Application of mHealth Technologies to Improve Self-Control of Children and Adolescents with Type 1 Diabetes

N. Zholdas, M. Mansurova, Magzhan Sarsembayev, O. Postolache, A. Shomanov, T. Sarsembayeva
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Abstract

Our research has shown that the use of mobile technologies (mHealth) to improve self-control of children and adolescents with diabetes, as well as for parental control, gives positive results. A functional implemented in a mobile application has been developed that contains recommendations from endocrinologists based on the analysis of data from sensors, taking into account the individual characteristics of the patient's body. Digital health profiles of patients with diabetes mellitus, containing the values of state indicators obtained from various sensors, mobile phones, medical watches and fitness bracelets, make it possible to develop systems for monitoring and supporting personalized decision-making. By observing a patient's digital profile, clinicians can determine some of the possible causes of deviations in glucose readings in predetermined time segments. During the project, under the close supervision of endocrinologists and a pediatrician, patient data were collected, such as continuous monitoring glucose sensor values, fitness bracelet records, anthropometric data, disease and family history data, eating behavior data, HbAl c (glycated hemoglobin) level data in beginning and end of the study to assess carbohydrate metabolism compensation, FA (fructosamine) level data twice during the study period in order to short-term assess the degree of carbohydrate metabolism compensation, general blood analysis and general urine analysis data in order to additionally assess the reliability of previous tests for data analysis.
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应用移动健康技术提高1型糖尿病儿童和青少年自我控制能力
我们的研究表明,使用移动技术(移动健康)来提高患有糖尿病的儿童和青少年的自我控制能力,以及父母的控制,产生了积极的结果。在移动应用程序中实现了一个功能,该功能包含内分泌学家基于传感器数据分析的建议,并考虑到患者身体的个体特征。糖尿病患者的数字健康概况,包含从各种传感器、移动电话、医疗手表和健身手环获得的状态指标值,使开发监测和支持个性化决策的系统成为可能。通过观察患者的数字档案,临床医生可以确定在预定时间段内血糖读数偏差的一些可能原因。项目期间,在内分泌科医生和儿科医生的密切监督下,收集患者数据,如持续监测血糖传感器值、健身手环记录、人体测量数据、疾病和家族史数据、饮食行为数据、研究开始和结束时的HbAl c(糖化血红蛋白)水平数据,以评估碳水化合物代谢代偿。研究期间两次FA(果糖胺)水平数据,以短期评估碳水化合物代谢代偿程度,一般血液分析和一般尿液分析数据,以额外评估以往测试数据分析的可靠性。
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