La revisión bibliográfica es una fase fundamental en un proyecto de investigación, y debe garantizar la obtención de la información más relevante en el campo de estudio. El objetivo principal de este proyecto es conocer los trabajos relacionados con el Internet de las Cosas Médicas, en adelante (IoMT). Se analiza un total de 535 artículos buscados en Association for Computing Machinery, en Adelante ACM, Web of Science y Scopus el dominio de búsqueda fue IoMT. Se establecieron tres parámetros, (problemática, artefacto y evaluación del artefacto), esto de acuerdo a la Investigación de la Ciencia del Diseño, en Adelante DSR, es un enfoque de investigación para la construcción de artefactos para proporcionar una solución útil a un problema en cada dominio. La ecuación (Internet de las cosas Y malla) dio como resultado 535, (Internet de las cosas Y medicina) un total de 417 y finalmente (Internet de las cosas Y malla médica) con 8, esto significa que hay mucho por indagar en este dominio de investigación. Las ventajas identificadas en este tipo de topología es llevar los mensajes de un nodo a otro por diferentes caminos, no puede haber absolutamente ninguna interrupción en las comunicaciones, cada servidor tiene sus propias comunicaciones con todos los demás servidores. Los grandes datos procedentes de los dispositivos IoMT han influido drásticamente en las cuestiones de salud e informática. En este documento, se realiza una revisión de la literatura científica y se mapean las tendencias de investigación sobre el paradigma IoMT en el ámbito de la salud. Por último, este documento amplía la literatura, y los resultados de este estudio pueden servir de base para futuras investigaciones.
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Referencias
Al-Kaisey, A. M., Koshy, A. N., Ha, F. J., Spencer, R., Toner, L., Sajeev, J. K., Teh, A. W., Farouque, O., & Lim, H. S. (2020). Accuracy of wrist-worn heart rate monitors for rate control assessment in atrial fibrillation. International Journal of Cardiology, 300, 161–164. https://doi.org/10.1016/j.ijcard.2019.11.120
Alarifi, A., AlZubi, A. A., & Al-Maitah, M. (2019). Study of soft-tissues borderline class I malocclusion on tooth extraction and non-extraction process using medical IoT device. Measurement: Journal of the International Measurement Confederation, 134, 923–929. https://doi.org/10.1016/j.measurement.2018.11.087
Ali, M. M., Haxha, S., Alam, M. M., Nwibor, C., & Sakel, M. (2020). Design of Internet of Things (IoT) and Android Based Low Cost Health Monitoring Embedded System Wearable Sensor for Measuring SpO2, Heart Rate and Body Temperature Simultaneously. Wireless Personal Communications, 111(4), 2449–2463. https://doi.org/10.1007/s11277-019-06995-7
Alonso-Rosa, M., Gil-de-Castro, A., Medina-Gracia, R., Moreno-Munoz, A., & Cañete-Carmona, E. (2018). Novel internet of things platform for in-building power quality submetering. Applied Sciences (Switzerland), 8(8). https://doi.org/10.3390/app8081320
Arulanthu, P., & Perumal, E. (2020). An intelligent IoT with cloud centric medical decision support system for chronic kidney disease prediction. International Journal of Imaging Systems and Technology, 30(3), 815–827. https://doi.org/10.1002/ima.22424
Awan, K. M., Ashraf, N., Saleem, M. Q., Sheta, O. E., Qureshi, K. N., Zeb, A., Haseeb, K., & Sadiq, A. S. (2019). A priority-based congestion-avoidance routing protocol using IoT-based heterogeneous medical sensors for energy efficiency in healthcare wireless body area networks. International Journal of Distributed Sensor Networks, 15(6). https://doi.org/10.1177/1550147719853980
Cappon, G., Acciaroli, G., Vettoretti, M., Facchinetti, A., & Sparacino, G. (2017). Wearable continuous glucose monitoring sensors: A revolution in diabetes treatment. Electronics (Switzerland), 6(3), 1–16. https://doi.org/10.3390/electronics6030065
Chen, C. L., Yang, T. T., Deng, Y. Y., & Chen, C. H. (2020). A secure Internet of Things medical information sharing and emergency notification system based on nonrepudiation mechanism. Transactions on Emerging Telecommunications Technologies, February, 1–21. https://doi.org/10.1002/ett.3946
Choi, J., Choi, C., Kim, S. H., & Ko, H. (2019). Medical information protection frameworks for smart healthcare based on IoT. ACM International Conference Proceeding Series. https://doi.org/10.1145/3326467.3326496
Cubillos-Calvachi, J., Piedrahita-Gonzalez, J., Gutiérrez-Ardila, C., Montenegro-Marín, C., Gaona-García, P., & Burgos, D. (2020). Analysis of stress’s effects on cardiac dynamics: A case study on undergraduate students. International Journal of Medical Informatics, 137(September 2019). https://doi.org/10.1016/j.ijmedinf.2020.104104
Cui, F., Ma, L., Hou, G., Pang, Z., Hou, Y., & Li, L. (2020). Development of smart nursing homes using systems engineering methodologies in industry 4.0. Enterprise Information Systems, 14(4), 463–479. https://doi.org/10.1080/17517575.2018.1536929
da Silva, V. J., Souza, V. da S., da Cruz, R. G., de Lucena, J. M. V. M., Jazdi, N., & Junior, V. F. de L. (2019). Commercial devices-based system designed to improve the treatment adherence of hypertensive patients. Sensors (Switzerland), 19(20), 1–31. https://doi.org/10.3390/s19204539
Díaz de León-Castañeda, C. (2019). Electronic health (e-Health): a conceptual framework for its implementation in health services facilities. Gaceta de México, 155(2), 161–168. https://doi.org/10.24875/gmm.m19000251
Elsts, A., Fafoutis, X., Woznowski, P., Tonkin, E., Oikonomou, G., Piechocki, R., & Craddock, I. (2018). Enabling Healthcare in Smart Homes: The SPHERE IoT Network Infrastructure. IEEE Communications Magazine, 56(12), 164–170. https://doi.org/10.1109/MCOM.2017.1700791
Evangeline, C. S., & Lenin, A. (2019). Human health monitoring using wearable sensor. Sensor Review, 39(3), 364–376. https://doi.org/10.1108/SR-05-2018-0111
Farahani, B., Barzegari, M., Shams Aliee, F., & Shaik, K. A. (2020). Towards collaborative intelligent IoT eHealth: From device to fog, and cloud. Microprocessors and Microsystems, 72, 102938. https://doi.org/10.1016/j.micpro.2019.102938
Garbhapu, V. V., & Gopalan, S. (2017). IoT Based Low Cost Single Sensor Node Remote Health Monitoring System. Procedia Computer Science, 113, 408–415. https://doi.org/10.1016/j.procs.2017.08.357
Gupta, A., Chakraborty, C., & Gupta, B. (2019). Smartphone Under IoT Framework. 283–308. https://doi.org/10.1007/978-981-13-7399-2
Han, T., Zeng, M., Zhang, L., & Sangaiah, A. K. (2020). A Channel-Aware Duty Cycle Optimization for Node-to-Node Communications in the Internet of Medical Things. International Journal of Parallel Programming, 48(2), 264–279. https://doi.org/10.1007/s10766-018-0587-5
Haoyu, L., Jianxing, L., Arunkumar, N., Hussein, A. F., & Jaber, M. M. (2019). An IoMT cloud-based real time sleep apnea detection scheme by using the SpO2 estimation supported by heart rate variability. Future Generation Computer Systems, 98, 69–77. https://doi.org/10.1016/j.future.2018.12.001
Hedrick, T. L., Hassinger, T. E., Myers, E., Krebs, E. D., Chu, D., Charles, A. N., Hoang, S. C., Friel, C. M., & Thiele, R. H. (2020). Wearable technology in the perioperative period: Predicting risk of postoperative complications in patients undergoing elective colorectal surgery. Diseases of the Colon and Rectum, 4, 538–544. https://doi.org/10.1097/DCR.0000000000001580
Huang, X., Li, Y., Chen, J., Liu, J., Wang, R., Xu, X., Yao, J., & Guo, J. (2019). Smartphone-Based Blood Lipid Data Acquisition for Cardiovascular Disease Management in Internet of Medical Things. IEEE Access, 7, 75276–75283. https://doi.org/10.1109/ACCESS.2019.2922059
Ignacio, J., Luna, V., Javier, F., Rangel, S., Francisco, J., & Aceves, C. (2019). MONITOREO DE SIGNOS VITALES USANDO IoT. 41(134), 751–769.
K., J., & Desai, A. (2016). IoT: Networking Technologies and Research Challenges. International Journal of Computer Applications, 154(7), 1–6. https://doi.org/10.5120/ijca2016912181
Kan, C., Chen, Y., Leonelli, F., & Yang, H. (2015). Mobile sensing and network analytics for realizing smart automated systems towards health Internet of Things. IEEE International Conference on Automation Science and Engineering, 2015-Octob, 1072–1077. https://doi.org/10.1109/CoASE.2015.7294241
Kang, S., Baek, H., Jun, S., Choi, S., Hwang, H., & Yoo, S. (2018). Laboratory environment monitoring: Implementation experience and field study in a tertiary general hospital. Healthcare Informatics Research, 24(4), 371–375. https://doi.org/10.4258/hir.2018.24.4.371
Karthick, T., & Manikandan, M. (2019). Fog assisted IoT based medical cyber system for cardiovascular diseases affected patients. Concurrency Computation , 31(12), 1–9. https://doi.org/10.1002/cpe.4861
Khan, S. U., Islam, N., Jan, Z., Din, I. U., Khan, A., & Faheem, Y. (2019). An e-Health care services framework for the detection and classification of breast cancer in breast cytology images as an IoMT application. Future Generation Computer Systems, 98, 286–296. https://doi.org/10.1016/j.future.2019.01.033
Kodali, R. K., Swamy, G., & Lakshmi, B. (2016). An implementation of IoT for healthcare. 2015 IEEE Recent Advances in Intelligent Computational Systems, RAICS 2015, December, 411–416. https://doi.org/10.1109/RAICS.2015.7488451
Lam, C., Van Velthoven, M. H., & Meinert, E. (2020). Application of internet of things in cell-based therapy delivery: Protocol for a systematic review. JMIR Research Protocols, 9(3), 1–6. https://doi.org/10.2196/16935
Latif, G., Shankar, A., Alghazo, J. M., Kalyanasundaram, V., Boopathi, C. S., & Arfan Jaffar, M. (2020). I-CARES: advancing health diagnosis and medication through IoT. Wireless Networks, 26(4), 2375–2389. https://doi.org/10.1007/s11276-019-02165-6
Leahy, J. L. (2008). Fully Automated Closed-Loop Insulin Delivery Versus Semiautomated Hybrid Control in Pediatric Patients With Type 1 Diabetes Using an Artificial Pancreas. Yearbook of Endocrinology, 2008, 55–57. https://doi.org/10.1016/s0084-3741(08)79222-9
Liu, L., Xu, J., Huan, Y., Zou, Z., Yeh, S. C., & Zheng, L. R. (2020). A Smart Dental Health-IoT Platform Based on Intelligent Hardware, Deep Learning, and Mobile Terminal. IEEE Journal of Biomedical and Health Informatics, 24(3), 898–906. https://doi.org/10.1109/JBHI.2019.2919916
Mavrogiorgou, A., Kiourtis, A., Perakis, K., Pitsios, S., & Kyriazis, D. (2019). IoT in Healthcare: Achieving Interoperability of High-Quality Data Acquired by IoT Medical Devices. Sensors (Basel, Switzerland), 19(9). https://doi.org/10.3390/s19091978
Medeiros, V. N., Silvestre, B., & Borges, V. C. M. (2019). Multi-objective routing aware of mixed IoT traffic for low-cost wireless Backhauls. Journal of Internet Services and Applications, 10(1). https://doi.org/10.1186/s13174-019-0108-9
Montiveros, M., Murazzo, M., Garabetti, M. M., Ros, J. S., & Rodríguez, N. (2018). Análisis de las Topologías IoT en Entornos Fog Computing mediante simulación. Libro de Actas JCC&BD 2018, 90–100.
Morzy, T., Härder, T., & Wrembel, R. (2013). Advances in Intelligent Systems and Computing: Preface. In Advances in Intelligent Systems and Computing: Vol. 186 AISC. https://doi.org/10.1007/978-3-030-37218-7
Mumtaz, S., Bo, A., Al-Dulaimi, A., & Tsang, K. F. (2018). Guest Editorial 5G and beyond Mobile Technologies and Applications for Industrial IoT (IIoT). IEEE Transactions on Industrial Informatics, 14(6), 2588–2591. https://doi.org/10.1109/TII.2018.2823311
Ng, C. L., Reaz, M. B. I., & Chowdhury, M. E. H. (2020). A Low Noise Capacitive Electromyography Monitoring System for Remote Healthcare Applications. IEEE Sensors Journal, 20(6), 3333–3342. https://doi.org/10.1109/JSEN.2019.2957068
Nørfeldt, L., Bøtker, J., Edinger, M., Genina, N., & Rantanen, J. (2019). Cryptopharmaceuticals: Increasing the Safety of Medication by a Blockchain of Pharmaceutical Products. Journal of Pharmaceutical Sciences, 108(9), 2838–2841. https://doi.org/10.1016/j.xphs.2019.04.025
Palani, D., & Venkatalakshmi, K. (2019). An IoT Based Predictive Modelling for Predicting Lung Cancer Using Fuzzy Cluster Based Segmentation and Classification. Journal of Medical Systems, 43(2). https://doi.org/10.1007/s10916-018-1139-7
Peng, Y., Wang, X., Guo, L., Wang, Y., & Deng, Q. (2017). An efficient network coding-based fault-tolerant mechanism in WBAN for smart healthcare monitoring systems. Applied Sciences (Switzerland), 7(8). https://doi.org/10.3390/app7080817
Performance, D. (2018). Five Requirements of a Good Strategy.pdf.
Pirbhulal, S., Samuel, O. W., Wu, W., Sangaiah, A. K., & Li, G. (2019). A joint resource-aware and medical data security framework for wearable healthcare systems. Future Generation Computer Systems, 95, 382–391. https://doi.org/10.1016/j.future.2019.01.008
Plageras, A. P., Psannis, K. E., Ishibashi, Y., & Kim, B. G. (2016). IoT-based surveillance system for ubiquitous healthcare. IECON Proceedings (Industrial Electronics Conference), 0, 6226–6230. https://doi.org/10.1109/IECON.2016.7793281
Quincozes, S., Emilio, T., & Kazienko, J. (2019). MQTT protocol: Fundamentals, tools and future directions. IEEE Latin America Transactions, 17(9), 1439–1448. https://doi.org/10.1109/TLA.2019.8931137
Qureshi, F., & Krishnan, S. (2018). Wearable hardware design for the internet of medical things (IoMT). Sensors (Switzerland), 18(11). https://doi.org/10.3390/s18113812
Rachakonda, L., Mohanty, S. P., & Kougianos, E. (2020). ILog: An Intelligent Device for Automatic Food Intake Monitoring and Stress Detection in the IoMT. IEEE Transactions on Consumer Electronics, 66(2), 115–124. https://doi.org/10.1109/TCE.2020.2976006
Rachakonda, L., Mohanty, S. P., Kougianos, E., & Sundaravadivel, P. (2019). Stress-Lysis: A DNN-Integrated Edge Device for Stress Level Detection in the IoMT. IEEE Transactions on Consumer Electronics, 65(4), 474–483. https://doi.org/10.1109/TCE.2019.2940472
Rajasekaran, M., Yassine, A., Hossain, M. S., Alhamid, M. F., & Guizani, M. (2019). Autonomous monitoring in healthcare environment: Reward-based energy charging mechanism for IoMT wireless sensing nodes. Future Generation Computer Systems, 98, 565–576. https://doi.org/10.1016/j.future.2019.01.021
Rajput, A., & Brahimi, T. (2019a). Characterizing internet of medical things/personal area networks landscape. In Innovation in Health Informatics: A Smart Healthcare Primer. Elsevier Inc. https://doi.org/10.1016/B978-0-12-819043-2.00015-0
Rajput, A., & Brahimi, T. (2019b). Characterizing IOMT/personal area networks landscape. ArXiv, 1–29.
Rani, S., Ahmed, S. H., & Shah, S. C. (2019). Smart health: A novel paradigm to control the chickungunya virus. IEEE Internet of Things Journal, 6(2), 1306–1311. https://doi.org/10.1109/JIOT.2018.2802898
Rubí, J. N. S., & Gondim, P. R. L. (2019). IoMT platform for pervasive healthcare data aggregation, processing, and sharing based on oneM2M and openEHR. Sensors (Switzerland), 19(19), 1–25. https://doi.org/10.3390/s19194283
Sánchez, A. A., González Guerrero, E., & Barreto, L. E. (2019). Modelo informático integrado AmI-IoT-DA para el cuidado de personas mayores que viven solas. Revista Colombiana de Computación, 20(1), 59–71. https://doi.org/10.29375/25392115.3607
Sanders, J. E., Garbini, J. L., McLean, J. B., Hinrichs, P., Predmore, T. J., Brzostowski, J. T., Redd, C. B., & Cagle, J. C. (2019). A motor-driven adjustable prosthetic socket operated using a mobile phone app: A technical note. Medical Engineering and Physics, 68, 94–100. https://doi.org/10.1016/j.medengphy.2019.04.003
Santagati, G. E., Dave, N., & Melodia, T. (2020). Design and performance evaluation of an implantable ultrasonic networking platform for the internet of medical things. IEEE/ACM Transactions on Networking, 28(1), 29–42. https://doi.org/10.1109/TNET.2019.2949805
Sarmento, R. M., Vasconcelos, F. F. X., Filho, P. P. R., & de Albuquerque, V. H. C. (2020). An IoT platform for the analysis of brain CT images based on Parzen analysis. Future Generation Computer Systems, 105, 135–147. https://doi.org/10.1016/j.future.2019.11.033
Sayeed, M. A., Mohanty, S. P., Kougianos, E., & Zaveri, H. P. (2019). Neuro-Detect: A Machine Learning-Based Fast and Accurate Seizure Detection System in the IoMT. IEEE Transactions on Consumer Electronics, 65(3), 359–368. https://doi.org/10.1109/TCE.2019.2917895
Sharman, J. E., O’Brien, E., Alpert, B., Schutte, A. E., Delles, C., Hecht Olsen, M., Asmar, R., Atkins, N., Barbosa, E., Calhoun, D., Campbell, N. R. C., Chalmers, J., Benjamin, I., Jennings, G., Laurent, S., Boutouyrie, P., Lopez-Jaramillo, P., McManus, R. J., Mihailidou, A. S., … Stergiou, G. (2020). Lancet Commission on Hypertension group position statement on the global improvement of accuracy standards for devices that measure blood pressure. Journal of Hypertension, 38(1), 21–29. https://doi.org/10.1097/HJH.0000000000002246
Silvestre-Blanes, J., Sempere-Payá, V., & Albero-Albero, T. (2020). Smart sensor architectures for multimedia sensing in iomt. Sensors (Switzerland), 20(5), 1–16. https://doi.org/10.3390/s20051400
Song, J., Pandian, V., Mauk, M. G., Bau, H. H., Cherry, S., Tisi, L. C., & Liu, C. (2018). Smartphone-Based Mobile Detection Platform for Molecular Diagnostics and Spatiotemporal Disease Mapping. Analytical Chemistry, 90(7), 4823–4831. https://doi.org/10.1021/acs.analchem.8b00283
Sood, S. K., & Mahajan, I. (2019). IoT-fog-based healthcare framework to identify and control hypertension attack. IEEE Internet of Things Journal, 6(2), 1920–1927. https://doi.org/10.1109/JIOT.2018.2871630
Toor, A. A., Usman, M., Younas, F., Fong, A. C. M., Khan, S. A., & Fong, S. (2020). Mining massive e-health data streams for IoMT enabled healthcare systems. Sensors (Switzerland), 20(7), 1–24. https://doi.org/10.3390/s20072131
Ullah, F., Habib, M. A., Farhan, M., Khalid, S., Durrani, M. Y., & Jabbar, S. (2017). Semantic interoperability for big-data in heterogeneous IoT infrastructure for healthcare. Sustainable Cities and Society, 34, 90–96. https://doi.org/10.1016/j.scs.2017.06.010
Vellappally, S., Al Kheraif, A. A., Anil, S., & Wahba, A. A. (2019). IoT medical tooth mounted sensor for monitoring teeth and food level using bacterial optimization along with adaptive deep learning neural network. Measurement: Journal of the International Measurement Confederation, 135, 672–677. https://doi.org/10.1016/j.measurement.2018.11.078
Xing, F., Peng, G., Liang, T., & Jiang, J. (2018). Challenges for deploying IoT wearable medical devices among the ageing population. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Vol. 10921 LNCS. Springer International Publishing. https://doi.org/10.1007/978-3-319-91125-0_25
Yadav, N., Jin, Y., & Stevano, L. J. (2019). AR-IoMT Mental Health Rehabilitation Applications for Smart Cities. HONET-ICT 2019 - IEEE 16th International Conference on Smart Cities: Improving Quality of Life Using ICT, IoT and AI, 166–170. https://doi.org/10.1109/HONET.2019.8907997
Yu, H. (2020). Research and optimization of sports injury medical system under the background of Internet of things. Transactions on Emerging Telecommunications Technologies, 31(12), 1–14. https://doi.org/10.1002/ett.3929
Zanjal, S. V., & Talmale, G. R. (2016). Medicine Reminder and Monitoring System for Secure Health Using IOT. Physics Procedia, 78(December 2015), 471–476. https://doi.org/10.1016/j.procs.2016.02.090
Zilani, T. A., Al-Turjman, F., Khan, M. B., Zhao, N., & Yang, X. (2020). Monitoring movements of ataxia patient by using UWB technology. Sensors (Switzerland), 20(3), 1–16. https://doi.org/10.3390/s20030931