Evidence map›Paper›PMID 29667028›Full record

ReviewJournal of medical systems2018

A Review of Commercial and Medical-Grade Physiological Monitoring Devices for Biofeedback-Assisted Quality of Life Improvement Studies.

Pedro Nogueira, Joana Urbano, Luís Paulo Reis, Henrique Lopes Cardoso, Daniel Castro Silva, Ana Paula Rocha, Joaquim Gonçalves, Brígida Mónica Faria

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of medical systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

6 citing papers in PubMed, 21 citations in OpenAlex.

  1. Trial
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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 at 3 institutions in 1 country.

Pedro NogueiraArtificial Intelligence and Computer Science Laboratory (LIACC), Porto, Portugal. pedro.alves.nogueira@fe.up.pt.
Joana UrbanoArtificial Intelligence and Computer Science Laboratory (LIACC), Porto, Portugal.
Luís Paulo ReisArtificial Intelligence and Computer Science Laboratory (LIACC), Porto, Portugal.
Henrique Lopes CardosoArtificial Intelligence and Computer Science Laboratory (LIACC), Porto, Portugal.
Daniel Castro SilvaArtificial Intelligence and Computer Science Laboratory (LIACC), Porto, Portugal.
Ana Paula RochaArtificial Intelligence and Computer Science Laboratory (LIACC), Porto, Portugal.
Joaquim GonçalvesEST/IPCA - Technology School/Polytechnic Institute of Cávado and Ave, Barcelos, Portugal.
Brígida Mónica FariaArtificial Intelligence and Computer Science Laboratory (LIACC), Porto, Portugal.
Universidade do Porto · PTPolytechnic Institute of Cávado and Ave · PTUniversity of Minho · PT

Funding

LIACC PEst-UID/CEC/00027/2013PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund NORTE-01-0247-FEDER-003446
6 · The paper itself

Abstract

With the rise in wearable technology and "health culture", we are seeing an increasing interest and affordances in studying how to not only prolong life expectancy but also in how to improve individuals' quality of life. On the one hand, this attempts to give meaning to the increasing life expectancy, as living above a certain threshold of pain and lack of autonomy or mobility is both degrading and unfair. On the other hand, it lowers the cost of continuous care, as individuals with high quality of life indexes tend to have lower hospital readmissions or secondary complications, not to mention higher physical and mental health. In this paper, we evaluate the current state of the art in physiological therapy (biofeedback) along with the existing medical grade and consumer grade hardware for physiological research. We provide a quick primer on the most commonly monitored physiologic metrics, as well as a brief discussion on the current state of the art in biofeedback-assisted medical applications. We then go on to present a comparative analysis between medical and consumer grade biofeedback devices and discuss the hardware specifications and potential practical applications of each consumer grade device in terms of functionality and adaptability for controlled (laboratory) and uncontrolled (field) studies. We end this article with some empirical observations based on our study so that readers might use take them into consideration when arranging a laboratory or real-world experience, thus avoiding costly time delays and material expenditures.

Indexed as

Quality of LifeBiofeedback, PsychologyBody TemperatureElectromyographyGalvanic Skin ResponseHemodynamicsHumansMonitoring, AmbulatoryOximetryRemote Sensing TechnologyRespirationBiofeedbackConsumer grade hardwareFitness trackingPsychophysiologyQuality of life

Identifiers

PMID29667028
OpenAlexW2801761100

What OpenQuestion holds

Textmetadata
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.