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المؤلفAziz, Sarah
المؤلفAhmed, Arfan
المؤلفAbd-Alrazaq, Alaa
المؤلفQidwai, Uvais
المؤلفFarooq, Faisal
المؤلفSheikh, Javaid
تاريخ الإتاحة2024-05-07T05:39:55Z
تاريخ النشر2023
اسم المنشورStudies in Health Technology and Informatics
المصدرScopus
المعرّفhttp://dx.doi.org/10.3233/SHTI230484
الرقم المعياري الدولي للكتاب9269630
معرّف المصادر الموحدhttp://hdl.handle.net/10576/54653
الملخصIn 2019 alone, Diabetes Mellitus impacted 463 million individuals worldwide. Blood glucose levels (BGL) are often monitored via invasive techniques as part of routine protocols. Recently, AI-based approaches have shown the ability to predict BGL using data acquired by non-invasive Wearable Devices (WDs), therefore improving diabetes monitoring and treatment. It is crucial to study the relationships between non-invasive WD features and markers of glycemic health. Therefore, this study aimed to investigate accuracy of linear and non-linear models in estimating BGL. A dataset containing digital metrics as well as diabetic status collected using traditional means was used. Data consisted of 13 participants data collected from WDs, these participants were divided in two groups young, and Adult Our experimental design included Data Collection, Feature Engineering, ML model selection/development, and reporting evaluation of metrics. The study showed that linear and non-linear models both have high accuracy in estimating BGL using WD data (RMSE range: 0.181 to 0.271, MAE range: 0.093 to 0.142). We provide further evidence of the feasibility of using commercially available WDs for the purpose of BGL estimation amongst diabetics when using Machine learning approaches.
راعي المشروعThe dataset used in this study was provided by Deepali Pankaj Javale from MIT World Peace University, Pune, India
اللغةen
الناشرIOS Press BV
الموضوعArtificial Intelligence
Blood glucose level
Deep learning
Diabetes
Machine learning
Wearable devices
العنوانEstimating Blood Glucose Levels Using Machine Learning Models with Non-Invasive Wearable Device Data
النوعConference Paper
الصفحات283-286
رقم المجلد305


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