Abstract
Preventing and reducing physical and cognitive decay in older adults is among the challenges of Healthcare 5.0. The research project ActivE3 aims at promoting older adults’ health and social inclusion through regular physical activity, leveraging an ICT-enabled network composed of elderlies, young people, and clinical personnel. Using a virtual reality-based application (SocialBike), older adults can adopt a healthier lifestyle while socializing with youngers through collaborative exercise. The exercise involves both physical and cognitive training, as users must cycle on a stationary bike while recognizing target animals or objects appearing along the way. Using wearable sensors and relying on clinical expertise, ActivE3 exploits semantic reasoning capabilities to tailor exercise’s workload and goals according to the specific users’ health conditions and abilities. The system stores the results from each exercise session and dispatches them to clinical personnel, to support the non-invasive monitoring of frail older adults’ health conditions.
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References
Mohanta, B., Das, P., Patnaik, S.: Healthcare 5.0: a paradigm shift in digital healthcare system using artificial intelligence, IOT and 5G communication. In: Proceedings - 2019 International Conference on Applied Machine Learning, ICAML 2019 (2019). https://doi.org/10.1109/ICAML48257.2019.00044
Powell, J.L., Leedham, C.: Post-industrial society and aging in a global world: the demographic context of social welfare. In: The Welfare State in Post-Industrial Society: A Global Perspective (2009). https://doi.org/10.1007/978-1-4419-0066-1_8
Spoladore, D., Arlati, S., Colombo, V., Modoni, G., Sacco, M.: A semantic-enabled smart home for AAL and continuity of care. In: Studies in Computational Intelligence (2021). https://doi.org/10.1007/978-981-15-9897-5_17
Arlati, S., et al.: A virtual reality-based physical and cognitive training system aimed at preventing symptoms of dementia. In: Perego, P., Rahmani, A., TaheriNejad, N. (eds.) Wireless Mobile Communication and Healthcare. MobiHealth 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 247, pp. 117–125. Springer, Heidelberg (2018). https://doi.org/10.1007/978-3-319-98551-0_14
Colombo, V., Mondellini, M., Gandolfo, A., Fumagalli, A., Sacco, M.: Usability and acceptability of a virtual reality-based system for endurance training in elderly with chronic respiratory diseases. In: Bourdot, P., Interrante, V., Nedel, L., Magnenat-Thalmann, N., Zachmann, G. (eds.) Virtual Reality and Augmented Reality. EuroVR 2019. Lecture Notes in Computer Science, vol. 11883, pp. 87–96. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-31908-3_6
Spoladore, D., Stella, F., Tosi, M., Lorenzini, E.C.: Towards a knowledge-based Decision Support System for the management of Type 2 diabetic patients (2023, in press)
Popovic, S., Masanovic, B.: Effects of physical and social activity on physical health and social inclusion of elderly people (2019). https://doi.org/10.18502/ijph.v48i10.3503
Buonsenso, A., et al.: Exploring the enjoyment of the intergenerational physical activity. J. Funct. Morphol. Kinesiol. 6 (2021). https://doi.org/10.3390/jfmk6020051
Murayama, Y., et al.: The effect of intergenerational programs on the mental health of elderly adults. Aging Ment. Health. 19 (2015). https://doi.org/10.1080/13607863.2014.933309
Santini, S., Tombolesi, V., Baschiera, B., Lamura, G.: Intergenerational programs involving adolescents, institutionalized elderly, and older volunteers: results from a pilot research-action in Italy. Biomed Res Int. 2018 (2018). https://doi.org/10.1155/2018/4360305
Femia, E.E., Zarit, S.H., Blair, C., Jarrott, S.E., Bruno, K.: Intergenerational preschool experiences and the young child: potential benefits to development. Early Child Res Q. 23 (2008). https://doi.org/10.1016/j.ecresq.2007.05.001
Golenko, X., Radford, K., Fitzgerald, J.A., Vecchio, N., Cartmel, J., Harris, N.: Uniting generations: a research protocol examining the impacts of an intergenerational learning program on participants and organisations. Australas. J. Ageing 39 (2020). https://doi.org/10.1111/ajag.12761
Arlati, S., et al.: A social virtual reality-based application for the physical and cognitive training of the elderly at home. Sensors (Switzerland) 19 (2019). https://doi.org/10.3390/s19020261
Garber, C.E., et al.: Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: Guidance for prescribing exercise. Med. Sci. Sports Exerc. 43 (2011). https://doi.org/10.1249/MSS.0b013e318213fefb
Nikitas, C., Kikidis, D., Bibas, A., Pavlou, M., Zachou, Z., Bamiou, D.-E.: Recommendations for physical activity in the elderly population: a scoping review of guidelines. J. Frailty Sarcopenia Falls 07 (2022). https://doi.org/10.22540/jfsf-07-018
Spoladore, D., Pessot, E., Trombetta, A.: A novel agile ontology engineering methodology for supporting organizations in collaborative ontology development. Comput Ind. 151, 103979 (2023). https://doi.org/10.1016/j.compind.2023.103979
Pan, J.Z.: Resource description framework. In: Handbook on Ontologies (2009). https://doi.org/10.1007/978-3-540-92673-3_3
Antoniou, G., Harmelen, F. van: Web Ontology Language: OWL. In: Handbook on Ontologies (2009). https://doi.org/10.1007/978-3-540-92673-3_4
Graves, M., Constabaris, A., Brickley, D.: FOAF: connecting people on the semantic web. Cat Classif. Q. 43 (2007). https://doi.org/10.1300/J104v43n03_10
Spoladore, D., Mahroo, A., Trombetta, A., Sacco, M.: DOMUS: a domestic ontology managed ubiquitous system. J. Amb. Intell. Humaniz. Comput.. 13 (2022). https://doi.org/10.1007/s12652-021-03138-4
Üstün, T.B., Chatterji, S., Bickenbach, J., Kostanjsek, N., Schneider, M.: The international classification of functioning, disability and health: a new tool for understanding disability and health. Disabil. Rehabil. 25 (2003). https://doi.org/10.1080/0963828031000137063
Spoladore, D., Sacco, M., Trombetta, A.: A review of domain ontologies for disability representation. Expert Syst. Appl. 228, 120467 (2023). https://doi.org/10.1016/j.eswa.2023.120467
Tanaka, H., Monahan, K.D., Seals, D.R.: Age-predicted maximal heart rate revisited. J. Am. Coll. Cardiol. 37 (2001). https://doi.org/10.1016/S0735-1097(00)01054-8
Horrocks, I., et al.: SWRL: a semantic web rule language combining OWL and RuleML. W3C Memb. Submiss. 21, 1–31 (2004)
Spoladore, D., Mondellini, M., Sacco, M., Spoladore, D., Trombetta, A.: An ontology-based framework for a Less Invasive Domestic Management System (LIDoMS). In: Proceedings of the 2020 16th International Conference on Intelligent Environments, IE 2020 (2020). https://doi.org/10.1109/IE49459.2020.9155023
Cruz, J., Brooks, D., Marques, A.: Home telemonitoring in COPD: a systematic review of methodologies and patients’ adherence (2014). https://doi.org/10.1016/j.ijmedinf.2014.01.008
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Spoladore, D., Mahroo, A., Colombo, V., Sacco, M. (2023). ActivE3: Fostering Social Inclusion Through Collaborative Physical and Cognitive Exercise. In: Camarinha-Matos, L.M., Boucher, X., Ortiz, A. (eds) Collaborative Networks in Digitalization and Society 5.0. PRO-VE 2023. IFIP Advances in Information and Communication Technology, vol 688. Springer, Cham. https://doi.org/10.1007/978-3-031-42622-3_36
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