Bibliometric Analysis of Internet of Things Applications in Healthcare Services

Yıl 2021, Sayı: 27, 412 - 432, 30.11.2021

Gizem Köse , Mehmet Nurullah Kurutkan

https://doi.org/10.31590/ejosat.868000

Cited By: 3

Öz

This study aims to examine the research trends of scientific publications dealing with Internet of Things (IoT) applications in healthcare. In this context, a bibliometric analysis of English articles in the Web of Science database between 2001-2019 was performed using the R programming language. In the bibliometric analysis, Biblioshiny (web interface of R program) was used. Publications were categorized their types and trends over the years were examined, it has been evaluated according to their countries', institutions' and authors'. Findings were discussed in the light of the most cited studies. This study is an important resource to present current issues of IoT applications in healthcare and to examine research trends.

Anahtar Kelimeler

Bibliometric analysis, Internet of Things, Healthcare

Sağlık Hizmetlerinde Nesnelerin İnterneti Uygulamalarının Bibliyometrik Analizi

Öz

Bu çalışmanın amacı, sağlık hizmetlerinde Nesnelerin İnterneti (IoT) uygulamalarını ele alan bilimsel yayınların araştırma eğilimlerini incelemektir. Bu bağlamda Web of Science veritabanında 2001-2019 yılları arasında yer alan İngilizce makalelerin R programlama dili kullanılarak bibliyometrik analizi yapılmıştır. Bibliyometrik analizde, R programının web arayüzü olan Biblioshiny kullanılmıştır. Yayınlar kategorize edilerek türleri, yıllara göre eğilimleri incelenmiş; ülkelerine, kurumlarına ve yazarlarına göre değerlendirilmiştir. Bulgular, en çok atıf alan çalışmalar ışığında tartışıldı. Bu çalışma sağlık alanında IoT uygulamalarının güncel konularını sunmak ve araştırma eğilimlerini incelemek için önemli bir kaynak niteliğindedir.

Anahtar Kelimeler

Bibliyometrik analiz, Nesnelerin interneti, Sağlık hizmetleri

Kaynakça

• Abawajy, J. H., & Hassan, M. M. (2017). Federated Internet of Things and cloud computing pervasive patient health monitoring system. IEEE Communications Magazine, 55(1), 48–53.
• Akhbarifar, S., Javadi, H. H. S., Rahmani, A. M., & Hosseinzadeh, M. (2020). A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment. Personal and Ubiquitous Computing, 1–17. https://doi.org/10.1007/s00779-020-01475-3.
• Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of Things: A survey on enabling technologies, protocols and applications. IEEE Communications Surveys And Tutorials, 17(4), 2347–2376.
• Albahri, A. ., Zaidan, B. ., Zaidan, A. ., Albahri, O. ., Alsalem, M. ., Mohsin, A. ., … Baqer, M. . (2019). Fault-tolerant mHealth framework in the context of IoT based real-time wearable health data sensor. IEEE Access, 7, 50052–50080. https://doi.org/10.1109/ACCESS.2019.2910411.
• Alhasan, A., Audah, L., Ibrahim, I., Al-Sharaa, A., Al-Ogaili, A. S., & Mohammed, J. M. (2020). A case-study to examine doctors’ intentions to use IoT healthcare devices in Iraq during COVID-19 pandemic. International Journal of Pervasive Computing and Communications. https://doi.org/https://doi.org/10.1108/IJPCC-10-2020-0175.
• Alhussein, M., Muhammad, G., Hossain, M. S., & Amin, S. U. (2018). Cognitive IoT-Cloud integration for smart healthcare: Case study for epileptic seizure detection and monitoring. Mobile Networks and Applications volume, 23, 1624–1635.
• Amendola, S., Lodato, R., Manzari, S., Occhiuzzi, C., & Marrocco, G. (2014). RFID technology for IOT-based personel healthcare in smart spaces. IEEE Internet of Things Journal, 1(2), 144–152.
• Amin, S. U., Hossain, M. S., Muhammed, G., Alhussein, M., & Rahman, M. A. (2019). Cognitive smart healthcare for pathology detection and monitoring. IEEE Access, 7, 10745–10753. https://doi.org/10.1109/ACCESS.2019.2891390.
• Asghari, P., Rahmani, A. M., & Javadi, H. H. S. (2019). Internet Of Things application: A systematic review. Computer Networks, 148, 241–261.
• Baker, S. B., Xiang, W., & Atkinson, I. (2017). Internet of Things for smart healthcare: Technologies, challenges and opportunities. IEEE Access, 5, 26521–26544.
• Barata, J. J. R., Munoz, R., De Carvalho Silva, R. D., Rodrigues, J., & Albuquerque, V. H. (2019). Internet of Things based on electronic and mobile health systems for blood glucose continuous monitoring and management. IEEE Access, 7, 175116–175125. https://doi.org/10.1109/ACCESS.2019.2956745.
• Bhatt, Y., & Bhatt, C. (2017). Internet of Things in HealthCare. Içinde Internet of Things and Big Data Technologies for Next Generation Healthcare (ss. 13–33). Cham, Switzerland: Springer International Publishing AG.
• Bornmann, L., & Daniel, H. D. (2007). What do we know about the h index? Journal of the American Society for Information Science and Technology, 58(9), 1381–1385.
• Bouzembrak, Y., Klüche, M., Gavai, A., & Marvin, H. J. P. (2019). Internet of Things in food safety: Literature review and a bibliometric analysis. Trends in Food Science & Technology, 94, 54–64.
• Castillejo, P., Martinez, J.-F., Rodriguez Molina, J., & Cuerva, A. (2013). Integration of wearable devices in a wireless sensor network for an e-health application. IEEE Wireless Communications, 20(4). https://doi.org/10.1109/MWC.2013.6590049.
• Catarinucci, L., De Donno, D., Mainetti, L., Palano, L., Patrono, L., Stefanizzi, M. L., & Tarricone, L. (2015). An IoT-Aware architecture for smart healthcare systems. IEEE Internet of Things Journal, 2(6), 515–526. https://doi.org/10.1109/JIOT.2015.2417684.
• Chen, M., Ma, Y., Li, Y., Wu, D., Zhang, Y., & Youn, C. H. (2017). Wearable 2.0: Enabling human-cloud integration in next generation healthcare systems. IEEE Communications Magazine, 55(1), 54–61. https://doi.org/10.1109/MCOM.2017.1600410CM.
• Dadkhah, M., Lagzian, M., Rahimnia, F., & Kimiafar, K. (2020). What do publications say about the Internet of Things challenges/barriers to unnformed authors? A bibliometric analysis. JLIS.it, 11(3), 77–98. https://doi.org/10.4403/jlis.it-12634.
• Darwish, A., Hassanien, A. E., Elhoseny, M., Sangaiah, A. K., & Muhammmad, K. (2019). The impact of the hybrid platform of internet of things and cloud computing on healthcare systems: opportunities, challenges, and open problems. Journal of Ambient Intelligence and Humanized Computing, 10, 4151–4166. https://doi.org/https://doi.org/10.1007/s12652-017-0659-1.
• Dimitrov, D. (2016). Medical Internet of Things and Big Data in Healthcare. Healthcare Informatics Research, 22(3), 156–163.
• Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152.
• Elhoseny, M., Abdelaziz, A., Salama, A. S., Riad, A. M., Muhammad, K., & Sangaiah, A. K. (2018). A hybrid model of Internet of Things and cloud computing to manage big data in health services applications. Future Generation Computer Systems, 86, 1383–1394. https://doi.org/https://doi.org/10.1016/j.future.2018.03.005.
• European Environment Agency. (2020). R Core Team (2020). Tarihinde 06 Aralık 2020, adresinden erişildi https://www.eea.europa.eu/data-and-maps/indicators/oxygen-consuming-substances-in-rivers/r-development-core-team-2006.
• Griggs, K. N., Ossipova, O., Kohlios, C. P., Baccarini, A. N., Howson, E. A., & Thaier, H. (2018). Healthcare blockchain system using smart contracts for secure automated remote patient monitoring. Journal of Medical Systems, 42, 130. https://doi.org/10.1007/s10916-018-0982-x.
• Harzing, A. W. (2012). Reflections on the h-index. Business&Leadership, 1(9), 101–106.
• Hirsch, J. E. (2007). Does the h index have predictive power? PNAS, 104(49), 19193–19198.
• Hossain, M. S., & Muhammad, G. (2016). Cloud-assisted Industrial Internet of Things (IIoT) - Enabled framework for health monitoring. Computer Networks, 101, 192–202. https://doi.org/https://doi.org/10.1016/j.comnet.2016.01.009.
• Hossain, M. S., & Muhammad, G. (2017). Emotion-aware connected healthcare big data towards 5G. IEEE Internet of Things Journal, 5(4), 2399–2406. https://doi.org/10.1109/JIOT.2017.2772959.
• IEEE Access. (2020). Learn More About IEEE Access. Tarihinde 22 Kasım 2020, adresinden erişildi https://ieeeaccess.ieee.org/about-ieee-access/learn-more-about-ieee-access/.
• Islam, S. M. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K.-S. (2015). The Internet of Things for health care: A comprehensive survey. IEEE Access, 3, 678–708. https://doi.org/10.1109/ACCESS.2015.2437951.
• Kelly, J. T., Campbell, K. L., & Scuffham, P. (2020). The Internet of Things: Impact and implications for health care delivery. Journal of Medical Internet Research, 22(11). https://doi.org/10.2196/20135.
• Kumar Dwivedi, R., Kumar, R., & Buyya, R. (2021). Gaussian Distribution-based machine learning for anomaly detection in healthcare sensor cloud. International Journal of Cloud Applications and Computing (IJCAC), 11(1), 52–72.
• Kumar, P., Kumari, S., Sangaiah, A. K., Wei, J., & Li, X. (2018). A certificateless aggregate signature scheme for healthcare wireless sensor network. Sustainable Computing: Informatics and Systems, 18, 80–89. https://doi.org/http://dx.doi.org/10.1016/j.suscom.2017.09.002.
• Kumar, P. M., Lokesh, S., Varatharajan, R., Babu, G. C., & Parthasarathy, P. (2018). Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier. Future Generation Computer Systems, 86(527–534). https://doi.org/https://doi.org/10.1016/j.future.2018.04.036.
• Li, G., Xu, G., Sangaiah, A. K., Wu, J., & Li, J. (2019). EdgeLaaS: Edge Learning as a Service for Knowledge-Centric Connected Healthcare. IEEE, 33(6), 37–43. https://doi.org/10.1109/MNET.001.1900019.
• Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington Academy of Sciences, 16(12), 317–323.
• MA, Y., Wang, Y., Yang, J., Miao, Y., & Li, W. (2016). Big Health Application System based on Health Internet of Things and Big Data. IEEE Access, 5, 7885–7897. https://doi.org/10.1109/ACCESS.2016.2638449.
• Madjido, M., Espressivo, A., Maula, A. W., Fuad, A., & Hasanbasri, M. (2019). Health information system research situation in Indonesia: A bibliometric analysis. Procedia Computer Science, 161, 781–787. https://doi.org/https://doi.org/10.1016/j.procs.2019.11.183.
• Mahmoud, M. M. E., Rodrigues, J., Ahmed, S. H., Shah, S. C., Al Muhtadi, J., Korotaev, V., & Albuquerque, V. H. (2018). Enabling technologies on Cloud of Things for Smart Healthcare. IEEE Access, 6, 31950–31967. https://doi.org/10.1109/ACCESS.2018.2845399.
• Mahmoud, M. M. E., Rodrigues, J., Saleem, K., Al Muhtadi, J., & Korotaev, V. (2018). Towards energy-aware fog-enabled cloud of things for healthcare. Computers and Electrical Engineering, 67, 58–69.
• Mano, L. Y., Faiçal, B. S., Nakamura, L. H. V, Gomes, P. H., Libralon, G. L., Meneguete, R. I., … Ueyama, J. (2016). Exploiting IoT technologies for enhancing Health Smart Homes through patient identification and emotion recognition. Computer Communications, 89(90), 178–190. https://doi.org/https://doi.org/10.1016/j.comcom.2016.03.010.
• Manyika, J., Michael, C., Bughin, J., Dobbs, R., Bisson, P., & Marrs, A. (2013). Disruptive technologies: Advances that will transform life, business, and the global economy. San Francisco, CA, USA.
• MDPI. (2020). Sensors. Tarihinde 22 Kasım 2020, adresinden erişildi https://www.mdpi.com/journal/sensors.
• Nepal, S., Ranjan, R., & Choo, K.-K. R. (2015). Trustworthy processing of healthcare big data in hybrid clouds. IEEE Cloud Compiting, 2(2), 78–84. https://doi.org/10.1109/MCC.2015.36.
• Ngayua, E. N., He, J., & Boahene, K. A. (2020). Applying advanced technologies to improve clinical trials: a systematic mapping study. Scientometrics, 21, 1–22. https://doi.org/10.1007/s11192-020-03774-1.
• Pai, R. R., & Alathur, S. (2021). Bibliometric Analysis and Methodological Review of Mobile Health Services and Applications in India. International Journal of Medical Informatics, 145, 104330. https://doi.org/https://doi.org/10.1016/j.ijmedinf.2020.104330.
• Pang, Z., Zheng, L., Tian, J., Kao-Walter, S., Dubrova, E., & Chen, Q. (2015). Design of a terminal solution for integration of in-home health care devices and services towards the Internet-of-Things. Enterprise Information Systems, 9(1), 86–116.
• Pernitez-Agan, S., Bautistia, M. A., Lopez, J., Sampson, M., & Wickramage, K. (2020). Bibliometric analysis of Covid-19 in the context migration health: A study protocol. medRxiv, 1–10. https://doi.org/https://doi.org/10.1101/2020.07.09.20149401.
• Potter, W. . (1988). Of making many books there is no end’: bibliometrics and libraries. Journal of Academic Librarianship, 14(4), 238a-9c.
• Prajapati, V. (2013). Big Data Analytics with R and Hadoop. UK: Packt Publishing.
• Princi, E., & Kramer, N. (2020). Out of control-privacy calculus and the effect of perceived control and moral considerations on the usage of IoT healthcare devices. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.582054.
• Purandhar, N., Ayyasamy, S., & Saravanakumar, N. . (2020). Clustering healthcare big data using advanced and enhanced fuzzy C‐means algorithm. International Journal of Communication Systems, 34(1). https://doi.org/https://doi.org/10.1002/dac.4629.
• Qi, J., Yang, P., Waraich, A., Deng, Z., Zhao, Y., & Yang, Y. (2018). Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review. Journal of Biomedical Informatics, 87, 138–153. https://doi.org/https://doi.org/10.1016/j.jbi.2018.09.002.
• Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., & Liljeberg, P. (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things:A fog computing approach. Future Generation Computer Systems-The International Journal of Escience, 78(2), 641–658.
• Rawashdeh, M., Mohammed, G. A. Z., Hossain, M. S., Samarah, S., Amin, S. U., & Muhammad, G. (2018). Reliable service delivery in Tele-health care systems. Journal of Network and Computer Applications, 115. https://doi.org/10.1016/j.jnca.2018.04.015.
• Rodrigues, JJPC Segundo, D., Junqueira, H., Sabino, M., Prince, R., Al-Muhtadi, J., & Albuquerque, D. (2018). Enabling Technologies for the Internet of Health Things. IEEE Access, 6, 13129–131141. https://doi.org/10.1109/ACCESS.2017.2789329.
• Rodriquez-Soler, R., Uribe-Toril, J., & Valencio, J. D. P. (2020). Worldwide trends in the scientific production on rural depopulation, a bibliometric analysis using bibliometrix R-tool. Land Use Policy, 97, 104787.
• Roehrs, A., da Costa, C. A., Righi, R. da R., & Farias de Oliveira, K. S. (2017). Personal health records: A systematic literature review. Journal of Medical Internet Research, 19(1). https://doi.org/10.2196/jmir.5876.
• Rowlands, I. (2004). Emerald authorship data, Lotka’s law and research productivity. Emerald Insight, 57(1), 5–10.
• Sadoughi, F., Behmanesh, A., & Sayfouri, N. (2020). Internet of things in medicine: A systematic mapping study. Journal of Biomedical Informatics, 103, 103383. https://doi.org/https://doi.org/10.1016/j.jbi.2020.103383.
• Santos, J., Rodrigues, J., Silva, B. M., Casal, J., Saleem, K., & Denisov, V. (2016a). An Iot-based mobile gateway for intelligent personal assistans on mobile health environments. Journal of Network and Computer Applications. https://doi.org/http://dx.doi.org/10.1016/j.jnca.2016.03.014.
• Santos, J., Rodrigues, J., Silva, B. M., Casal, J., Saleem, K., & Denisov, V. (2016b). An IoT-based mobile gateway for intelligent personal assistants on mobile health environments. Journal of Network and Computer Applications, 71. https://doi.org/10.1016/j.jnca.2016.03.014.
• Shang, G., Saladin, B., Fry, T., & Donohue, J. (2015). Twenty-six years of operations management research (1985–2010): authorship patterns and research constituents in eleven top rated journals. International Journal of Production Research, 53(20), 6161–6197.
• Sodhro, A. H., Pirbhulal, S., & Sangaiah, A. K. (2018). Convergence of IoT and product lifecycle management in medical health care. Future Generation Computer Systems, 86, 380–391. https://doi.org/https://doi.org/10.1016/j.future.2018.03.052.
• Suciu, G., Martian, A., Craciunescu, R., Vulpe, A., Marcu, I., Halunga, S., & Fratu, O. (2015). Big data, Internet of Things and Clous Convergence-An architecture for secure e-health applications. Journal of Medical Systems, 39(11), 327. https://doi.org/10.1007/s10916-015-0327-y.
• Talal, M., Zaidan, A. ., Zaidan, B. ., Albahri, A. ., Alamoodi, A. ., Albahri, O. ., … Mohammed, K. . (2019). Smart Home-based IoT for real-time and secure remote health monitoring of triage and priority system using body sensors: Multi-driven systematic review. Journal of Medical Systems, 43(42), 1–34. https://doi.org/https://doi.org/10.1007/s10916-019-1158-z.
• The R Foundation. (2020). What is R? Tarihinde 06 Aralık 2020, adresinden erişildi https://www.r-project.org/about.html.
• Tian, S., Yang, W., Grange, J. M. Le, Wang, P., Huang, W., & Ye, Z. (2019). Smart healthcare: making medical care more intelligent. Global Health Journal, 3(3), 62–65. https://doi.org/10.1016/j.glohj.2019.07.001.
• Tsai, J. C., Leu, J.-S., Prakosa, S. W., Hsiao, L.-C., Huang, P.-C., Yang, S.-Y., & Huang, Y.-T. (2020). Design and implementation of an Internet of Healthcare Things System for respiratory diseases. Wireless Personal Communications, 1–14. https://doi.org/10.1007/s11277-020-07871-5.
• Uslu, Çalış, B., Okay, E., & Dursun, E. (2020). Analysis of factors affecting IoT-based smart hospital design. J Cloud Comp, 9(1). https://doi.org/10.1186/s13677-020-00215-5.
• Vilela, P. H., Rodrigues, J., Solic, P., Saleem, K., & Furtado, V. (2019). Performance evaluation of a fog-assisted IoT solution for e-Health applications. Future Generation Computer Systems, 97, 379–386.
• Wu, F., Li, X., Sangaiah, A. K., Xu, L., Kumari, S., Wu, L., & Shen, J. (2018). A lightweight and robust two-factor authentication scheme for personalized healthcare systems using wireless medical sensor networks. Future Generation Computer Systems, 82, 727–737. https://doi.org/https://doi.org/10.1016/j.future.2017.08.042.
• Xiang, G. Y., Zeng, Z., & Shen, Y. J. (2016). Present Situation and Development Trend of China’s Intelligent Medical Construction. Chinese General Practice, 19(24), 2998–3000. https://doi.org/10.3969/j.issn.1007-9572.2016.24.027.
• Xie, C., Cai, H., Yang, Y., Jiang, L., & Yang, P. (2018). User profiling in elderly healthcare services in China: Scalper Detection. IEEE Journal of Biomedical and Health Informatics, 22(6), 1796–1806. https://doi.org/10.1109/JBHI.2018.2852495.
• Yang, P., Qi, J., Min, G., & Xu, L. (2017). Advanced Internet of Things for personalised healthcare system: A survey. Pervasive and Mobile Computing, 41, 132–149.
• Yang, P., Stankevicius, D., Marozas, V., Deng, Z., Liu, E., Lukosevicius, A., … Min, G. (2018). Lifelogging data validation model for Internet of Things enabled personalized healthcare. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(1), 50–64.
• Yang, Yang, Zheng, X., Guo, W., Liu, X., & Chang, V. (2019). Privacy-preserving smart IoT-based healthcare big data storage and self-adaptive access control system. Information Sciences, 479, 567–592.
• Yang, Yun, Nan, F., Yang, P., Meng, Q., Xie, Y., Zhang, D., & Muhammad, K. (2019). GAN-Based Semi- Supervised learning approach for clinical decision support in health-IoT platform. IEEE Access, 7, 8048–8057. https://doi.org/10.1109/ACCESS.2018.2888816.
• Yin, Y., Zeng, Y., Chen, X., & Fan, Y. (2016). The internet of things in healthcare: An overview. Journal of Industrial Information Integration, 1, 3–13.
• Zhang, D., Xia, X., Yang, Y., Yang, P., Xie, C., Cui, M., & Liu, Q. (2021). A novel word similarity measure method for IoT-enabled healthcare applications. Future Generation Computer Systems, 114, 209–218. https://doi.org/https://doi.org/10.1016/j.future.2020.07.053.
• Zupic, I., & Cater, T. (2014). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472.