating realistic HR and RR signals across a wide range (HR: 40-240 bpm, RR: 8-40 bpm). Our system uses a voice coil motor that acts as the vibration source, driven by a Raspberry Pi-based control circuit. Unlike similar systems that use separate modules for heart and lung signals, our setup generates both signals using a single motor. The synthetic signals exhibit a strong correlation of 0.85 compared with data from 75 human subjects. We use this system to design signal processing-based algorithms for vital signs monitoring and demonstrate their robustness for extreme physiological ranges. The proposed system enhances the understanding of cardiorespiratory vibration dynamics while significantly reducing the time and effort required to collect real-world data.

Indexed as

Vital SignsAlgorithmsHeart RateHumansMonitoring, PhysiologicRespiratory RateSignal Processing, Computer-AssistedVibrationalgorithm validationcardiorespiratory testbedcontactless vital signs monitoringsignal processingsystem development

Identifiers

PMID41755034
PMCPMC12944418

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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.