Assessment of Tremor Severity in Patients with Essential Tremor Using Smartwatches
Ver/ abrir
Use este enlace para citar
http://hdl.handle.net/2183/25743
A non ser que se indique outra cousa, a licenza do ítem descríbese como Atribución-NoComercial-CompartirIgual 4.0 España
Coleccións
Metadatos
Mostrar o rexistro completo do ítemTítulo
Assessment of Tremor Severity in Patients with Essential Tremor Using SmartwatchesAutor(es)
Data
2017Cita bibliográfica
Velasco, M.A., López Blanco, R., Romero Muñoz, J.P., Castillo Sobrino, M.D., Serrano Moreno, J.I., Benito León, J., Rocón de Lima, E . B Assessment of Tremor Severity in Patients with Essential Tremor Using Smartwatches. En Actas de las XXXVIII Jornadas de Automática, Gijón, 6-8 de Septiembre de 2017 (pp.347-352). DOI capítulo: https://doi.org/10.17979/spudc.9788497497749.0347 DOI libro: : https://doi.org/10.17979/spudc.9788497497749
Versións
http://hdl.handle.net/10651/46514
Resumo
[Abstract] This paper presents a classification model for the automatic quantification of tremor severity in patients with essential tremor (ET). The system is based on the signals measured by two commercial smartwatches that the patients wear on their wrist and ankle. The smartwatches register acceleration and angular velocity in these body segments. A set of nine tremor features were used to train the classification algorithm. The proposed algorithm is based on a C4.5 decision tree classifier. It is able to assess rest and kinetic (postural or action) tremor. The method was evaluated using data collected from thirty-four patients with ET. The algorithm classifies the severity of tremor in five levels 0-4 corresponding to those in the Fahn-Tolosa-Marin tremor rating scale with a 94% accuracy. The method can be implemented in a networked platform for the remote monitoring and assessment of movement disorders such as ET or Parkinson’s disease.
Palabras chave
Tremor assessment
Time series classification
Essential tremor
Time series classification
Essential tremor
Versión do editor
Dereitos
Atribución-NoComercial-CompartirIgual 4.0 España
ISBN
978-84-16664-74-0 (UOV) 978-84-9749-774-9 (UDC electrónico)