Cargando…
A model of healthy aging based on smartphone interactions reveals advanced behavioral age in neurological disease
Smartphones offer unique opportunities to trace the convoluted behavioral patterns accompanying healthy aging. Here we captured smartphone touchscreen interactions from a healthy population (N = 684, ∼309 million interactions) spanning 16 to 86 years of age and trained a decision tree regression mod...
Autores principales: | Ceolini, Enea, Brunner, Iris, Bunschoten, Johanna, Majoie, Marian H.J.M., Thijs, Roland D., Ghosh, Arko |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9418593/ https://www.ncbi.nlm.nih.gov/pubmed/36039359 http://dx.doi.org/10.1016/j.isci.2022.104792 |
Ejemplares similares
-
Common multi-day rhythms in smartphone behavior
por: Ceolini, Enea, et al.
Publicado: (2023) -
Temporal clusters of age-related behavioral alterations captured in smartphone touchscreen interactions
por: Ceolini, Enea, et al.
Publicado: (2022) -
Artificial neural network trained on smartphone behavior can trace epileptiform activity in epilepsy
por: Duckrow, Robert B., et al.
Publicado: (2021) -
Fundoscopy in the smartphone age: current ophthalmoscopy methods in neurology
por: Corr, Richard Henrik
Publicado: (2023) -
The details of past actions on a smartphone touchscreen are reflected by intrinsic sensorimotor dynamics
por: Balerna, Myriam, et al.
Publicado: (2018)