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Article type: Research Article
Authors: Mendoza Laiz, Nuriaa | Del Valle Díaz, Sagrarioa; * | Rioja Collado, Nataliaa | Gomez-Pilar, Javierb | Hornero, Robertob
Affiliations: [a] Department of Physical Activity and Sport Sciences, University of Castilla-La Mancha (UCLM), Toledo, Spain | [b] Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
Correspondence: [*] Corresponding author: Sagrario Del Valle Díaz, PhD., Professor, University of Castilla-La Mancha (UCLM), Avda. Carlos III, s/n. 45571 Toledo (Spain). Tel.: +34 925268800; E-mail: [email protected].
Abstract: Background:Dementia is a disease that is constantly evolving in older people. Its diverse symptoms appear with varying degrees of severity affecting the daily life of those who suffer from it. The rate in which dementia progresses depends on different aspects of the treatment, chosen to try to control and slow down the development of the illness. Objective:The aim of this study is to assess the effectiveness of cognitive training through a Brain Computer Interface (BCI) and the NeuronUp platform in two age groups whose MMSE is between 18–23 MCI (mild dementia). Method:32 subjects took part in the study. There were 22 subjects in Group 1 (61–69 years of age) and 10 subjects in Group 2 (70–81 years of age). The criterium for the selection of the groups was to identify the age range with greater improvements due to the training. In order to estimate neuropsychological performance, the subjects were evaluated with the Luria-DNA neuropsychological battery before and after training. This design enables us to evaluate five cognitive areas: visuospatial, spoken language, memory, intellectual processes and attention. Results:After training, Group 1 showed significant improvements in almost all the variables measured when compared with Group 2. This reveals a significant increase in cognitive ability, the degree of which depends on the age. Conclusion:People with mild dementia may delay cognitive impairment with a suitable cognitive training program.
Keywords: MCI, BCI, Neuro-feedback, Luria-DNA, independence ageing, autonomy ageing
DOI: 10.3233/RNN-170754
Journal: Restorative Neurology and Neuroscience, vol. 36, no. 2, pp. 207-213, 2018
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