Healthcare & Active Ageing

The CAOS lab specializes in the applications of machine learning and big data technologies in different fields of Healthcare and Active Aging. We also have a long track record of developments in other aspects of information and telecommunication technologies in healthcare.

Research Lines

CAOS research lines in healthcare & active ageing are the following: big data in healthcare, ambient assisted living, predictive models, electronic healthcare, personal healthcare systems.

Big data in healthcare, with a specific focus on using routinely acquired data from the Electronic Healthcare Recordto identify and stratify patients according to the risks and costs of chronic disease.

Big data in healthcare

Big data in healthcare

Ambient Assisted living, systems and algorithms for behavioral monitoring, activity recognition and anomaly detection for elderly patients living alone.

Activity Recognition

Activity Recognition

Predictive models, predictive models in healthcare, with applications in Subaracnoid Haemorrage and ICU monitoring data.

Predictive Models

Predictive Models

Electronic Healthcare, record models and interoperability of healthcare information systems.

Interoperability

Interoperability

Personal healthcare systems, devices and algorithms for the remote monitoring of patients living with chronic disease.

Patient Monitoring

Patient Monitoring

Publications (summary)

  • Sensor-based Bayesian detection of anomalous living patterns in a home setting. Ordoñez FJ, de Toledo P, Sanchis A. Personal and Ubiquitous Computing. February 2015, Volume 19, Issue 2, pp 259-270 (2015)
  • Bayesian Inference in Hidden Markov Models for In-Home Activity Recognition. FJ Ordóñez, G Englebienne, P de Toledo, T van Kasteren, A Sanchis, B Kröse. . IEEE Pervasive Computing. Vol.13 (3), pp.67,75 (2014)
  • Usability and interoperability in wireless sensor networks for patient telemonitoring in chronic disease management. Jimenez-Fernandez, S., De Toledo, P., Del Pozo, F. IEEE Transactions on Biomedical Engineering, 60 (12,3331-9. (2013)
  • Activity recognition using hybrid generative/discriminative models on home environments using binary sensors. JF Ordóñez, de Toledo P, Sanchis A. Sensors (Switzerland), 13(5), 5460-77. (2013)
  • Online Activity Recognition using Evolving Classifiers. F.J. Ordoñez, J.A. Iglesias, M.Toledo, A. I. Ledezma y A. Sanchis, Expert Systems With Applications. 40 (4), 1248- 1255,(2013). http://dx.doi.org/10.1016/j.eswa.2012.08.066 issn 0957-4174.
  • Predicting the outcome of patients with Subarachnoid Hemorrhage using machine learning techniques. De Toledo P, Rios PM, Ledesma A, Sanchis A, Alen JF, Lagares A.. Accepted for publication in IEEE Transactions on Information Technology in Biomedicine (March 2009)
  • Implementation of an End-to-End Standards-based Patient Monitoring Solution. Martínez I, Fernández J, Galarraga M, Serrano L, de Toledo P, et al. IET Communications . vol 2, issue 2, pp181-191. 2008
  • Interoperability of a Mobile Health Care Solution with Electronic Healthcare Record Systems. De Toledo P, Lalinde W, del Pozo F, Thurber D, Jimenez S.. 28th IEEE EMBS Annual International Conference. pp 5214-5217. 2006.
  • Telemedicine Experience for Chronic Care in COPD De Toledo P, Jiménez S, Del Pozo F, Roca J, Alonso A, Hernandez C.. IEEE Transactions on Information Technology in Biomedicine. vol 10, issue 3, p.p. 567-573. 2006.
  • Integrated care prevents hospitalization for exacerbation in COPD patients. Casas A, Troosters T, García-Aymerich J, Roca J, Hernández C, Alonso A, del Pozo F, de Toledo P, Antó JM, Rodríguez-Roisín R, Decramer M. Eur Respir J, 2006 28: 123-130.

Research projects

  • Trainutri. Training and Nutrition senior social platform. European Commission. Ambient assisted living joint programme. Principal Investigator. 2011-2013

Participation in research projects

  • PreDiCT-TB. Model-based preclinical development of anti-tuberculosis drug combinations. European Commission. Innovative Medicines Initiative (IMI). 2012-2017
  • Topus: Tomografía por Emisión de Positrones y Ultrasonidos. S2013/MIT-3024. Programa de Actividades de I+D en Tecnologías . Comunidad de Madrid
  • Spanish Telemedicine Research Network. Grant by the Spanish Ministry of Health. 2003-2007. Technical manager.
  • Perseia: Personal and self-configurable wireless network for home telemonitoring in telemedicine applications. Grant by the Madrid’s Regional Authority. 2005. Technical manager.
  • HealthMate. Personal intelligent health mobile systems for Tele-care and Tele-consultation. European Commision-IST. 2001-2003. Technical manager
  • Chronic: An Information capture and processing environment for Chronic Patients in the Information Society. European Commision-IST. Technical manager. 1999-2002.

Research collaborations

The CAOS lab has stable collaborations with the following institutions:

  • Institute of Biomedical Engineering. University of Oxford
  • Hospital 12 de Octubre de Madrid
  • Hospital de Fuenlabrada
  • Asociación Parkinson Madrid
  • Integrating the Healthcare Enterprise standard development Organization
  • Cruz Roja de Colombia
  • Infolab21, School of Computing and Communications, Lancaster University