City4Age Behaviour Dataset

  1. Abril-Jiménez, Patricia 1
  2. Almeida, Aitor 2
  3. Andrić, Marina 3
  4. Waldmeyer, María Teresa Arredondo 1
  5. Azkune, Gorka 2
  6. Bryant, Nicola 4
  7. Buján, David 2
  8. Chamorro, Javier 5
  9. Christantoni, Ilia 6
  10. Copelli, Sergio 7
  11. Pérez, Silvia De Los Ríos 1
  12. Blas, Nicoletta Di 8
  13. Fasano, Francesca 9
  14. Laghi, Luca 10
  15. Mainetti, Luca 11
  16. Mercalli, Franco 7
  17. Colomer, Juan Bautista Montalvá 1
  18. Mulero, Rubén 2
  19. Paolini, Paolo 12
  20. Páramo, Miguel 1
  21. Parlangeli, Raffaele 9
  22. Patrono, Luigi 11
  23. Piercosimo Rametta
  24. Lacal, Javier Rojo 1
  25. Spencer, Nikki 4
  26. Tsakanina, Dimitra 6
  27. Urošević, Vladimir 3
  28. Montrer des auteurs +
  1. 1 Universidad Politécnica de Madrid
    info

    Universidad Politécnica de Madrid

    Madrid, España

    ROR https://ror.org/03n6nwv02

  2. 2 Universidad de Deusto
    info

    Universidad de Deusto

    Bilbao, España

    ROR https://ror.org/00ne6sr39

  3. 3 Belit d.o.o. Beograd
  4. 4 Birmingham City Council
  5. 5 Consorcio Regional de Transportes de Madrid
  6. 6 DAEM
  7. 7 MultiMed Engineers
  8. 8 Polytechnic University of Milan
    info

    Polytechnic University of Milan

    Milán, Italia

    ROR https://ror.org/01nffqt88

  9. 9 Municipality of Lecce
  10. 10 Queen Elizabeth Hospital Birmingham
    info

    Queen Elizabeth Hospital Birmingham

    Birmingham, Reino Unido

    ROR https://ror.org/048emj907

  11. 11 University of Salento
    info

    University of Salento

    Lecce, Italia

    ROR https://ror.org/03fc1k060

  12. 12 FPM
Montrer des affiliations +

Éditeur: Zenodo

Année de publication: 2019

Type: Dataset

DOI: 10.5281/ZENODO.2602651 lock_openAccès ouvert editor

Résumé

City4Age (Elderly-friendly city services for active and healthy ageing) is a research and innovation project funded by the European Commission under the Horizon 2020 Programme. The first and core objective of City4Age is to enable Ambient Assisted Cities or Age-friendly Cities. The project aims to create an innovative framework on ICT tools and services that can be deployed by European cities in order to: enhance early detection of risk related to frailty and Mild Cognitive Impairments (MCI), and provide personalised intervention that can help the elderly population to improve their daily life and also promote positive behaviour changes. The dataset contains the data captured during the 6 pilots (Madrid, Birmingham, Montpellier, Lecce, Singapore and Athens), being composed by the users’ activities and behavior both inside their home and in the city. The dataset is divided into two parts: 1) the ‘low elementary actions’ which contains the basic actions; 2) the measures which are physiological values of the monitored users. The file ‘data_format.zip’ contains the description of the dataset.