Evidence map›Paper›PMID 33805690›Full record

ArticleSensors (Basel, Switzerland)2021

Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring.

Bríd McDevitt, Lisa Moore, Nishat Akhtar, James Connolly, Rónán Doherty, William Scott

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 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.8field-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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

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  10. State-of-the-Art Sensors Research in Ireland.Sensors (Basel, Switzerland) · 2022
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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

6 authors at 1 institution in 1 country.

Bríd McDevittDepartment of Computing, Letterkenny Institute of Technology, Letterkenny, F92 FC93 Donegal, Ireland.ORCID 0000-0001-6813-920X
Lisa MooreDepartment of Science, Letterkenny Institute of Technology, Letterkenny, F92 FC93 Donegal, Ireland.
Nishat AkhtarDepartment of Computing, Letterkenny Institute of Technology, Letterkenny, F92 FC93 Donegal, Ireland.
James ConnollyDepartment of Computing, Letterkenny Institute of Technology, Letterkenny, F92 FC93 Donegal, Ireland.ORCID 0000-0002-7970-1699
Rónán DohertyDepartment of Law & Humanities, Letterkenny Institute of Technology, Letterkenny, F92 FC93 Donegal, Ireland.ORCID 0000-0002-7808-1715
William ScottDepartment of Science, Letterkenny Institute of Technology, Letterkenny, F92 FC93 Donegal, Ireland.
Letterkenny Institute of Technology · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the midst of the COVID-19 pandemic, Remote Patient Monitoring technologies are highly important for clinicians and researchers. These connected-health technologies enable monitoring of patients and facilitate remote clinical trial research while reducing the potential for the spread of the novel coronavirus. There is a growing requirement for monitoring of the full 24 h spectrum of behaviours with a single research-grade sensor. This research describes a free-living and supervised protocol comparison study of the Verisense inertial measurement unit to assess physical activity and sleep parameters and compares it with the Actiwatch 2 actigraph. Fifteen adults (11 males, 23.4 ± 3.4 years and 4 females, 29 ± 12.6 years) wore both monitors for 2 consecutive days and nights in the free-living study while twelve adults (11 males, 23.4 ± 3.4 years and 1 female, 22 ± 0 years) wore both monitors for the duration of a gym-based supervised protocol study. Agreement of physical activity epoch-by-epoch data with activity classification of sedentary, light and moderate-to-vigorous activity and sleep metrics were evaluated using Spearman's rank-order correlation coefficients and Bland-Altman plots. For all activity, Verisense showed high agreement for both free-living and supervised protocol of r = 0.85 and r = 0.78, respectively. For physical activity classification, Verisense showed high agreement of sedentary activity of r = 0.72 for free-living but low agreement of r = 0.36 for supervised protocol; low agreement of light activity of r = 0.42 for free-living and negligible agreement of r = -0.04 for supervised protocol; and moderate agreement of moderate-to-vigorous activity of r = 0.52 for free-living with low agreement of r = 0.49 for supervised protocol. For sleep metrics, Verisense showed moderate agreement for sleep time and total sleep time of r = 0.66 and 0.54, respectively, but demonstrated high agreement for determination of wake time of r = 0.83. Overall, our results showed moderate-high agreement of Verisense with Actiwatch 2 for assessing epoch-by-epoch physical activity and sleep, but a lack of agreement for activity classifications. Future validation work of Verisense for activity cut-point potentially holds promise for 24 h continuous remote patient monitoring.

Indexed as

TelemedicineAccelerometryActigraphyAdolescentAdultCOVID-19ExerciseFemaleHumansMaleMiddle AgedMonitoring, AmbulatoryPandemicsReproducibility of ResultsSARS-CoV-2Sleepaccelerometeractigraphyactivity cut-pointsDigital Healthcarefree-livinghealth behaviorsinertial measurement unitphysical activitysleep monitoringsupervised protocol

Identifiers

PMID33805690
PMCPMC7998122
OpenAlexW3138317114

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.