A Personalized mHealth Monitoring System for Children and Adolescents with T1 Diabetes by Utilizing IoT Sensors and Assessing Physical Activities

Authors

  • Nurassyl Zholdas Al-Farabi Kazakh National University, Almaty, Kazakhstan
  • Madina Mansurova Al-Farabi Kazakh National University, Almaty, Kazakhstan
  • Octavian Postolache Iscte-Instituto Universití¡rio de Lisboa, Lisboa, Portugal
  • Maksat Kalimoldayev Institute of Information and Computational Technologies, Almaty, Kazakhstan
  • Talshyn Sarsembayeva Al-Farabi Kazakh National University, Almaty, Kazakhstan

DOI:

https://doi.org/10.15837/ijccc.2022.3.4558

Keywords:

mHealth, monitoring system, IoT sensors, children and adolescents with T1 diabetes, glucose level

Abstract

The problem of diabetes mellitus is becoming alarming due to the increase in morbidity among children. Patients are undergoing vital insulin replacement therapy, the dose depends on the level of glucose in the blood. The glucose level prediction program, taking into account the impact of physical activity on the body, the use of mobile health capabilities will allow us to develop personalized tactics for a child patient and minimize the risks of a critical health condition. The target group of this study are children and adolescents with type 1 diabetes. This study provides an IoT based mHealth monitoring system, including sensors, medical bracelets, mobile devices with applications. The mobile healthcare application for personalized monitoring can implement the functions of more effectively targeting young users to support their own health and improve the quality of life. In addition to monitoring blood glucose levels, the effect of physical activity on the condition of patients is also taken into account. The use of the proposed method for calculating the probable change in the patient’s blood glucose level after the end of physical activity will allow the doctor to make individual recommendations for the diet before the start of physical activity and its intensity.

References

[1] Alfian, G.; Syafrudin, M., Ijaz, M.F., Syaekhoni, M.A., Fitriyani, N.L., Rhee, J. (2018). A Personalized Healthcare Monitoring System for Diabetic Patients by Utilizing BLE-Based Sensors and Real-Time Data Processing, Sensors, 18(7), 2183, 2018. https://doi.org/10.3390/s18072183

[2] Blake, H.; Roberts, A., Roberts A., Stanulewicz N., Stanulewicz N. (2015). Telemedicine and mHealth Interventions for Children and Young People with Type One Diabetes (T1DM), International Journal of Diabetes and Endocrinology, 1(1), 100-104, 2015.

[3] Bruen, D.; Delaney, C., Florea, L., Diamond, D. (2017). Glucose sensing for diabetes monitoring: Recent developments, Sensors, 17, 1866, 2017. https://doi.org/10.3390/s17081866

[4] Cafazzo, J.A.; Casselman, M., Hamming, N., Katzman, D.K., Palmert, M.R. (2012). Design of an mHealth App for the Self-management of Adolescent Type 1 Diabetes: A Pilot Study, J. Med Internet Res., 14(3), e70, 2012. https://doi.org/10.2196/jmir.2058

[5] Carter, A.; Liddle, J., Hall, W., Chenery, H. (2015). Mobile phones in research and treatment: ethical guidelines and future directions, JMIR Mhealth Uhealth, 3(4), e95, 2015. https://doi.org/10.2196/mhealth.4538

[6] Davie, R.; Panting, C., Charlton, T. (2004). Mobile phone ownership and usage among preadolescents, Telematics and Informatics, 21(4), 359-373, 2004. https://doi.org/10.1016/j.tele.2004.04.001

[7] Fernández-Caramés, T.M.; Froiz-Mí­guez, I., Blanco-Novoa, O., Fraga-Lamas, P. (2019). Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care, Sensors, 19, 3319, 2019. https://doi.org/10.3390/s19153319

[8] Fraga-Lamas, P.; Fernández-Caramés, T.M., Noceda-Davila, D., Dí­az-Bouza, M., Vilar- Montesinos, M., Pena-Agras, J.D., Castedo, L. (2017). Enabling automatic event detection for the pipe workshop of the shipyard 4.0, 56th FITCE Congress, 20-27, 2017. https://doi.org/10.1109/FITCE.2017.8093002

[9] Giménez-Pérez, G.; Recasens, A., Simó, O., Aguas, T., Suárez, A., Vila, M. (2016). Use of communication technologies by people with type 1 diabetes in the social networking era. A chance for improvement, Prim Care Diabetes, 10(2), 121-128, 2016. https://doi.org/10.1016/j.pcd.2015.09.002

[10] Holtz, B.; Mitchell, K.M., Holmstrom, A.J., Cotton, S.R., Dunneback, J.K., Jimenez-Vega, J., Ellis, D.A., Wood, M.A. (2021). An mHealth-Based Intervention for Adolescents With Type 1 Diabetes and Their Parents: Pilot Feasibility and Efficacy Single-Arm Study, JMIR Mhealth Uhealth, 9(9), e23916, 2021. https://doi.org/10.2196/23916

[11] Mitchell, K.M.; Holtz, B.E., McCarroll, A. (2019). Patient-Centered Methods for Designing and Developing Health Information Communication Technologies: A Systematic Review, Telemed J. E Health, 25(11), 1012-1021, 2019. https://doi.org/10.1089/tmj.2018.0236

[12] Monteiro-Guerra, F.; Rivera, O., Fernandez-Luque, L., Caulfield, B. (2019). Personalization in Real-Time Physical Activity Coaching Using Mobile Applications: A Scoping Review, IEEE Journal of Biomedical and Health Informatics, 1, 2019.

[13] Oddershede, A.M.; Cordova, F.M., Carrasco, R.A., Watkins, F.J. (2014). Decision Model for Assessing Healthcare ICT Support Implications: User Perception, International Journal of Computers Communications & Control, 9(5), 593-601, 2014. https://doi.org/10.15837/ijccc.2014.5.1278

[14] Payne, H.; Moxley, V., MacDonald, E. (2015). Health behavior theory in physical activity game apps: a content analysis, JMIR Serious Games, 3(2), e4, 2015. https://doi.org/10.2196/games.4187

[15] Rasyid, U.Al; Astika, F., Christian, A. (2016). Implementation of blood glucose levels monitoring system based on wireless body area network, IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), 1-2, 2016. https://doi.org/10.1109/ICCE-TW.2016.7521005

[16] Schiel, R.; Thomas, A., Kaps, A., Bieber, G. (2011). An Innovative Telemedical Support System to Measure Physical Activity in Children and Adolescents with Type 1 Diabetes Mellitus, Experimental and Clinical Endocrinology & Diabetes, 119 (9), 565-568, 2011. https://doi.org/10.1055/s-0031-1273747

[17] Wang, X.; Shu, W., Du, J. et al. (2019). Mobile health in the management of type 1 diabetes: a systematic review and meta-analysis, BMC Endocr Disord, 19, 21, 2019. https://doi.org/10.1186/s12902-019-0347-6

[18] Wang, Y.; Liu, Sh., Chen, R., Chen, Zh., Yuan, J., Li, Q. (2017). A Novel Classification Indicator of Type 1 and Type 2 Diabetes, China Sci. Rep., 7(1), 2017. https://doi.org/10.1038/s41598-017-17433-8

[19] Wang, Y.; Xue, H., Huang, Y., Huang, L., Zhang, D. (2017). A systematic review of application and effectiveness of mHealth interventions for obesity and diabetes treatment and selfmanagement, Adv Nutr, 8(3), 449-462, 2017. https://doi.org/10.3945/an.116.014100

[20] Wang, Y; Min J, Khuri, J., Xue, H., Xie, B., A Kaminsky, L., Cheskin, J.L. (2020). Effectiveness of Mobile Health Interventions on Diabetes and Obesity Treatment and Management: Systematic Review of Systematic Reviews, JMIR Mhealth Uhealth, 8(4), e15400, 2020. https://doi.org/10.2196/15400

[21] Yoo, E.H.; Lee, S.Y. (2010). Glucose biosensors: An overview of use in clinical practice, Sensors, 10, 4558-4576, 2010. https://doi.org/10.3390/s100504558

[22] Zhang, W.; Thurow, K., Stoll, R. (2014). A Knowledge-based Telemonitoring Platform for Application in Remote Healthcare, International Journal of Computers Communications & Control, 9(5), 644-654, 2014. https://doi.org/10.15837/ijccc.2014.5.661

[23] Zhang, W.; Thurow, K., Stoll, R. (2016). A Context-Aware mHealth System for Online Physiological Monitoring in Remote Healthcare, International Journal of Computers Communications & Control, 11(1), 142-156, 2016. https://doi.org/10.15837/ijccc.2016.1.1333

[24] Zholdas, N.; Postolache, O., Mansurova, M. (2021). Health Monitoring System Using Internet of Things, IEEE International Conference on Smart Information Systems and Technologies (SIST), 2021. https://doi.org/10.1109/SIST50301.2021.9465928

[25] American Diabetes Association (2018). Introduction: Standards of medical care in diabetes, Diabetes Care, 41 (Suppl. 1), S1-S2, 2018. https://doi.org/10.2337/dc18-Sint01

[26] [Online]. How Children With Type 1 Diabetes Can Exercise Safely, https://www.kidshealth.org.nz/how-children-type-1-diabetes-can-exercise-safely

[27] [Online]. International Telecommunication Union (ITU), The World in 2016: ICT Facts and Figures, https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2016.pdf. 2016.

[28] [Online]. Physical activity and your child, https://www.diabetes.org.uk/guide-to-diabetes/yourchild- and-diabetes/physical-activity, 2021.

[29] [Online]. Physical Activity for Children with Type 1 Diabetes, https://www.endocrineweb.com/guides/type-1-children/physical-activity-children-type-1- diabetes, 2021.

Additional Files

Published

2022-04-15

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.