| dc.contributor.author | Moreno Ligero, Marta | |
| dc.contributor.author | Lucena Antón, David Manuel | |
| dc.contributor.author | Salazar Couso, Alejandro | |
| dc.contributor.author | Failde Martínez, Inmaculada | |
| dc.contributor.author | Moral Muñoz, José Antonio | |
| dc.contributor.other | Biomedicina, Biotecnología y Salud Pública | es_ES |
| dc.contributor.other | Enfermería y Fisioterapia | es_ES |
| dc.contributor.other | Estadística e Investigación Operativa | es_ES |
| dc.date.accessioned | 2024-03-11T10:04:24Z | |
| dc.date.available | 2024-03-11T10:04:24Z | |
| dc.date.issued | 2023-07-18 | |
| dc.identifier.issn | 0148-5598 | |
| dc.identifier.uri | http://hdl.handle.net/10498/31348 | |
| dc.description.abstract | Gait and dynamic balance are two main goals in neurorehabilitation that mHealth systems could address. To analyze the impact of using mHealth systems on gait and dynamic balance outcomes in subjects with neurological disorders. Randomized controlled trials (RCT) published in PubMed, Web of Science, Scopus, and PEDro databases were searched up to April 2023. Studies including adults with neurological disorders, analyzing the effectiveness of mHealth systems on gait and dynamic balance compared with conventional therapy and/or not intervention, were included. The PEDro scale and the Cochrane Collaboration’s 2.0 tool were used for the methodological quality and risk of bias assessment. The Review Manager 5.4 software was used to obtain meta-analyses. 13 RCT were included in the systematic review and 11 in the meta-analyses, involving 528 subjects. A total of 21 mobile applications were identified for gait and balance training, and to enhance physical activity behaviors. There were significant differences in gait parameters, speed by 0.10 s/m (95% confidence interval (CI)=0.07,0.13;p<0.001), cadence by 8.01 steps/min (95%CI=3.30,12.72;p<0.001), affected step length by 8.89 cm (95%CI=4.88,12.90;p<0.001), non-affected step length by 8.08 cm (5%CI=2.64,13.51;p=0.004), and in dynamic balance, Timed Up and Go by -7.15 s (95%CI=-9.30,-4.99;p<0.001), and mobility subscale of Posture Assessment Scale for Stroke by 1.71 points (95%CI=1.38,2.04;p[removed] | es_ES |
| dc.format | application/pdf | es_ES |
| dc.language.iso | eng | es_ES |
| dc.publisher | Springer | es_ES |
| dc.rights | Atribución 4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.source | Journal of Medical Systems. Vol. 47, nº 1, December 2023, 75 | es_ES |
| dc.subject | Gait | es_ES |
| dc.subject | mHealth | es_ES |
| dc.subject | Balance | es_ES |
| dc.subject | Mobile applications | es_ES |
| dc.subject | Neurological disorders | es_ES |
| dc.subject | Rehabilitation | es_ES |
| dc.title | mHealth Impact on Gait and Dynamic Balance Outcomes in Neurorehabilitation: Systematic Review and Meta-analysis | es_ES |
| dc.type | journal article | es_ES |
| dc.rights.accessRights | open access | es_ES |
| dc.description.physDesc | 19 páginas | es_ES |
| dc.identifier.doi | 10.1007/s10916-023-01963-y | |
| dc.relation.projectID | FPU19/04377 | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/Ministerio de Educación y Formación Profesional//FPU19%2F04377/ | es_ES |
| dc.type.hasVersion | VoR | es_ES |