Evidence map›Paper›PMID 29534448›Full record

ArticleSensors (Basel, Switzerland)2018

Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation.

Giuseppe Placidi, Luigi Cinque, Matteo Polsinelli, Matteo Spezialetti

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. A DICOM-based standard for quantitative physical rehabilitation.Computational and structural biotechnology journal · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
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.

Giuseppe PlacidiA²VI_Lab, Department of Life, Health & Environmental Sciences, University of L'Aquila, Via Vetoio 1, 67100 Coppito, L'Aquila, Italy. giuseppe.placidi@univaq.it.ORCID 0000-0002-4790-4029
Luigi CinqueDepartment of Computer Science, Sapienza University, Via Salaria 113, Rome 00198, Italy. cinque@di.uniroma1.it.
Matteo PolsinelliA²VI_Lab, Department of Life, Health & Environmental Sciences, University of L'Aquila, Via Vetoio 1, 67100 Coppito, L'Aquila, Italy. matteo.polsinelli@student.univaq.it.
Matteo SpezialettiA²VI_Lab, Department of Life, Health & Environmental Sciences, University of L'Aquila, Via Vetoio 1, 67100 Coppito, L'Aquila, Italy. matteo.spezialetti@graduate.univaq.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hand rehabilitation is fundamental after stroke or surgery. Traditional rehabilitation requires a therapist and implies high costs, stress for the patient, and subjective evaluation of the therapy effectiveness. Alternative approaches, based on mechanical and tracking-based gloves, can be really effective when used in virtual reality (VR) environments. Mechanical devices are often expensive, cumbersome, patient specific and hand specific, while tracking-based devices are not affected by these limitations but, especially if based on a single tracking sensor, could suffer from occlusions. In this paper, the implementation of a multi-sensors approach, the Virtual Glove (VG), based on the simultaneous use of two orthogonal LEAP motion controllers, is described. The VG is calibrated and static positioning measurements are compared with those collected with an accurate spatial positioning system. The positioning error is lower than 6 mm in a cylindrical region of interest of radius 10 cm and height 21 cm. Real-time hand tracking measurements are also performed, analysed and reported. Hand tracking measurements show that VG operated in real-time (60 fps), reduced occlusions, and managed two LEAP sensors correctly, without any temporal and spatial discontinuity when skipping from one sensor to the other. A video demonstrating the good performance of VG is also collected and presented in the Supplementary Materials. Results are promising but further work must be done to allow the calculation of the forces exerted by each finger when constrained by mechanical tools (e.g., peg-boards) and for reducing occlusions when grasping these tools. Although the VG is proposed for rehabilitation purposes, it could also be used for tele-operation of tools and robots, and for other VR applications.

Indexed as

Gloves, ProtectiveHandHand StrengthHumansStroke RehabilitationUser-Computer InterfaceVirtual Realityhand rehabilitationhand trackingLEAP motion controllerVirtual Glove

Identifiers

PMID29534448
PMCPMC5877317

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.