An Immersive Motor Protocol for Frailty Rehabilitation.

CAVE balance elderly frailty motor rehabilitation risk of falls stationary bike virtual reality

Journal

Frontiers in neurology
ISSN: 1664-2295
Titre abrégé: Front Neurol
Pays: Switzerland
ID NLM: 101546899

Informations de publication

Date de publication:
2019
Historique:
received: 09 04 2019
accepted: 24 09 2019
entrez: 5 11 2019
pubmed: 5 11 2019
medline: 5 11 2019
Statut: epublish

Résumé

Frailty is a pre-clinical condition that worsens physical health and quality of life. One of the most frequent symptoms of frailty is an increased risk of falling. In order to reduce this risk, we propose an innovative virtual reality motor rehabilitation program based on an immersive tool. All exercises will take place in the CAVE, a four-screen room with a stationary bike. The protocol will include two types of exercises for the improvement of balance: "Positive Bike" and "Avoid the Rocks." We will choose evaluation scales related to the functional aspects and subjective perception of balance. Our aim is to prove that our innovative motor rehabilitation protocol is as effective as or more effective than classical rehabilitation.

Identifiants

pubmed: 31681149
doi: 10.3389/fneur.2019.01078
pmc: PMC6803811
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1078

Informations de copyright

Copyright © 2019 Pedroli, Cipresso, Greci, Arlati, Boilini, Stefanelli, Rossi, Goulene, Sacco, Stramba-Badiale, Gaggioli and Riva.

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Auteurs

Elisa Pedroli (E)

Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.

Pietro Cipresso (P)

Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.
Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.

Luca Greci (L)

Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, Milan, Italy.

Sara Arlati (S)

Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, Milan, Italy.
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.

Lorenzo Boilini (L)

Department of Geriatrics and Cardiovascular Medicine, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.

Laura Stefanelli (L)

Department of Geriatrics and Cardiovascular Medicine, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.

Monica Rossi (M)

Department of Geriatrics and Cardiovascular Medicine, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.

Karine Goulene (K)

Department of Geriatrics and Cardiovascular Medicine, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.

Marco Sacco (M)

Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing, National Research Council, Milan, Italy.

Marco Stramba-Badiale (M)

Department of Geriatrics and Cardiovascular Medicine, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.

Andrea Gaggioli (A)

Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.
Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.

Giuseppe Riva (G)

Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano - Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy.
Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy.

Classifications MeSH