Updated research trend and clustering algorithm on virtual reality and pulmonary rehabilitation: Scopus-based bibliometric and visual analysis
Article Sidebar
Main Article Content
Abstract
Background: Virtual reality (VR) is a new innovative technology that can enhance intervention and should promote the effectiveness of rehabilitation, but there is a lack of scientific evidence on the clustering and topic research trend, especially on VR and pulmonary rehabilitation (PR). More evidence about network clusters and trends will encourage the research in the future.
Objective: This study aimed to explore, identify, cluster, and forecast analysis for the research trend of VR and PR from the research articles on the SCOPUS database.
Materials and methods: In this study, the search terms “virtual reality” AND “pulmonary rehabilitation” were extracted from specific English research articles published on the SCOPUS database between 2013-2023. RStudio software was used to perform bibliometric and visual analysis. During the analysis in the bibliometric tool, the normalization process with Salton’s Cosine and network clustering via trend topic with the Walktrap algorithm was analyzed before specific visualization with the network clustering mapping, Treemap, and trend topic line by KamadaKawai layout algorithm.
Results: From the 1,396 articles on “VR” published between 2010 and 2023, there were 13 research articles on “VR AND PR” published between 2013 and 2023. The bibliometric result from 13 articles showed total of 36 subdisciplines correlated networks among virtual reality (20, 7%), male (16, 6%), female (15, 5%), aged (12, 4%), chronic obstructive lung disease (12, 4%), exercise (11, 4%), human (10, 4%), humans (10, 4%), middle-aged (10, 4%), quality of life (10, 4%), article (9, 3%), pulmonary rehabilitation (9, 3%), controlled study (8, 3%), adult (6, 2%), chronic obstructive (6, 2%), clinical article (6, 2%), forced expiratory volume (6, 2%), pulmonary disease (6, 2%), randomized controlled trial (6, 2%), and forced vital capacity (5, 2%), etc., respectively. Three network clusters were reported after the normalization process and clustering evaluation by factorial analysis. The first cluster was composed of virtual reality, male, female, aged, chronic obstructive lung disease, exercise, human, humans, middle-aged, quality of life, article, pulmonary rehabilitation, controlled study, adult, chronic obstructive, clinical article, forced expiratory volume, randomized controlled trial, forced vital capacity, six-minute walk test, depression, technology, telerehabilitation, breathing exercise, Covid-19, dyspnea, functional status, hospital patient, and physical activity, respectively. The second cluster consisted of procedure and exercise therapy, and the last cluster consisted of exercise tolerance, lung, treatment outcome, health program, and convalescence. Finally, trend research topics were presented in virtual reality, male, female, aged, chronic obstructive lung disease, human, exercise, quality of life, and middle-aged, respectively, in 2023.
Conclusion: Therefore, the contribution from data analysis in this article can identify the clustering and trend topics of VR, chronic obstructive lung disease, aging participants, exercise, and quality of life in future research.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Personal views expressed by the contributors in their articles are not necessarily those of the Journal of Associated Medical Sciences, Faculty of Associated Medical Sciences, Chiang Mai University.
References
Dockx K, Bekkers EM, Van den Bergh V, Ginis P, Rochester L, Hausdorff JM, et al. Virtual reality for rehabilitation in Parkinson’s disease. Cochrane Database Syst Rev. 2016; 12(12): CD010760. doi: 10.1002/14651858. CD010760.pub2.
Weiss PL, Kizony R, Feintuch U, Katz N. Virtual reality in neurorehabilitation. In: Gage F, Cohen L, Selzer M, Duncan P, Clarke S, editors. Textbook of neural repair and rehabilitation: Volume 2: Medical Neurorehabilitation. 2nd Ed. Cambridge: Cambridge University Press; 2006: 182-97.
Keshner EA. Virtual reality and physical rehabilitation; a new toy or a new research and rehabilitation tool? J Neuroeng Rehabil. 2004: 1(1): 8. doi: 10.1186/1743-0003-1-8.
Lee LG, Krovi VN. Musculoskeletal simulation-based optimization of rehabilitation program. International Workshop on Virtual Rehabilitation, New York, NY, USA, 2006, pp. 36-41, doi: 10.1109/IWVR.2006.1707524.
Kizony R, Katz N, Weiss PL. Adapting an immersive virtual reality system for rehabilitation. Comput Animat Virtual Worlds. 2003; 14(5): 261-8. doi: 10.1002/vis.323.
Weiss PL, Rand D, Katz N, Kizony R. Video captures virtual reality as a flexible and effective rehabilitation tool. J Neuroeng Rehabil. 2004; 1(1): 12. doi: 10.1186/1743-0003-1-12.
Burdea GC. Virtual rehabilitation benefits and challenges. Methods Inf Med. 2003; 42: 519-23. doi: 10.1267/METH03050519.
Yang X. Virtual reality in rehabilitation. Rehabilitation Engineering. [Internet]. Tan Yen Kheng (Ed), ISBN: 978- 953-307-023-0, InTech, Available from: http://www.intechopen.com/books/rehabilitation-engineering/virtual-reality-in-rehabilitation.
Schäfer AGM, Zalpour C, von Piekartz H, Hall TM, Paelke V. The efficacy of electronic health supported home exercise interventions for patients with osteoarthritis of the knee: systematic review. J Med Internet Res. 2018; 20(4): e152. doi: 10.2196/jmir.9465.
Trost Z, Anam M, Seward J, Shum C, Rumble D, Sturgeon J, et al. Immersive interactive virtual walking reduces neuropathic pain in spinal cord injury: findings from a preliminary investigation of feasibility and clinical efficacy. Pain. 2022; 163(2): 350-61. doi: 10.1097/j.pain.0000000000002348.
Powell V, Powell W. Therapy-led design of homebased virtual rehabilitation. 2015 IEEE 1st Workshop on Everyday Virtual Reality (WEVR), Arles, France; 2015: 11-4. doi: 10.1109/WEVR.2015.7151688.
Roy AK, Soni Y, Dubey S. Enhancing the effectiveness of motor rehabilitation using Kinect motion sensing technology. 2013 IEEE Global Humanitarian Technology Conference: South Asia Satellite (GHTC-SAS), Trivandrum, India; 2013: 298-304. doi: 10.1109/GHTC-SAS.2013.6629934.
Su WC, Yeh SC, Lee SH, Huang HC. A virtual reality lower-back pain rehabilitation approach: System design and user acceptance analysis. In Stephanidis C, Antona M, Stephanidis C, editors, Universal Access in Human-Computer Interaction: Access to Learning, Health and Well-Being. Proceedings of the 9th International Conference, UAHCI 2015 Held as Part of HCI International 2015. Springer Verlag; 2015: 374-82. doi: 10.1007/978-3-319-20684-4_37.
Kim J, Son J, Ko N, Yoon B. Unsupervised virtual reality-based exercise program improves hip muscle strength and balance control in older adults: a pilot study. Arch Phys Med Rehabil. 2013; 94(5): 937-43. doi: 10.1016/j.apmr.2012.12.010. Epub 2012 Dec 21.
Bryanton C, Bosse J, Brien M, Mclean J, McCormick A, Sveistrup H. Feasibility, motivation, and selective motor control: virtual reality compared to conventional home exercise in children with cerebral palsy. Cyberpsychol Behav. 2006; 9(2): 123-8. doi: 10.1089/cpb.2006.9.123.
Casuso-Holgado MJ, Martín-Valero R, Carazo AF, Medrano-Sanchez EM, Cortes Vega M.D, MonteroBancalero FJ. Effectiveness of virtual reality on training for balance and gait rehabilitation in people with multiple sclerosis: a systematic review and meta-analysis. Clin Rehabil. 2018; 32: 1220-34. doi: 10.1177/0269215518768084. Epub 2018 Apr 13.
Iruthayarajah J, McIntyre A, Cotoi A, Macaluso S, Teasell R. The use of virtual reality for balance among individuals with chronic stroke: a systematic review and meta-analysis. Top Stroke Rehabil. 2017; 24(1): 68-79. doi: 10.1080/10749357.2016.1192361. Epub 2016 Jun 16.
Porras DC, Siemonsma P, Inzellberg R, Zeilig G, Plotnik M. Advantages of virtual reality in the rehabilitation of balance and gait: Systematic review. Neurology. 2018; 90(22): 1017-25. doi: 10.1212/WNL.0000000000005603. Epub 2018 May 2.
Lopes JBP, de Almeida-Carvalho Duarte N, Lazzari RD, Oliveira CS. Virtual reality in the rehabilitation process for individuals with cerebral palsy and Down syndrome: A systematic review. J Bodyw Mov Ther. 2018; 24(4): 479-83. doi: 10.1016/j. jbmt.2018.06.006. Epub 2018 Jun 28.
Howard MC. A meta-analysis and systematic literature review of virtual reality rehabilitation programs. Comput Human Behav Rep. 2017; 70: 317-27. doi: 10.1016/j.chb.2017.01.013.
Peek K, Sanson-Fisher R, Mackenzie L, Carey M. Interventions to aid patient adherence to physiotherapist prescribed self-management strategies: a systematic review. Physiotherapy. 2016; 102(2): 127-35. doi: 10.1016/j.physio.2015.10.003. Epub 2015 Oct 22.
Mujber TS, Szecsi T, Hashmi MSJ. Virtual reality applications in manufacturing process simulation. J Mater Process Technol. 2004; 156: 1834-8. doi: 10.1016/j.jmatprotec.2004.04.401.
Zhang G, Qin Y, Liu S, Chen X, Zhang W. Bibliometric analysis of research trends and topic area in traditional Chinese medicine therapy for lymphoma. Pharm Biol. 2024; 62(1): 13-21. doi: 10.1080/13880209.2023.
Epub 2023 Dec 13.
Garrido-Cardenas JA, de Lamo-Sevilla C, CabezasFernandez MT, Manzano-Agugliaro F, MartinerxLirola M. Global tuberculosis research and its future prospects. Tuberculosis. 2020; 121: 101917. doi: 10.1016/j.tube.2020.101917. Epub 2020 Feb 23.
Dinic BM, Jevremov, T. Trends in research related to the dark triad: A bibliometric analysis. Curr Psychol. 2021; 40(7): 3206-15. doi: 10.1007/s12144-019-00250-9.
Mongeon, P, Paul-Hus, A. The Journal coverage of web of science and Scopus: A comparative analysis. Scientometrics. 2016: 106(1): 213-28. doi: 10.1007/s11192-021-03948-5.
Cobo MJ, Lopez-Herrera AG, Herrera-Viedma E, Herrera F. Science mapping software tools; review, analysis, and cooperative study among tools, J Amer Soc Inform Sci Technol. 2011; 62(7): 1382-402. doi: 10.1002/asi.21525.
Wichaisri S, Sapadan, A. Trends and future future directions in sustainable development. Sustain Develop. 2018; 26(1): 1-17. doi: 10.1002/sd.1687.
Aria M, Cuccurullo C. Bibliometrix: An R-tool for comprehensive science mapping analysis. J Inform. 2017; 11(4): 959-75. doi: 10.1016/j.joi.2017.08.007.
Salton G, McHill MJ. Introduction to Modern Information Retrieval, McGraw-Hill, Auckland. 1983.
Cons P, Latapy M. Computing communities in large networks using random walks. J Graph Algorithms Appl. 2006; 10(2): 191-218. doi: 10.7155/jgaa.00124.
Kamada T, Kawai S. An algorithm for drawing general undirected graphs. Inform Process Letters. 1989; 49 (1112): 7-15. doi: 10.1016/0020-0190(89)90102-6.
Leydesdorff L. On the normalization and visualization of author co-citation data: Salton’s Cosine versus the Jaccard Index. J Amer Inform Sci Technol. 2008; 59(1): 77-85. doi: 10.1002/asi.20732.
Pons P, Latapy M. Computing communities in large networks using random walks. In: Yolum P, Güngör T, Gürgen F, Özturan C. (eds) Computer and Information Sciences - ISCIS 2005. Springer, Berlin, Heidelberg. 2005; 284-93. doi: 10.1007/11569596_31.
Kang GJ, Ewing-Nelson SR, Mackey L, Schlitt JT, Marathe A, Abbas KM, et al. Semantic network analysis of vaccine sentiment in online social media. Vaccine. 2017; 35(29): 3621-38. doi: 10.1016/j.vaccine.2017.05.052.
Lee Y, Lee Y, Seong J, Stanescu A, Hwang CS. A comparison of network clustering algorithms in keyword network analysis: a case study with geography conference presentations. Int J Geospat Environ Res. 2020; 7(3): 1-14. https://dc.uwm.edu/ijger/vol7/iss3/1.
Li Y, Jiang H, Lyu X. Virtual reality as an adjunct to pulmonary rehabilitation of patients with chronic obstructive pulmonary disease: a protocol for systematic review and meta-analysis. BMJ Open. 2023; 13(12): e074688. doi: 10.1136/bmjopen-2023-074688.
Rutkowski S, Bogacz K, Rutkowska A, Szczegielniak J, Casaburi R. Inpatient post-COVID-19 rehabilitation program featuring virtual reality-Preliminary results of randomized controlled trial. Front Public Health. 2023; 11: 1121554. doi: 10.3389/fpubh.2023.1121554. eCollection 2023.
Rutkowski S, Bogacz K, Czech O, Rutkowsha A, Szczegielniak J. Effectiveness of an Inpatient Virtual Reality-Based Pulmonary Rehabilitation Program among COVID-19 Patients on Symptoms of Anxiety, Depression, and Quality of Life: Preliminary Results from a Randomized Controlled Trial. Int J Environ Res Public Health. 2022; 19(24): 16980. doi: 10.3390/ijerph192416980.
Cerdan-De-las-heras J, Balbino F, Lokke A, CatalanMatamoros D, Hilberg O, Bendstrup E. Telerehabilitation program in idiopathic pulmonary fibrosis-A single-center randomized trial. Int J Environ Res Public Health. 2021; 18(19): 10016. doi: 10.3390/ijerph181910016.
Rutkowski S, Szczegielniak J, Szczepanska-gieracha J. Evaluation of the efficacy of immersive virtual reality therapy as a method-supporting pulmonary rehabilitation: A randomized controlled trial. J Clin Med. 2021; 10(2): 1-12, 352. doi: 10.3390/jcm10020352.
Liu H, Yang X, Wang X, Zhang X, Zhang X, Li Q. Study on adjuvant medication for patients with mild cognitive impairment based on VR technology and health education. Contrast Media Mol Imag. 2021:
doi: 10.1155/2021/1187704.
Xie X, Fan J, Chen H, Zhu L, Wan T, Zhou J, et al. Virtual reality technology combined with comprehensive pulmonary rehabilitation on patients with stable chronic obstructive pulmonary disease. J Healthc Eng. 2021: 9987200. doi: 10.1155/2021/9987200.
Jung T, Moorhouse N, Shi X, Amin MF. A virtual realitysupported intervention for pulmonary rehabilitation of patients with chronic obstructive pulmonary disease: Mixed methods study. J Med Internet Res. 2020; 22(7): e14178. doi: 10.2196/14178.
Rutkowshi S, Rutknowska A, Kiper P, Jastrzebski D, Racheniuk H, Turolla A, et al. Virtual reality rehabilitation in patients with chronic obstructive pulmonary disease: A randomized controlled trial. Int J Chron Obstruct Pulmon Dis. 2020; 15: 117-24. doi: 10.2147/COPD.S223592.
Alves da Cruz, MM, Ricci-Vitor AL, Bonnini Borges GL, Fernanda da Silva P, Ribeiro F, Marques Vanderlei LC. Acute hemodynamic effects of virtual reality-based therapy in patients of cardiovascular rehabilitation; a cluster randomized crossover trial. Arch Phys Med Rehabil. 2020; 10(14): 642-49. doi: 10.1016/j.apmr.2019.12.006.
Knox L, Dunning M, Davies CA, Bennet RM, Sion TW, Phipps K, et al. Safety, feasibility, and effectiveness of virtual pulmonary rehabilitation in the real world. Int J Chron Obstruct Pulmon Dis. 2019; 12: 775-80. doi: 10.2147/COPD.S193827.
Rutkowski S, Rutkowska A, Jastrzebski D, Racheniuk H, Pawetczyk W, Szczegielniak J. Effect of virtual realitybased rehabilitation on physical fitness in patients with chronic obstructive pulmonary disease. J Hum Kinet. 2019; 69(1): 149-57. doi: 10.2478/hukin-2019-0022.
Wardini R, Dajczman E, Yang N, Baltzan M, Prefontaine D, Stathatos M, et al. Using a virtual game system to innovate pulmonary rehabilitation: Safety, adherence, and enjoyment in severe chronic obstructive pulmonary disease. Can Respir J. 2013; 20(5): 357-61. doi: 10.1155/2013/563861.
Heradio R, Perez-Morago H, Perez-Morago D, Cabrerizo
FJ, Herrera-Viedma E. A bibliometric analysis of 20 years of research on software product lines. Inform Sof Technol. 2016; 72: 1-15. doi: 10.1016/j.infsof.2015.11.004.
Donthu N, Kumar S, Mukherjee D, Pandey N, Lim WM. How to conduct a bibliometric analysis: An
overview and guidelines. J Bus Res. 2021; 133(2021): 285-96. doi: 10.1016/j.jbusres.2021.04.070.
Sapountzoglou N. A bibliometric analysis of risk management methods in the space sector. J Space Saf Eng. 2023; 10(1): 13-21. doi: 10.13140/RG.2.2.36270.84808/1.
Kokol L, Vosner HB, Zavrsnik J. Application of bibliometrics in medicine; a historical analysis. Health Inform Libr J. 2021; 38(2): 125-38. doi: 10.1111/hir.12295.
Pittara M, Matsangidou M, Pattichis CS. Virtual reality
for pulmonary rehabilitation: Comprehensive Review. JMIE Rehabil Assist Technol. 2023; 10: e477114. doi: 10.2196/47114.
Luukkonen T, Tijssen R, Persson O, Sivertsen G. The measurement of international scientific collaboration. Scientometrics. 1993; 28(1): 15-36. doi: 10.1007/BF02016282.
Kobourov SG. Force-directed drawing algorithms. In. Tamassia R (editor). Handbook of graph drawing and visualization, New York: CRC Press; 2013: 383-408.
Waltman L, van Eck NJ. A smart local moving algorithm for large-scale modularity-based community detection. Eur Phys J B. 2013; 86(11): 471. doi: 10.1140/epjb/e2013-40829-0.
Wang S, Koopman R. They are clustering articles based on semantic similarity. Scientometrics. 2017; 111(2): 1017-31. doi: 10.1007/s11192-017-2298-x.
De Rezende LB, Blackwell P, Pessanha Goncalves M.D. Research focuses, trends, and major findings on project complexity; A bibliometric network analysis of 50 years of project complexity research. Proj Manag J. 2018; 49(1): 42-9. doi: 10.1177/875697281804900104.
Zhuang Y, Liu X, Nguyen T, He Q, Hong S. Global remote sensing research trends during 1991-2010; a bibliometric analysis. Scientometrics. 2013; 96(1): 203-19. doi: 10.1007/s11192-012-0918-z.
Colombo V, Aliverti A, Sacco M. Virtual reality for COPD rehabilitation: a technological perspective. Pulmonology. 2022; 28(2): 119-33. doi: 10.1016/j.pulmoe.2020.11.010.
Patsaki I, Avgeri V, Rigoulia T, Zekis T, Koumantakis GA, Grammatopoulou E. Benefits from incorporating virtual reality in pulmonary rehabilitation of COPD patients: A systematic review and meta-analysis. Adv Respir Med. 2023; 91(4): 324-36. doi: 10.3390/arm91040026.
Nederhof AJ. Bibliometric monitoring of research performance in the social sciences and the humanity: A review. Scientometrics.2006; 66(1): 81-100. doi: 10.1007/s11192-006-0007-2.