Replication data for: Home-based telerehabilitation improves quality of life and shoulder range of motion in individuals with chronic post-stroke impairments: A randomize controlled trial

DOI

This dataset contains clinical, patient-reported, and joint range-of-motion variables collected during a randomized controlled trial evaluating a home-based non-immersive virtual reality telerehabilitation system (Muvity) for individuals with chronic post-stroke impairments.

The study was conducted between 2023 and 2024 in Catalonia (Spain), involving participants recruited through primary care centers and outpatient rehabilitation services located in rural and semi-rural regions.

The dataset includes baseline (V1) and post-intervention (V2) assessments of upper-limb motor function, balance, functional independence, pain, stroke-specific quality of life, and active joint range of motion captured using the Muvity system.

Additionally, derived pre-post change variables (Delta = V2 − V1) used in the statistical analyses are included.

The primary efficacy analyses reported in the associated manuscript were conducted on a per-protocol subsample of 27 participants with complete post-intervention assessments.

JMP Pro, 18

MATLAB, R2023a

Identifier
DOI https://doi.org/10.34810/DATA3306
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/DATA3306
Provenance
Creator Molas-Ferrer, Cris Unai ORCID logo; Serrancolí, Gil ORCID logo
Publisher CORA.Repositori de Dades de Recerca
Contributor Molas Ferrer, Cris Unai; Serrancolí, Gil; Universitat Politècnica de Catalunya; Associació Diversitat Funcional Osona; Universitat Autònoma Barcelona
Publication Year 2026
Funding Reference Generalitat de Catalunya DDS008/22/000342
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact Molas Ferrer, Cris Unai (Universitat Autònoma de Barcelona); Serrancolí, Gil (Universitat Politècnica de Catalunya)
Representation
Resource Type Clinical data; Dataset
Format text/csv; text/plain
Size 3954; 10234
Version 1.0
Discipline Life Sciences; Medicine