A Preliminary Study for Automatic Activity Labelling on an Elder PeopleADL Dataset

• Cal, Enrique de la ^[1] ; Mirko Fáñez ^[2] ; Alvaro DaSilva ^[2] ; José Ramón Villar ^[1] ; Javier Sedano ^[2] ; Victor Suárez ^[1]
  1. [1] Universidad de Oviedo

     Universidad de Oviedo

     Oviedo, España

     
  2. [2] Instituto Tecnológico de Castilla y León

     Instituto Tecnológico de Castilla y León

     Burgos, España

     
• Localización: 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020 / coord. por Álvaro Herrero Cosío, Carlos Cambra Baseca, Daniel Urda Muñoz, Javier Sedano Franco, Héctor Quintián Pardo, Emilio Santiago Corchado Rodríguez, 2021, ISBN 978-3-030-57802-2, págs. 13-21
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • One consequence of the aging population is an increase in life expectancy implying greater healthcare needs as well as a serious healthy aging program. So healthy aging is one of the main challenges in the first world nowadays, and as much as possible devices, software and technological solutions applied to measure and improve the quality of life of the elder people are necessary.Recently, we presented a first prototype of an activity monitoring kit, and this study includes the analysis of the dataset gathered after six months of use. Since the wearable devices employed in this monitoring kit have not the automatic activity recognition service available, current work proposes several techniques to label automatically the Time Series (TS) obtained in the experiment. Thus, a new device with the same sensors as the old one plus the automatic activity recognition service available will be used to obtain a new labelled dataset, that will be used to learn a new model using semi-supervised learning to tag the not-labelled dataset.