COGNITIO COGNITIO

COGNITIO COGNITIO

 : 

Case-Based Reasoning for the optimization of cognitive rehabilitation on TBI Case-Based Reasoning for the optimization of cognitive rehabilitation on TBI

A Project coordinated by IIIA.

Principal investigator:

Josep Lluís Arcos Josep Lluís Arcos

Collaborating organisations:

Universidad Politécnica de Madrid, Fundació Privada Institut de Neurorehabilitació Guttmann Universidad Politécnica de Madrid, Fundació Privada Institut de Neurorehabilitació Guttmann

Funding entity:

TIN2012-38450- C03-03 TIN2012-38450- C03-03

Funding call:

Project #:

COGNITIO COGNITIO

Funding amount:

0,00€ 0,00€

Duration:

2013-01-01 2013-01-01

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2015-12-31 2015-12-31
Acquired Brain Injury (ABI) constitutes a major and increasing social and healthcare concern of high diagnostic and therapeutic complexity. Its incidence and survival rate after the initial critical phases makes it a prevalent problem that needs to be addressed. ABI patients frequently suffer from a series of cognitive disorders related to memory, attention, language, or executive functions. Cognitive rehabilitation aims to reduce the impact of the disabling conditions in order to reduce functional limitations and increase patient's autonomy. For the rehabilitation process to be more effective, treatments must be intensive, personalized to the patient's condition and evidence-based; and require constant monitoring. The main goal of the IIIA team is the research on new machine learning/CBR techniques able to propose and revise personalized therapies in real-time. Acquired Brain Injury (ABI) constitutes a major and increasing social and healthcare concern of high diagnostic and therapeutic complexity. Its incidence and survival rate after the initial critical phases makes it a prevalent problem that needs to be addressed. ABI patients frequently suffer from a series of cognitive disorders related to memory, attention, language, or executive functions. Cognitive rehabilitation aims to reduce the impact of the disabling conditions in order to reduce functional limitations and increase patient's autonomy. For the rehabilitation process to be more effective, treatments must be intensive, personalized to the patient's condition and evidence-based; and require constant monitoring. The main goal of the IIIA team is the research on new machine learning/CBR techniques able to propose and revise personalized therapies in real-time.
2016
Joan SerràJosep Lluis Arcos; Particle Swarm Optimization for Time Series Motif Discovery. Knowledge-Based Systems; 2016.  [BibTeX]
Joan SerràIsabel SerraÁlvaro CorralJosep Lluis Arcos; Ranking and significance of variable-length similarity-based time series motifs. Expert Systems with Applications, Elsevier; 2016.  [BibTeX]
2015
Eva ArmengolJosep Puyol-Gruart; A Simple Experiment to Guide the Design of a Preference Model. 2015.  [PDF]  [BibTeX]
2014
Joan SerràJosep Lluis Arcos; An empirical evaluation of similarity measures for time series classification. Knowledge-Based Systems; 2014.  [PDF]  [BibTeX]
2013
Joan SerràJosep Lluis ArcosAlejandro Garcia-RudolphAlberto García-MolinaTeresa RoigJosep Maria Tormos; Cognitive prognosis of acquired brain injury patients using machine learning techniques. 2013.  [PDF]  [BibTeX]