Personalized 3D exergames for in-home rehabilitation after stroke: a pilot study

References

• Center for Disease Control and Prevention: Stroke Facts; [cited 2020 Jan 31]. Available: https://www.cdc.gov/stroke/facts.htm.
   Google Scholar
• Ovbiagele B, Goldstein LB, Higashida RT, et al. Forecasting the future of stroke in the United States: a policy statement from the American Heart Association and American Stroke Association. Stroke. 2013;44(8):2361–2375.
   PubMed Web of Science ®Google Scholar
• Buntin MB, Colla CH, Deb P, et al. Medicare spending and outcomes after postacute care for stroke and hip fracture. Med Care. 2010;48(9):776–784.
   PubMed Web of Science ®Google Scholar
• Winstein CJ, Stein J, Arena R, et al. Guidelines for adult stroke rehabilitation and recovery: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2016;47(6):e98–e169.
   PubMed Web of Science ®Google Scholar
• Broeks JG, Lankhorst G, Rumping JK, Prevo AH. The long-term outcome of arm function after stroke: results of a follow-up study. Disabil Rehabil. 1999;21(8):357–364.
   PubMed Web of Science ®Google Scholar
• Gelaw AY, Janakiraman B, Gebremeskel BF, et al. Effectiveness of home-based rehabilitation in improving physical function of persons with Stroke and other physical disability: a systematic review of randomized controlled trials. J Stroke Cerebrovasc Dis. 2020;29(6):104800.
   PubMed Web of Science ®Google Scholar
• Miller KK, Porter RE, DeBaun-Sprague E, et al. Exercise after stroke: patient adherence and beliefs after discharge from rehabilitation. Top Stroke Rehabil. 2017;24(2):142–148.
   PubMed Web of Science ®Google Scholar
• Saposnik G, Levin M, Stroke Outcome Research Canada (SORCan) Working Group. Virtual reality in stroke rehabilitation a meta-analysis and implications for clinicians. Stroke. 2011;42(5):1380–1386.
   PubMed Web of Science ®Google Scholar
• Sucar LE, Luis R, Leder R, et al. Gesture therapy: a vision-based system for upper extremity stroke rehabilitation. in Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE, 2010.
   Google Scholar
• Vieira J, Sousa M, Arsenio A, et al. Augmented reality for rehabilitation using multimodal feedback. in Proceedings of the 3rd 2015 Workshop on ICTs for improving Patients Rehabilitation Research Techniques, 2015.
   Google Scholar
• Kizony R, Weiss PLT, Shahar M, et al. TheraGame: a home based virtual reality rehabilitation system. Int J Disabil Hum Dev. 2006;5(3):265–270.
   Google Scholar
• Borrego A, Latorre J, Alcaniz M, et al. Comparison of Oculus Rift and HTC Vive: feasibility for virtual reality-based exploration, navigation, exergaming, and rehabilitation. Games for Health. 2018;7(3):151–156.
   PubMed Web of Science ®Google Scholar
• Cruz L, Lucio D, Velho L. Kinect and RGBD images: challenges and applications. In: 25th SIBGRAPI Conference on Graphics, Patterns and Images Tutorials (SIBGRAPI-T), 2010.
   Google Scholar
• Tanaka K, Parker J, Baradoy G, et al. A comparison of exergaming interfaces for use in rehabilitation programs and research. Loading. 2012;6(9):69–81.
   Google Scholar
• Afyouni I, Einea A, Murad A. RehaBot: gamified virtual assistants towards adaptive TeleRehabilitation. In: Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization, 2019.
   Google Scholar
• Demers M, Nguyen A-V, Ong Y-LA, et al. Exergaming for stroke rehabilitation: lessons learned for future implementation strategies. In: 2019 International Conference on Virtual Rehabilitation (ICVR), 2019.
   Google Scholar
• Stamm O, Vorweg S, Muller-Werdan U. Exergames in augmented reality for older adults with hypertension: a qualitative study exploring user requirements. In: International Conference on Human-Computer Interaction, 2019.
   Google Scholar
• Agmon M, Perry CK, Phelan E, et al. A pilot study of Wii Fit exergames to improve balance in older adults. J Geriatr Phys Ther. 2011;34(4):161–167.
   PubMed Web of Science ®Google Scholar
• Oliver M, Molina JP, Fernandez-Caballero A, et al. Collaborative computer-assisted cognitive rehabilitation system. ADCAIJ. 2017;6(3):57–74.
   Google Scholar
• Bahirat K, Chung Y-Y, Annaswamy T, et al. Using Mr. MAPP for lower limb phantom pain management. In: Proceedings of the 27th ACM International Conference on Multimedia, 2019.
   Google Scholar
• Desai K, Bahirat K, Ramalingam S, et al. Augmented reality-based exergames for rehabilitation. In: Proceedings of the 7th International Conference on Multimedia Systems, Klagenfurt, Austria, 2016.
   Google Scholar
• Johnson-Glenberg MC, Savio-Ramos C, Henry H. Alien health: a nutrition instruction exergame using the Kinect sensor. Games Health. 2014;3(4):241–251.
   PubMed Web of Science ®Google Scholar
• Wüest S, Borghese NA, Pirovano M, et al. Usability and effects of an exergame-based balance training program. Games Health. 2014;3(2):106–114.
   PubMed Web of Science ®Google Scholar
• Borghese NA, Pirovano M, Lanzi PL, et al. Computational intelligence and game design for effective at-home stroke rehabilitation. Games for Health. 2013;2(2):81–88.
   PubMed Web of Science ®Google Scholar
• Johnson L, Bird M-L, Muthalib M, et al. An innovative stroke interactive virtual therapy (STRIVE) online platform for community-dwelling stroke survivors: a randomized controlled trial. Arch Phys Med Rehabil. 2020;101(7):1131–1137.
   PubMed Web of Science ®Google Scholar
• Szturm T, Imran Z, Pooyania S, et al. Evaluation of a game based tele rehabilitation platform for in-home therapy of hand-arm function post stroke: feasibility study. PM R. 2020;13(1):45–54.
   PubMedGoogle Scholar
• Bethoux F, Rogers HL, Nolan KJ, et al. Freed and others, the effects of peroneal nerve functional electrical stimulation versus ankle-foot orthosis in patients with chronic stroke: a randomized controlled trial. Neurorehabil Neural Repair. 2014;28(7):688–697.
   PubMed Web of Science ®Google Scholar
• Duncan PW, Wallace D, Lai SM, et al. The stroke impact scale version 2.0: evaluation of reliability, validity, and sensitivity to change. Stroke. 1999;30(10):2131–2140.
   PubMed Web of Science ®Google Scholar
• Herman T, Giladi N, Hausdorff JM. Properties of the ‘timed up and go’ test: more than meets the eye. Gerontology. 2011;57(3):203–210.
   PubMed Web of Science ®Google Scholar
• Zaza C, Stolee P, Prkachin K. The application of goal attainment scaling in chronic pain settings. J Pain Symptom Manage. 1999;17(1):55–64.
   PubMed Web of Science ®Google Scholar
• Liao Y, Vakanski A, Xian M, et al. A review of computational approaches for evaluation of rehabilitation exercises. Comput Biol Med. 2020;119:103687.
   PubMed Web of Science ®Google Scholar
• Ifejika NL, Bhadane M, Cai C, et al. Cluster enrollment: a screening tool for stroke risk factors in minority women caregivers. J Natl Med Assoc. 2019;111(3):281–284.
   PubMed Web of Science ®Google Scholar
• Ifejika NL, Noser EA, Grotta JC, et al. Swipe out stroke: feasibility and efficacy of using a smart-phone based mobile application to improve compliance with weight loss in obese minority stroke patients and their carers. Int J Stroke. 2016;11(5):593–603.
   PubMed Web of Science ®Google Scholar
• Ifejika NL, Bhadane M, Cai CC, et al. Use of a smartphone-based mobile app for weight management in obese minority stroke survivors: pilot randomized controlled trial with open blinded end point. JMIR Mhealth Uhealth. 2020;8(4):e17816.
   PubMed Web of Science ®Google Scholar