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The authors who contributed equally to this work are Alfonso Monaco and Gianluca Sforza, both first names of the paper.
The cognitive and computational neurosciences have developed neurorehabilitative tools able to treat suffering subjects from early symptoms, in order to give priority to a home environment. In this way, the curative treatment would not burden the hospital with excessive costs and the patient with psychological disorientation. Recent studies have shown the efficacy of video games on improving cognitive processes impaired by ageing’s physiological effect, neurodegenerative or other diseases, with potential beneficial effects. The PERvasive game for perSOnalized treatment of cognitive and functional deficits associated with chronic and Neurodegenerative diseases (PERSON) project proposed new tools for cognitive rehabilitation, aiming to improve the quality of life for patients with cognitive impairments, especially at early stages, by the use of sophisticated, non-invasive technology. This article is an overview of game solutions for training cognitive abilities and it presents the tools developed within the PERSON project. These tools are serious games based on virtual reality, connected to a brain-computer interface based on electroencephalography (EEG) and to haptic devices. The project was born thanks to a strategic synergy between research and public health, to implement a technology for personalized medicine that relies on the cloud infrastructure of the REte di CAlcolo per SuperB ed altre applicazioni (ReCaS)-Bari data centre. PERSON developed a completely open source and innovative framework to interface the game device with the computational resources in the cloud. We exploited the container technology and the Software as a Service (SaaS) paradigm to implement a genetic algorithm that analyses the neural responses in EEG recordings. The paper focuses on technical aspects of the designed tools. A test was conducted on a few volunteers for the purpose of tuning the overall system. The paper does not contain results of a clinical trial as this is planned in a second testing phase, when the user’s perception of the system will also be tested.
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Rose FD, Brooks BM, Rizzo AA. Virtual reality in brain damage rehabilitation: review. CyberPsychology & Behavior 2005;8(3):241. CrossRef
Brettschneider J, Tredici KD, Lee VM, Trojanowski JQ. Spreading of pathology in neurodegenerative diseases: a focus on human studies. Nat Rev Neurol 2015;16(2):109. CrossRef
Prince M, Comas-Herrera A, Knapp M, Guerchet M, Karagiannidou M. 2016. World Alzheimer report 2016: improving healthcare for people living with dementia: coverage quality and costs now and in the future (Alzheimer’s Disease International).
Amoroso N, Errico R, Bruno S, Chincarini A, Garuccio E, Sensi F, Tangaro S, Tateo A, Bellotti R. For the Alzheimer’s disease neuroimaging initiative. Phys Med Biol 2015;60(22):8851. CrossRef
Amoroso N, Diacono D, Fanizzi A, La Rocca M, Monaco A, Lombardi A, Guaragnella C, Bellotti R, Tangaro S. 2018. Deep learning reveals Alzheimer’s disease onset in MCI subjects: Results from an international challenge. J Neurosci Methods. 302:3–9 https://doi.org/10.1016/.jneumeth.2017.12.011.
Serino S, Pedroli E. Technology and cognitive empowerment for healthy elderly: the link between cognitive skills acquisition and well-being. Integrating technology in positive psychology practice (IGI Global); 2016. p. 193–213.
Wattanasoontorn V, Hernández RJG, Sbert M. Serious games for e-health care. Simulations serious games and their applications. Berlin: Springer; 2014. p. 127–146.
McCallum S. Gamification and serious games for personalized health. Proceedings of the international conference on wearable micro and nano technologies for personalized health; 2012. p. 85–96.
Bowes J, Brown A, Hamon J, Jarolimek W, Sridhar A, Waldron G, Whitebread S. Reducing safety-related drug attrition: the use of in vitro pharmacological profiling. Nat Rev Drug Discov 2012;11(12): 909. CrossRef
Luck SJ. An Introduction to the Event-Related Potential Technique. Cambridge: MIT Press; 2005.
Polich J, Margala C. P300 and probability: comparison of oddball and single-stimulus paradigms. Int J Psychophysiol 1997;25(2):169. CrossRef
Howard MC. A meta-analysis and systematic literature review of virtual reality rehabilitation programs. Comput Hum Behav 2017;70:317. CrossRef
Burdea G. Virtual rehabilitation-benefits and challenges. Methods Inf Med 2003;42(5):519. CrossRef
Romero LE, Chatterjee P, Armentano RL. An IoT approach for integration of computational intelligence and wearable sensors for Parkinson’s disease diagnosis and monitoring. Heal Technol 2016;6(3):167. CrossRef
Lavalle SM. Virtual reality. Cambridge: Cambridge University Press; 2017.
Lee TS, Goh SJA, Quek SY, Phillips R, Guan C, Cheung YB, Feng L, Teng SSW, Wang CC, Chin ZY, Zhang H, Ng TP, Lee J, Keefe R, Krishnan KRR. A brain-computer interface based cognitive training system for healthy elderly: a randomized control pilot study for usability and preliminary efficacy. PLoS One 2013;8:1.
Guy V, Soriani MH, Bruno M, Papadopoulo T, Desnuelle C, Clerc M. Brain computer interface with the P300 speller: usability for disabled people with amyotrophic lateral sclerosis. Ann Phys Rehabil Med 2018; 61(1):5. CrossRef
Garcia-Betances RI, Jimenez-Mixco V, Arredondo MT, Cabrera-Umpierrez MF. Using virtual reality for cognitive training of the elderly. Am J Alzheimers Dis Other Demen 2015;30 (1):49. CrossRef
Lin CX, Lee C, Lally D, Coughlin JF. Impact of virtual reality (VR) experience on older adults’ well-being. Proceedings of the international conference on human aspects of IT for the aged population; 2018. p. 89–100.
Yoon HU, Anil Kumar N, Hur P. Synergistic effects on the elderly people’s motor control by wearable skin-stretch device combined with haptic joystick. Frontiers in Neurorobotics 2017;11:31. CrossRef
Che Me R, Biamonti A, Mohd Saad MR. Conceptual design of haptic-feedback navigation device for individuals with Alzheimer’s disease. Proceedings of the European Conference on the Advancement of Assistive Technology; 2015. p. 195–203.
Pfurtscheller G, Müller-Putz GR, Scherer R, Neuper C. Rehabilitation with braincomputer interface systems. Computer 2008;41(10):58. CrossRef
Lotte F, Larrue F, Mühl C. Flaws in current human training protocols for spontaneous brain-computer interfaces: lessons learned from instructional design. Front Hum Neurosci 2013;7:568. CrossRef
Lécuyer A., Lotte F, Reilly RB, Leeb R, Hirose M, Slater M. Brain-computer interfaces, virtual reality, and videogames. Computer 2008;41(10):66. CrossRef
Burdea G, Polistico K, Krishnamoorthy A, House G, Rethage D, Hundal J, Damiani F, Pollack S. Feasibility study of the BrightBrainer integrative cognitive rehabilitation system for elderly with dementia. Disabil Rehabil Assist Technol 2015;10(5):421. CrossRef
Zyda M. From visual simulation to virtual reality to games. Computer 2005;38(9):25. CrossRef
Burdea GC, Polistico K. A review of integrative virtual reality games for rehabilitation. Proceedings of the E-Health and Bioengineering Conference; 2017. p. 733–736.
Burdea GC, Polistico K, House GP, Liu RR, Muniz R, Macaro NA, Slater LM. Novel integrative virtual rehabilitation reduces symptomatology of primary progressive aphasia - a case report. Int J Neurosci 2015;125(12):949. CrossRef
Sánchez J, Lumbreras M. Usability and cognitive impact of the interaction with 3D virtual interactive acoustic environments by blind children. Proceedings of the international conference on disability, virtual reality and associated technologies; 2000. p. 67–73.
Jiang L, Guan C, Zhang H, Wang C, Jiang B. Brain computer interface based 3D game for attention training and rehabilitation. Proceedings of the IEEE conference on industrial electronics and applications; 2011. p. 124–127.
Strauss E, Sherman EM, Spreen O. 2006. A compendium of neuropsychological tests: administration, norms and commentary (American Chemical Society).
Unsworth N, Heitz RP, Schrock JC, Engle RW. An automated version of the operation span task. Behav Res Methods 2005;37(3):498. CrossRef
Robert P, Konig A, Amieva H, Andrieu S, Bremond F, Bullock R, Ceccaldi M, Dubois B, Gauthier S, Kenigsberg PA, Nave S, Orgogozo JM, Piano J, Benoit M, Touchon J, Vellas B, Yesavage J, Manera V. Recommendations for the use of serious games in people with Alzheimer’s disease, related disorders and frailty. Front Aging Neurosci 2014;6:54. CrossRef
Ouellet E, Boller B, Corriveau-Lecavalier N, Cloutier S, Belleville S. The virtual shop: a new immersive virtual reality environment and scenario for the assessment of everyday memory. J Neurosci Methods 2018; 303:126. CrossRef
Invitto S, Faggiano C, Sammarco S, De Luca V, De Paolis LT. Haptic, virtual interaction and motor imagery: entertainment tools and psychophysiological testing. Sensors 2016;16(3):394. CrossRef
Ortner R, Allison BZ, Korisek G, Gaggl H, Pfurtscheller G. An SSVEP BCI to control a hand orthosis for persons with tetraplegia. IEEE Trans Neural Syst Rehabil Eng 2011;19(1):1. CrossRef
Wang Z, Ji Q, Miller K, Schalk G. Prior knowledge improves decoding of finger flexion from electrocorticographic signals. Front Neurosci 2011;5:127. CrossRef
Jones HE. Augmenting mental chronometry: the P300 as a measure of stimulus evaluation time. Am J Psychol 1935;47(2):241. CrossRef
Kutas M, McCarthy G, Donchin E. Augmenting mental chronometry: the P300 as a measure of stimulus evaluation time. Science 1977;197(4305):792. CrossRef
Da Pelo P, De Tommaso M, Monaco A, Stramaglia S, Bellotti R, Tangaro S. Trial latencies estimation of event-related potentials in EEG by means of genetic algorithms. J Neural Eng 2018;15:026016. 2. CrossRef
Beasley D, Bull DR, Martin RR. An overview of genetic algorithms: Part 2, research topics. University computing 1993;15(4):170.
De Venuto D, Annese VF, Ruta M, Di Sciascio E. A. Sangiovanni Vincentelli. IEEE Design & Test 2015;33(3):66. CrossRef
De Venuto D, Annese VF, Mezzina G, Ruta M, Di Sciascio E. Brain-computer interface using p300: a gaming approach for neurocognitive impairment diagnosis. Proceedings of the IEEE international high level design validation and test workshop; 2016. p. 93–99.
Buyya R, Broberg J, Goscinski AM. Cloud computing: principles and paradigms. New York: Wiley; 2010.
Salomoni D, Campos Plasencia I, Gaido L, Donvito G, Antonacci M, Fuhrmann P, Marco J, Lopez-Garcia A, Orviz Fernandez P, Blanquer I, Caballer M, Molto G, Plociennik M, Owsiak M, Urbaniak M, Hardt M, Ceccanti A, Wegh B, Gomes J, Rocha R. 2016. INDIGO-Datacloud: foundations and architectural description of a Platform as a Service oriented to scientific computing, arXiv: 1603.09536.
- The PERSON project: a serious brain-computer interface game for treatment in cognitive impairment
Marina de Tommaso
Pierpaolo Di Bitonto
Eugenio Di Sciascio
- Springer Berlin Heidelberg
- Health and Technology
Print ISSN: 2190-7188
Elektronische ISSN: 2190-7196
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