Evidence map›Paper›PMID 34960261›Full record

ArticleSensors (Basel, Switzerland)2021

Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies.

Luca Ascari, Anna Marchenkova, Andrea Bellotti, Stefano Lai, Lucia Moro, Konstantin Koshmak, Alice Mantoan, Michele Barsotti, Raffaello Brondi, Giovanni Avveduto and 5 more

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. 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

15 authors at 2 institutions in 2 countries.

Luca AscariHenesis s.r.l., 43123 Parma, Italy.ORCID 0000-0002-0956-1598
Anna MarchenkovaInstitute of Neuroscience, National Research Council of Italy, 43125 Parma, Italy.
Andrea BellottiHenesis s.r.l., 43123 Parma, Italy.ORCID 0000-0002-9544-0310
Stefano LaiHenesis s.r.l., 43123 Parma, Italy.
Lucia MoroCamlin Italy s.r.l., 43123 Parma, Italy.
Konstantin KoshmakCamlin Italy s.r.l., 43123 Parma, Italy.ORCID 0000-0002-6479-7923
Alice MantoanHenesis s.r.l., 43123 Parma, Italy.
Michele BarsottiHenesis s.r.l., 43123 Parma, Italy.
Raffaello BrondiCamlin Italy s.r.l., 43123 Parma, Italy.
Giovanni AvvedutoHenesis s.r.l., 43123 Parma, Italy.
Davide SechiHenesis s.r.l., 43123 Parma, Italy.
Alberto CompagnoHenesis s.r.l., 43123 Parma, Italy.
Pietro AvanziniInstitute of Neuroscience, National Research Council of Italy, 43125 Parma, Italy.
Jonas Ambeck-MadsenToyota Motor Europe, 1114 Bruxelles, Belgium.
Giovanni VecchiatoInstitute of Neuroscience, National Research Council of Italy, 43125 Parma, Italy.ORCID 0000-0001-6037-5806
National Research Council · ITToyota Motor Corporation (Belgium) · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays, the growing interest in gathering physiological data and human behavior in everyday life scenarios is paralleled by an increase in wireless devices recording brain and body signals. However, the technical issues that characterize these solutions often limit the full brain-related assessments in real-life scenarios. Here we introduce the Biohub platform, a hardware/software (HW/SW) integrated wearable system for multistream synchronized acquisitions. This system consists of off-the-shelf hardware and state-of-art open-source software components, which are highly integrated into a high-tech low-cost solution, complete, yet easy to use outside conventional labs. It flexibly cooperates with several devices, regardless of the manufacturer, and overcomes the possibly limited resources of recording devices. The Biohub was validated through the characterization of the quality of (i) multistream synchronization, (ii) in-lab electroencephalographic (EEG) recordings compared with a medical-grade high-density device, and (iii) a Brain-Computer-Interface (BCI) in a real driving condition. Results show that this system can reliably acquire multiple data streams with high time accuracy and record standard quality EEG signals, becoming a valid device to be used for advanced ergonomics studies such as driving, telerehabilitation, and occupational safety.

Indexed as

Brain-Computer InterfacesWearable Electronic DevicesElectroencephalographyErgonomicsHumansSystems Analysisbehaviorbio-potentialsEEGergonomicswearable device

Identifiers

PMID34960261
PMCPMC8707223
OpenAlexW4200578128

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.