Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with acquired brain injury

BackgroundThis paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The ITA is integrated in “Guttmann, Neuro Personal Trainer” (GNPT), a cognitive tele-rehabilitation platform that provides neuropsychological services.MethodsThe ITA selects those tasks that are more suitable for the specific needs of each patient, considering previous experiences, and improving the personalization of the treatment. The system applies data mining techniques to cluster the patients according their cognitive impairment profile. Then, the algorithm rates every rehabilitation task, based on its cognitive structure and the clinical impact of executions done by similar patients. Finally, it configures the most suitable degree of difficulty, depending on the impairment of the patient and his/her evolution during the treatment.ResultsThe ITA has been evaluated during 18 months by 582 patients. In order to evaluate the effectiveness of the ITA, a comparison between the traditional manual planning procedure and the one presented in this paper has been done, taking into account: a) the selected tasks assigned to rehabilitation sessions; b) the difficulty level configured for the sessions; c) and the improvement of their cognitive capacities after completing treatment.ConclusionsThe obtained results reveal that the rehabilitation treatment proposed by the ITA is as effective as the one performed manually by therapists, arising as a new powerful support tool for therapists. The obtained results make us conclude that the proposal done by the ITA is very close to the one done by therapists, so it is suitable for real treatments.

[1]  Thomas Ewert,et al.  Linking health-status measurements to the international classification of functioning, disability and health. , 2002, Journal of rehabilitation medicine.

[2]  E. J. Aguilera,et al.  2D-Tasks for Cognitive Rehabilitation , 2011 .

[3]  Javier Solana Sánchez,et al.  Clustering techniques for patients suffering acquired brain injury inneuro personal trainer , 2013 .

[4]  Yee Lee Shing,et al.  Aging Neuroscience , 2022 .

[5]  Joanne Azulay,et al.  Evidence-based cognitive rehabilitation: updated review of the literature from 2003 through 2008. , 2011, Archives of physical medicine and rehabilitation.

[6]  Carlo Caltagirone,et al.  Telecommunications technology in cognitive rehabilitation. , 2008, Functional neurology.

[7]  R. Chesnut,et al.  Effect of cognitive rehabilitation on outcomes for persons with traumatic brain injury: A systematic review. , 1999, The Journal of head trauma rehabilitation.

[8]  L. C. Álvaro,et al.  [Hospitalizations for acute cerebrovascular accidents and transient ischemic attacks in Spain: temporal stability and spatial heterogeneity, 1998-2003]. , 2009, Revista de calidad asistencial : organo de la Sociedad Espanola de Calidad Asistencial.

[9]  J. Giacino,et al.  Evidence-based cognitive rehabilitation: updated review of the literature from 1998 through 2002. , 2005, Archives of physical medicine and rehabilitation.

[10]  C. Cáceres,et al.  Clinical program of cognitive tele-rehabilitation for traumatic brain injury , 2010, eChallenges e-2010 Conference.

[11]  Enrique J. Gómez,et al.  Data mining applied to the cognitive rehabilitation of patients with acquired brain injury , 2013, Expert Syst. Appl..

[12]  E. Balas,et al.  Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success , 2005, BMJ : British Medical Journal.

[13]  L C Alvaro,et al.  [Hospitalizations for acute cerebrovascular accidents and transient ischemic attacks in Spain: temporal stability and spatial heterogeneity, 1998-2003]. , 2009, Revista de calidad asistencial : organo de la Sociedad Espanola de Calidad Asistencial.

[14]  F. Servadei,et al.  A systematic review of brain injury epidemiology in Europe , 2006, Acta Neurochirurgica.

[15]  Jean Sanderson,et al.  The Role of Decision Support System (DSS) in Prevention of Cardiovascular Disease: A Systematic Review and Meta-Analysis , 2012, PloS one.

[16]  Kensaku Kawamoto,et al.  Clinical decision support for genetically guided personalized medicine: a systematic review , 2013, J. Am. Medical Informatics Assoc..

[17]  M J Rosen,et al.  Aspects of human factors engineering in home telemedicine and telerehabilitation systems. , 1999, Telemedicine journal : the official journal of the American Telemedicine Association.

[18]  S. Cross,et al.  Antibody negative coeliac disease presenting in elderly people—an easily missed diagnosis , 2005, BMJ : British Medical Journal.

[19]  Javier Solana Sánchez,et al.  PREVIRNEC A new platform for cognitive tele-rehabilitation , 2011 .

[20]  S E Palsbo,et al.  Telerehabilitation: managed care's new opportunity. , 2000, Managed care quarterly.

[21]  Bradley J. Morris,et al.  Gaming science: the “Gamification” of scientific thinking , 2013, Front. Psychol..

[22]  Paul E. Johnson,et al.  Impact of Electronic Health Record Clinical Decision Support on Diabetes Care: A Randomized Trial , 2011, The Annals of Family Medicine.

[23]  G. Winocur,et al.  Cognitive neurorehabilitation : evidence and application , 2008 .

[24]  Cleofé Peña-Gómez,et al.  Changes in Cortical Plasticity Across the Lifespan , 2011, Front. Ag. Neurosci..