Evidence map›Paper›PMID 31516957›Full record

ArticleData in brief2019

Simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement.

Paola Pierleoni, Ennio Gambi, Manola Ricciuti, Agnese Sbrollini, Lorenzo Palma, Alberto Belli, Micaela Morettini, Laura Burattini

Abstract read
In one paragraph

Article in Data in brief, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Artificial intelligence opportunities in cardio-oncology: Overview with spotlight on electrocardiography.American heart journal plus : cardiology research and practice · 2022
    Article
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.

Paola PierleoniDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
Ennio GambiDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
Manola RicciutiDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
Agnese SbrolliniDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
Lorenzo PalmaDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
Alberto BelliDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
Micaela MorettiniDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.
Laura BurattiniDepartment of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proposed dataset provides a complete set of simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement. Data were acquired on a total of 20 healthy white Caucasian subjects wearing no makeup (10 males and 10 females; age: 22.50 ± 1.57 years; height: 173 ± 10 cm; weight: 62.80 ± 9.52 kg) and consisted of: i) videos of the subject's face acquired by a RGB-D (Red, Green, Blue and Depth) camera (Microsoft Kinect v2), which is a contactless device; ii) electrocardiographic (ECG) recordings acquired by a clinical Holter ECG recorder (Global Instrumentation's M12R Holter), which is a wearable device; and iii) heart-rate measurements acquired from a commercial smartwatch (Moto 360 smartwatch by Motorola), which is also a wearable device. ECG recordings were processed to extract the R-peaks position and obtain a reference indirect measurement of the heart rate. A direct measurement of the heart rate was provided by the commercial smartwatch. The dataset here presented could be useful to develop new algorithms for heart-rate detection from contactless devices and to validate contactless heart-rate estimation in comparison to reference heart rate from clinical wearable devices and to heart rate from commercial wearable devices.

Indexed as

Contactless sensingHeart-rate measurementHolter electrocardiographyRGB-D sensorsWearable sensor

Identifiers

PMID31516957
PMCPMC6736776

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LicenceCC BY-NC-ND
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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.