Evidence map›Paper›PMID 29359128›Full record

ArticleFrontiers in bioengineering and biotechnology2017

Virtual Reality-Based Center of Mass-Assisted Personalized Balance Training System.

Deepesh Kumar, Alejandro González, Abhijit Das, Anirban Dutta, Philippe Fraisse, Mitsuhiro Hayashibe, Uttama Lahiri

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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, 2 syntheses or guidelines pooled it.

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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

7 authors.

Deepesh KumarDepartment of Electrical Engineering, Indian Institute of Technology Gandhinagar, Gandhinagar, India.
Alejandro GonzálezINRIA Camin team and LIRMM, University of Montpellier, Montpellier, France.
Abhijit DasAMRI Institute of Neuroscience, Kolkata, India.
Anirban DuttaDepartment of Biomedical Engineering, University at Buffalo, Buffalo, NY, United States.
Philippe FraisseINRIA Camin team and LIRMM, University of Montpellier, Montpellier, France.
Mitsuhiro HayashibeINRIA Camin team and LIRMM, University of Montpellier, Montpellier, France.
Uttama LahiriDepartment of Electrical Engineering, Indian Institute of Technology Gandhinagar, Gandhinagar, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Poststroke hemiplegic patients often show altered weight distribution with balance disorders, increasing their risk of fall. Conventional balance training, though powerful, suffers from scarcity of trained therapists, frequent visits to clinics to get therapy, one-on-one therapy sessions, and monotony of repetitive exercise tasks. Thus, technology-assisted balance rehabilitation can be an alternative solution. Here, we chose virtual reality as a technology-based platform to develop motivating balance tasks. This platform was augmented with off-the-shelf available sensors such as Nintendo Wii balance board and Kinect to estimate one's center of mass (CoM). The virtual reality-based CoM-assisted balance tasks (Virtual CoMBaT) was designed to be adaptive to one's individualized weight-shifting capability quantified through CoM displacement. Participants were asked to interact with Virtual CoMBaT that offered tasks of varying challenge levels while adhering to ankle strategy for weight shifting. To facilitate the patients to use ankle strategy during weight-shifting, we designed a heel lift detection module. A usability study was carried out with 12 hemiplegic patients. Results indicate the potential of our system to contribute to improving one's overall performance in balance-related tasks belonging to different difficulty levels.

Indexed as

ankle strategybalance rehabilitationcenter of massKinectstrokevirtual reality

Identifiers

PMID29359128
PMCPMC5765271

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.