Parkinson’s Disease Classification Using Inertial Signals from Smartwatches and Tree-Based Classifiers
Resumo
This study evaluates the use of statistical features extracted from inertial signals obtained from smartwatches to assist in distinguishing patients with Parkinson’s disease, differential diagnoses, and healthy controls. Using a public dataset comprising data from 469 individuals, tree-based classifiers were applied. The results indicate that simple motion information can support the diagnosis of Parkinson’s disease in a non-invasive and accessible manner.
Palavras-chave:
Parkinson's Disease, Smartwatches, Inertial Signals, Tree-Based Classifiers, Diagnosis
Referências
Bloem, B. R., Okun, M. S., and Klein, C. (2021). Parkinson’s disease. The Lancet, 397(10291):2284–2303.
Braak, H. and Braak, E. (2000). Pathoanatomy of parkinson’s disease. J Neurol, 247 Suppl 2:II3–10.
Delrobaei, M., Memar, S., Pieterman, M., Stratton, T., McIsaac, K., and Jog, M. (2017). Towards Remote Monitoring of Parkinson’s Disease Tremor using Wearable Motion Capture Systems. Journal of the Neurological Sciences, 384.
Maetzler, W. and Hausdorff, J. M. (2012). Motor signs in the prodromal phase of parkinson’s disease. Movement Disorders, 27(5):627–633.
Poewe, W., Seppi, K., Tanner, C. M., Halliday, G. M., Brundin, P., Volkmann, J., Schrag, A.-E., and Lang, A. E. (2017). Parkinson disease. Nature Reviews Disease Primers, 3(1):1–21.
Varghese, J., Brenner, A., Fujarski, M., van Alen, C. M., Plagwitz, L., and Warnecke, T. (2024). Machine Learning in the Parkinson’s disease smartwatch (PADS) dataset. npj Parkinson’s Disease, 10(1):9.
Zhou, Z. D., Yi, L. X., Wang, D. Q., Lim, T. M., and Tan, E. K. (2023). Role of dopamine in the pathophysiology of parkinson’s disease. Translational Neurodegeneration, 12(1):44.
Braak, H. and Braak, E. (2000). Pathoanatomy of parkinson’s disease. J Neurol, 247 Suppl 2:II3–10.
Delrobaei, M., Memar, S., Pieterman, M., Stratton, T., McIsaac, K., and Jog, M. (2017). Towards Remote Monitoring of Parkinson’s Disease Tremor using Wearable Motion Capture Systems. Journal of the Neurological Sciences, 384.
Maetzler, W. and Hausdorff, J. M. (2012). Motor signs in the prodromal phase of parkinson’s disease. Movement Disorders, 27(5):627–633.
Poewe, W., Seppi, K., Tanner, C. M., Halliday, G. M., Brundin, P., Volkmann, J., Schrag, A.-E., and Lang, A. E. (2017). Parkinson disease. Nature Reviews Disease Primers, 3(1):1–21.
Varghese, J., Brenner, A., Fujarski, M., van Alen, C. M., Plagwitz, L., and Warnecke, T. (2024). Machine Learning in the Parkinson’s disease smartwatch (PADS) dataset. npj Parkinson’s Disease, 10(1):9.
Zhou, Z. D., Yi, L. X., Wang, D. Q., Lim, T. M., and Tan, E. K. (2023). Role of dopamine in the pathophysiology of parkinson’s disease. Translational Neurodegeneration, 12(1):44.
Publicado
04/12/2025
Como Citar
LOBO, Pedro L. S.; CHAGAS, Ana Luísa de Bastos; BUCCI, Giordana de Farias F. B.; SALVINI, Rogerio L.; SOARES, Fabrizzio A.; FELIX, Juliana P..
Parkinson’s Disease Classification Using Inertial Signals from Smartwatches and Tree-Based Classifiers. In: ESCOLA REGIONAL DE INFORMÁTICA DE GOIÁS (ERI-GO), 13. , 2025, Luziânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 354-357.
DOI: https://doi.org/10.5753/erigo.2025.17135.
