Evidence map›Paper›PMID 32899618›Full record

ArticleSensors (Basel, Switzerland)2020

Sit-To-Stand Movement Evaluated Using an Inertial Measurement Unit Embedded in Smart Glasses-A Validation Study.

Justine Hellec, Frédéric Chorin, Andrea Castagnetti, Serge S Colson

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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.

Justine HellecUniversité Côte d'Azur, LAMHESS, EUR HEALTHY, 06205 Nice, France.ORCID 0000-0003-0982-7509
Frédéric ChorinUniversité Côte d'Azur, LAMHESS, EUR HEALTHY, 06205 Nice, France.
Andrea CastagnettiEllcie Healthy, 06270 Villeneuve-Loubet, France.
Serge S ColsonUniversité Côte d'Azur, LAMHESS, EUR HEALTHY, 06205 Nice, France.ORCID 0000-0002-3315-9486

Funding

Fondation MAIF NARégion SUD Provence Alpes Côte d'Azur 2018 08943 00
6 · The paper itself

Abstract

Wearable sensors have recently been used to evaluate biomechanical parameters of everyday movements, but few have been located at the head level. This study investigated the relative and absolute reliability (intra- and inter-session) and concurrent validity of an inertial measurement unit (IMU) embedded in smart eyeglasses during sit-to-stand (STS) movements for the measurement of maximal acceleration of the head. Reliability and concurrent validity were investigated in nineteen young and healthy participants by comparing the acceleration values of the glasses' IMU to an optoelectronic system. Sit-to-stand movements were performed in laboratory conditions using standardized tests. Participants wore the smart glasses and completed two testing sessions with STS movements performed at two speeds (slow and comfortable) under two different conditions (with and without a cervical collar). Both the vertical and anteroposterior acceleration values were collected and analyzed. The use of the cervical collar did not significantly influence the results obtained. The relative reliability intra- and inter-session was good to excellent (i.e., intraclass correlation coefficients were between 0.78 and 0.91) and excellent absolute reliability (i.e., standard error of the measurement lower than 10% of the average test or retest value) was observed for the glasses, especially for the vertical axis. Whatever the testing sessions in all conditions, significant correlations (

Indexed as

MovementSmart GlassesAccelerationAgedBiomechanical PhenomenaHumansReproducibility of Resultsaccelerometerchair rise testreliabilityvertical accelerationwearable sensors

Identifiers

PMID32899618
PMCPMC7570552

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Registered trials

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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.