Evidence map›Paper›PMID 34315497›Full record

ArticleJournal of neuroengineering and rehabilitation2021

A wearable ring-shaped inertial system to identify action planning impairments during reach-to-grasp sequences: a pilot study.

Erika Rovini, Guenda Galperti, Valeria Manera, Gianmaria Mancioppi, Laura Fiorini, Auriane Gros, Philippe Robert, Filippo Cavallo

Open access · goldAbstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 53% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Smart Ring in Clinical Medicine: A Systematic Review.Biomimetics (Basel, Switzerland) · 2025
    Review
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 2 countries.

Erika RoviniDepartment of Industrial Engineering, University of Florence, Florence, Italy.
Guenda GalpertiThe BioRobotics Institute of Scuola Superiore Sant'Anna, Pontedera, Pisa, Italy.
Valeria ManeraCoBTeK Lab of the Université Cote D'Azur, Nice, France.
Gianmaria MancioppiThe BioRobotics Institute of Scuola Superiore Sant'Anna, Pontedera, Pisa, Italy.
Laura FioriniDepartment of Industrial Engineering, University of Florence, Florence, Italy.
Auriane GrosCoBTeK Lab of the Université Cote D'Azur, Nice, France.
Philippe RobertCoBTeK Lab of the Université Cote D'Azur, Nice, France.
Filippo CavalloDepartment of Industrial Engineering, University of Florence, Florence, Italy. filippo.cavallo@unifi.it.ORCID 0000-0001-7432-5033
Cognition Behaviour Technology · FRScuola Superiore Sant'Anna · ITUniversity of Florence · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe progressive ageing of the population is leading to an increasing number of people affected by cognitive decline, including disorders in executive functions (EFs), such as action planning. Current procedures to evaluate cognitive decline are based on neuropsychological tests, but novel methods and approaches start to be investigated. Reach-to-grasp (RG) protocols have shown that intentions can influence the EFs of action planning. In this work, we proposed a novel ring-shaped wearable inertial device, SensRing, to measure kinematic parameters during RG and after-grasp (AG) tasks with different end-goals. The aim is to evaluate whether SensRing can characterize the motor performances of people affected by Mild Neurocognitive Disorder (MND) with impairment in EFs.

methodsEight Individuals with dysexecutive MND, named d-MND, were compared to ten older healthy subjects (HC). They were asked to reach and grasp a can with three different intentions: to drink (DRINK), to place it on a target (PLACE), or to pass it to a partner (PASS). Twenty-one kinematic parameters were extracted from SensRing inertial data.

resultsSeven parameters resulted able to differentiate between HC and d-MND in the RG phase, and 8 features resulted significant in the AG phase. d-MND, indeed, had longer reaction times (in RG PLACE), slower peak velocities (in RG PLACE and PASS, in AG DRINK and PLACE), longer deceleration phases (in all RG and AG DRINK), and higher variability (in RG PLACE, in AG DRINK and PASS). Furthermore, d-MND showed no significant differences among conditions, suggesting that impairments in EFs influence their capabilities in modulating the action planning based on the end-goal.

conclusionsBased on this explorative study, the system might have the potential for objectifying the clinical assessment of people affected by d-MND by administering an easy motor test. Although these preliminary results have to be investigated in-depth in a larger sample, the portability, wearability, accuracy, and ease-of use of the system make the SensRing potentially appliable for remote applications at home, including analysis of protocols for neuromotor rehabilitation in patients affected by MND.

Indexed as

Hand StrengthWearable Electronic DevicesBiomechanical PhenomenaHumansMotivationPilot ProjectsAction planningDysexecutive syndromeExecutive functionsMild cognitive impairmentMotor programmingReach-to-grasp

Identifiers

PMID34315497
PMCPMC8314592
OpenAlexW3111225351

What OpenQuestion holds

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LicenceCC BY
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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.