Evidence map›Paper›PMID 34770477›Full record

ReviewSensors (Basel, Switzerland)2021

Biopotential Signal Monitoring Systems in Rehabilitation: A Review.

Arrigo Palumbo, Patrizia Vizza, Barbara Calabrese, Nicola Ielpo

Open access · goldAbstract readReview
In one paragraph

Review 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 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

25 citing papers in PubMed, 77 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Arrigo PalumboDepartment of Medical and Surgical Sciences, Magna Græcia University, 88100 Catanzaro, Italy.ORCID 0000-0002-1554-9210
Patrizia VizzaMater Domini University Hospital, 88100 Catanzaro, Italy.ORCID 0000-0002-0014-478X
Barbara CalabreseDepartment of Medical and Surgical Sciences, Magna Græcia University, 88100 Catanzaro, Italy.ORCID 0000-0003-2123-8221
Nicola IelpoDepartment of Medical and Surgical Sciences, Magna Græcia University, 88100 Catanzaro, Italy.ORCID 0000-0002-7313-8882
Magna Graecia University · IT

Funding

Ministry of Education, Universities and Research SCN$_$00558 "H@H (Health@Home)" Simple - Smart Solutions for health monitoring and independent mobility for elderly and disable people
6 · The paper itself

Abstract

Monitoring physical activity in medical and clinical rehabilitation, in sports environments or as a wellness indicator is helpful to measure, analyze and evaluate physiological parameters involving the correct subject's movements. Thanks to integrated circuit (IC) technologies, wearable sensors and portable devices have expanded rapidly in monitoring physical activities in sports and tele-rehabilitation. Therefore, sensors and signal acquisition devices became essential in the tele-rehabilitation path to obtain accurate and reliable information by analyzing the acquired physiological signals. In this context, this paper provides a state-of-the-art review of the recent advances in electroencephalogram (EEG), electrocardiogram (ECG) and electromyogram (EMG) signal monitoring systems and sensors that are relevant to the field of tele-rehabilitation and health monitoring. Mostly, we focused our contribution in EMG signals to highlight its importance in rehabilitation context applications. This review focuses on analyzing the implementation of sensors and biomedical applications both in literature than in commerce. Moreover, a final review discussion about the analyzed solutions is also reported at the end of this paper to highlight the advantages of physiological monitoring systems in rehabilitation and individuate future advancements in this direction. The main contributions of this paper are (i) the presentation of interesting works in the biomedical area, mainly focusing on sensors and systems for physical rehabilitation and health monitoring between 2016 and up-to-date, and (ii) the indication of the main types of commercial sensors currently being used for biomedical applications.

Indexed as

ElectrocardiographySportsElectroencephalographyElectromyographyMonitoring, Physiologicbiomedical signalmonitoring systemrehabilitationsignal processing

Identifiers

PMID34770477
PMCPMC8587479
OpenAlexW3211093741

What OpenQuestion holds

Textmetadata
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.