Modelling Ecological Cognitive Rehabilitation Therapies for Building Virtual Environments in Brain Injury
23 March 2015
accepted 16 June 2015
08 January 2018 (online)
Background: Brain Injury (BI) has become one of the most common causes of neurological disability in developed countries. Cognitive disorders result in a loss of independence and patients’ quality of life. Cognitive rehabilitation aims to promote patients’ skills to achieve their highest degree of personal autonomy. New technologies such as virtual reality or interactive video allow developing rehabilitation therapies based on reproducible Activities of Daily Living (ADLs), increasing the ecological validity of the therapy. However, the lack of frameworks to formalize and represent the definition of this kind of therapies can be a barrier for widespread use of interactive virtual environments in clinical routine. Objectives: To provide neuropsychologists with a methodology and an instrument to design and evaluate cognitive rehabilitation therapeutic interventions strategies based on ADLs performed in interactive virtual environments. Methods: The proposed methodology is used to model therapeutic interventions during virtual ADLs considering cognitive deficit, expected abnormal interactions and therapeutic hypotheses. It allows identifying abnormal behavioural patterns and designing interventions strategies in order to achieve errorless-based rehabilitation. Results: An ADL case study (’buying bread’) is defined according to the guidelines established by the ADL intervention model. This case study is developed, as a proof of principle, using interactive video technology and is used to assess the feasibility of the proposed methodology in the definition of therapeutic intervention procedures. Conclusions: The proposed methodology provides neuropsychologists with an instrument to design and evaluate ADL-based therapeutic intervention strategies, attending to solve actual limitation of virtual scenarios, to be use for ecological rehabilitation of cognitive deficit in daily clinical practice. The developed case study proves the potential of the methodology to design therapeutic interventions strategies; however our current work is devoted to designing more experiments in order to present more evidence about its values.
- 1 Elbaum J. Acquired Brain Injury and the Family. Acquired Brain Injury. Springer; 2007. pp 275-285.
- 2 Barbara Woodward Lips Patient Education Center.. Understanding Brain Injury. A Guide for the Family. 2008
- 3 Karol RL. Neuropsychosocial intervention: The practical treatment of severe behavioral dyscontrol after acquired brain injury. CRC press; 2003
- 4 Marcotte TD, Cobb Scott J, Kamat R, Heaton RK. Neuropsychology and the Prediction of Everyday Functioning. In: Marcotte TD, Grant I. editors. Neuropsychology of Everyday Functioning. The Guilford Press; 2010. pp 5-38.
- 5 Kaplan RM, Mausbach BT, Marcotte TD, Patterson TL. The Impact of Cognitive Impairments on Healh-Related Quality of Life. In: Marcotte TD, Grant I. editors. Neuropsychology of Everyday Functioning. The Guilford Press; 2010. pp 225-247.
- 6 Wilson BA. Cognitive Rehabilitation: How it is and how it might be. J Int Neuropsychol Soc 1997; 3 (Suppl. 05) 487-496.
- 7 Lövdén M, Bäckman L, Lindenberger U, Schaefer S, Schmiedek F. A theoretical framework for the study of adult cognitive plasticity. Psychol Bull 2010; 136 (Suppl. 04) 659.
- 8 Pascual-Leone A, Amedi A, Fregni F, Merabet L. The plastic human brain cortex. Annu Rev Neurosci 2005; 28: 377-401.
- 9 Johansson BB. Current trends in stroke rehabilitation. A review with focus on brain plasticity. Acta Neurol Scand 2011; 123 (Suppl. 03) 147-159.
- 10 Kleim JA, Jones TA. Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. Journal of Speech, Language, and Hearing Research 2008; 51 (Suppl. 01) S225-S239.
- 11 Cicerone KD, Langenbahn DM, Braden C, Malec JF, Kalmar K, Fraas M. et al. Evidence-Based Cognitive Rehabilitation: Updated Review of the Literature from 2003 through 2008. Arch Phys Med Rehabil 2011; 92 (Suppl. 04) 519-530.
- 12 Rizzo AA, Schultheis M, Kerns KA, Mateer C. Analysis of assets for virtual reality applications in neuropsychology. Neuropsychological Rehabilitation 2004; 14 1–2 207-239.
- 13 Green CS, Bavelier D. Exercising Your Brain: A Review of Human Brain Plasticity and Training-Induced Learning. Psychol Aging 2008; 23 (Suppl. 04) 692-701.
- 14 Wilson BA. Neuropsychological rehabilitation: State of the science. S Afr J Psychol 2013; 43 (Suppl. 03) 267-277.
- 15 Wilson BA, Herbert CM, Shiel A. Behavioural approaches in neuropsychological rehabilitation: Optimising rehabilitation procedures. Psychology Press; 2003
- 16 Solana Sanchez J, Caceres C, García-Molina A, Opisso E, Roig T, Tormos J. et al. Improving brain injury cognitive rehabilitation by personalized tele-rehabilitation services: Guttmann Neuro Personal Trainer system. 2014
- 17 Marcano-Cedeño A, Chausa P, García A, Cáceres C, Tormos JM, Gómez EJ. Artificial metaplasticity prediction model for cognitive rehabilitation outcome in acquired brain injury patients. Artif Intell Med 2013; 58 (Suppl. 02) 91-99.
- 18 Marcano-Cedeño A, Chausa P, García A, Cáceres C, Tormos JM, Gómez EJ. Data mining applied to the cognitive rehabilitation of patients with acquired brain injury. Expert Syst Appl 2013; 40 (Suppl. 04) 1054-1060.
- 19 Aghajan ZM, Acharya L, Moore JJ, Cushman JD, Vuong C, Mehta MR. Impaired spatial selectivity and intact phase precession in two-dimensional virtual reality. Nature Neuroscience 2015; 18: 121-128.
- 20 Katz N, Ring H, Naveh Y, Kizony R, Feintuch U, Weiss PL. Interactive virtual environment training for safe street crossing of right hemisphere stroke patients with Unilateral Spatial Neglect. Disabil Rehabil 2005; 27 (Suppl. 20) 1235-1243.
- 21 Edmans J, Gladman J, Walker M, Sunderland A, Porter A, Fraser DS. Mixed reality environments in stroke rehabilitation: Development as rehabilitation tools. International Journal on Disability and Human Development 2004; 6 (Suppl. 01) 39-45.
- 22 Sorita E, N’Kaoua B, Larrue F, Criquillon J, Simion A, Sauzéon H. et al. Do patients with traumatic brain injury learn a route in the same way in real and virtual environments?. Disabil Rehabil 2013; 35 (Suppl. 16) 1371-1379.
- 23 Rizzo AA, Bowerly T, Buckwalter JG, Klimchuk D, Mitura R, Parsons TD. A virtual reality scenario for all seasons: The virtual classroom. Cns Spectrums 2006; 11 (Suppl. 01) 35-44.
- 24 Renison B, Ponsford J, Testa R, Richardson B, Brownfield K. The Ecological and Construct Validity of a Newly Developed Measure of Executive Function: The Virtual Library Task. J Int Neuropsychol Soc 2012; 18 (Suppl. 03) 440-450.
- 25 Tarnanas I, Tsolakis A, Tsolaki M. Assessing Virtual Reality Environments as Cognitive Stimulation Method for Patients with MCI. Technologies of Inclusive Well-Being. Springer; 2014. pp 39-74.
- 26 Fidopiastis CM, Stapleton CB, Whiteside JD, Hughes CE, Fiore SM, Martin GA. et al. Human experience modeler: Context-driven cognitive retraining to facilitate transfer of learning. Cyber-Psychology & Behavior 2006; 9 (Suppl. 02) 183-187.
- 27 Klinger E, Cao X, Douguet A, Fuchs P. Designing an Ecological and Adaptable Virtual Task in the Context of Executive Functions. Cyberpsychology & Behavior 2009; 12 (Suppl. 05) 626-627.
- 28 Gamito P, Oliveira J, Caires C, Morais D, Brito R, Lopes P. et al. Virtual Kitchen Test Assessing Frontal Lobe Functions in Patients with Alcohol Dependence Syndrome. Methods Inf Med 2015; 54 (Suppl. 02) 122-126.
- 29 da Costa R, de Carvalho L, de Aragon D. Virtual city for cognitive rehabilitation. Proceedings of the 3rd International Conference on Disability Virtual Reality and Associated Technologies. Alghero, Sardinia: 2000
- 30 Dores A, Miranda M, Carvalho I, Mendes L, Barbosa F, Coelho A, de Sousa L, Caldas A. Virtual City: Neurocognitive rehabilitation of Acquired Brain Injury. Information Systems and Technologies (CISTI), 2012 7th Iberian Conference on IEEE; 2012
- 31 Klinger E, Kadri A, Sorita E, Le Guiet J, Coignard P, Fuchs P. et al. AGATHE: A tool for personalized rehabilitation of cognitive functions based on simulated activities of daily living. IRBM 2013; 34 (Suppl. 02) 113-118.
- 32 Grewe P, Kohsik A, Flentge D, Dyck E, Botsch M, Winter Y. et al. Learning real-life cognitive abilities in a novel 360 degrees-virtual reality supermarket: a neuropsychological study of healthy participants and patients with epilepsy. J NeuroEng Rehabil 2013; 10: 42.
- 33 Lee JH, Ku J, Cho W, Hahn WY, Kim IY, Lee S. et al. A virtual reality system for the assessment and rehabilitation of the activities of daily living. CyberPsychology & Behavior 2003; 6 (Suppl. 04) 383-388.
- 34 Werner P, Rabinowitz S, Klinger E, Korczyn AD, Josman N. Use of the virtual action planning supermarket for the diagnosis of mild cognitive impairment: a preliminary study. Dement Geriatr Cogn Disord 2009; 27 (Suppl. 04) 301-309.
- 35 Rand D, Weiss PL, Katz N. Training Multitasking in a Virtual Supermarket: A Novel Intervention After Stroke. Am J Occup Ther 2009; 63 (Suppl. 05) 535-542.
- 36 Pietrzak E, Pullman S, McGuire A. Using Virtual Reality and Videogames for Traumatic Brain Injury Rehabilitation: A Structured Literature Review. GAMES FOR HEALTH: Research, Development, and Clinical Applications 2014; 3 (Suppl. 04) 202-214.
- 37 Riva G, Gaggioli A, Grassi A, Raspelli S, Cipresso P, Pallavicini F. et al. NeuroVR 2 – a free virtual reality platform for the assessment and treatment in behavioral health care. Stud Health Technol Inform 2011; 163: 493-495.
- 38 Lange B, Koenig S, Chang C, McConnell E, Suma E, Bolas M. et al. Designing informed game-based rehabilitation tasks leveraging advances in virtual reality. Disabil Rehabil 2012; 34 (Suppl. 22) 1863-1870.
- 39 Whyte J, Hart T. It’s more than a black box; It’s a Russian doll – Defining rehabilitation treatments. Am J Phys Med Rehabil 2003; 82 (Suppl. 08) 639-652.
- 40 Whyte J, Dijkers MP, Hart T, Zanca JM, Packel A, Ferraro M. et al. Development of a theory-driven rehabilitation treatment taxonomy: conceptual issues. Arch Phys Med Rehabil 2014; 95 (Suppl. 01) S24-S32. e2.
- 41 Dijkers MP, Hart T, Tsaousides T, Whyte J, Zanca JM. Treatment Taxonomy for Rehabilitation: Past, Present, and Prospects. Arch Phys Med Rehabil 2014; 95 (Suppl. 01) S6-S16.
- 42 Grove MJ. Development of an Ontology for Rehabilitation: Traumatic Brain Injury. University of Minnesota; 2013
- 43 Giustini A, Varela E, Franceschini M, Votava J, Zampolini M, Berteanu M. et al. UEMS--Position Paper. New technologies designed to improve functioning: the role of the physical and rehabilitation medicine physician. European journal of physical and rehabilitation medicine 2014; 50 (Suppl. 05) 579-583.
- 44 Baum CM, Katz N. Occupational Therapy Approach to Assessing the Relationship between Cognition and Function. In: Marcotte TD, Grant I. editors. Neuropsychology of Everyday Functioning. The Guilford Press; 2010. pp 62-90.
- 45 Stanford University.. Protégé. 2014
- 46 W3C OWL Working Group.. OWL 2 Web Ontology Language Document Overview (Second Edition). 2012 Available at: http://www.w3.org/TR/owl2-overview/. Accessed September 2014
- 47 McGuinness D, Van Harmelen F. OWL Web Ontology Language Overview. 2004 Available at: http://www.w3.org/standards/techs/owl#w3c_all. Accessed September 2014
- 48 Martínez-Moreno JM, Sánchez-González P, García A, González S, Cáceres C, Sánchez-Carrión R, Roig T, Tormos JM, Gómez EJ. A Graphical Tool for Designing Interactive Video Cognitive Rehabilitation Therapies. XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013. Springer; 2014
- 49 Martinez-Moreno JM, Solana J, Sanchez R, Gonzalez S, Sanchez-Gonzalez P, Gomez C. et al. Cognitive Neurorehabilitation based on Interactive Video Technology. Informatics, Management and Technology in Healthcare 2013; 190: 27-29.