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This paper is in the following e-collection/theme issue:

Digital Health Reviews (3720) Web-based and Mobile Health Interventions (5877) Mobile Health (mhealth) (5216) mHealth for Wellness, Behavior Change and Prevention (4283) Wearable Devices and Sensors (1608) Machine Learning (3235) Artificial Intelligence (4853)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/40259, first published .
Person checks fitness tracker on wrist outdoors

The Effectiveness of Wearable Devices Using Artificial Intelligence for Blood Glucose Level Forecasting or Prediction: Systematic Review

The Effectiveness of Wearable Devices Using Artificial Intelligence for Blood Glucose Level Forecasting or Prediction: Systematic Review

Authors of this article:

Arfan Ahmed1 Author Orcid Image ;   Sarah Aziz1 Author Orcid Image ;   Alaa Abd-alrazaq1 Author Orcid Image ;   Faisal Farooq2 Author Orcid Image ;   Mowafa Househ3 Author Orcid Image ;   Javaid Sheikh1 Author Orcid Image
Article Authors Cited by (51) Tweetations (3) Metrics

Journals

  1. Ahmed A, Aziz S, Qidwai U, Abd-Alrazaq A, Sheikh J. Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data. Computer Methods and Programs in Biomedicine Update 2023;3:100094 View
  2. Huang Y, Ni Z, Lu Z, He X, Hu J, Li B, Ya H, Shi Y. Heterogeneous temporal representation for diabetic blood glucose prediction. Frontiers in Physiology 2023;14 View
  3. Gonzalez-Rodriguez R, Hathaway E, Coffer J, del Castillo R, Lin Y, Cui J. Gold Nanoparticles in Porous Silicon Nanotubes for Glucose Detection. Chemosensors 2024;12(4):63 View
  4. Hou H, Zhang R, Li J. Artificial intelligence in the clinical laboratory. Clinica Chimica Acta 2024;559:119724 View
  5. Becker M, Matt C. How individuals perceive and process diagnostic device errors. Journal of Decision Systems 2024:1 View
  6. Kaladharan S, Manayath D, Gopalakrishnan R. Regulatory Challenges in AI/ML-Enabled Medical Devices: A Scoping Review and Conceptual Framework. Journal of Medical Devices 2024;18(4) View
  7. Yammouri G, Ait Lahcen A. AI-Reinforced Wearable Sensors and Intelligent Point-of-Care Tests. Journal of Personalized Medicine 2024;14(11):1088 View
  8. Morawski R. Teaching measurement science and technology in the times of pervasive AI. Measurement: Sensors 2025;38:101315 View
  9. Piao C, Zhu T, Baldeweg S, Taylor P, Georgiou P, Sun J, Wang J, Li K. GARNN: An interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series. Neural Networks 2025;185:107229 View
  10. Du Z, Zhang F, Ge Y, Liu Y, Yu H, Wang Y, Dalan R, Shen X. Application of Wearable Devices in Diabetes Management. Health and Metabolism 2025:7 View
  11. Truong Duc P, Toan V. Wearable Fall Detection Device for Stroke Warning Based on IoT Technology and Convolutional Neural Network. Measurement: Interdisciplinary Research and Perspectives 2026;24(2):120 View
  12. El-Helaly M. Artificial Intelligence and Occupational Health and Safety, Benefits and Drawbacks. La Medicina del Lavoro 2024;115(2):e2024014 View
  13. Taherdoost H. Wearable Healthcare and Continuous Vital Sign Monitoring with IoT Integration. Computers, Materials & Continua 2024;81(1):79 View
  14. Martins O, Oosthuizen C, Desai D. Exploring the import of mechatronics engineering in medicine: a review. Beni-Suef University Journal of Basic and Applied Sciences 2025;14(1) View
  15. Vargas-Santiago M, León-Velasco D, Maldonado-Sifuentes C, Chanona-Hernandez L. A State-of-the-Art Review of Artificial Intelligence (AI) Applications in Healthcare: Advances in Diabetes, Cancer, Epidemiology, and Mortality Prediction. Computers 2025;14(4):143 View
  16. Maheshwari S, Kalia A, Tewari J, Tewari A, Srivastava A, Dantu R, Sachan A, Verma N, Maheshwari A. Artificial intelligence for diabetes management – a review. Journal of Diabetes, Metabolic Disorders & Control 2025;12(1):24 View
  17. Pillay T, Khan A, Yenice S. Artificial intelligence (AI) in point-of-care testing. Clinica Chimica Acta 2025;574:120341 View
  18. Liu Y, Li J, Jia S, Lu Y, Shi D, Shi L. Noninvasive Glucose Monitoring With Low-Order Electrical Impedance Sensing Arrays: An Information Boosting Approach. IEEE Transactions on Instrumentation and Measurement 2025;74:1 View
  19. Ullah Q, Rauta T, Keskikuru J, Haverinen J, Ruuskanen P. Innovations in energy harvesting: A survey of low-power technologies and their potential. Energy Reports 2025;14:671 View
  20. Mahmood A. The Role of AI and Wearables in Injury Prediction and Performance Optimization. Premier Journal of Artificial Intelligence 2025 View
  21. Romano S, Yazdanpanah S, Conte R, De Rosa A, Fico A, Peluso G, Pedram P, Moeini A. Smart Theranostic Platforms Based on Carbohydrate Hydrogels. Macromol 2025;5(3):37 View
  22. Aviha R, Slaughter G. Electrochemical and Nanomaterial‐Based Strategies for Nonenzymatic Glucose Detection: A Review. ChemistryOpen 2025;14(11) View
  23. Kına E. Yapay zekânın multidisipliner alanlardaki uygulamaları. Türkiye Teknoloji ve Uygulamalı Bilimler Dergisi 2025;6(2):165 View
  24. Tsutsumi T, Tsuchiya K. Testosterone and Obesity in an Aging Society. Biomolecules 2025;15(11):1521 View
  25. Khatoon S, Miraj M, Mansoor V, Alam Q, Kazmi S, Rasheed F, Mannan A, Aqeel M. Different Barriers, Different Needs: A Qualitative Study on How Educational Level Shapes Barriers to Type 2 Diabetes Self-Management in Urban Pakistan. Cureus 2025 View
  26. Uçar Z, Çiçek B. Estimation of daily energy requirements using a hybrid artificial intelligence model. Scientific Reports 2025;15(1) View
  27. Fraser R, Walker R, Campbell J, Ekwunife O, Egede L. Integration of artificial intelligence and wearable technology in the management of diabetes and prediabetes. npj Digital Medicine 2025;8(1) View
  28. CARLUCCI F, TABUCCHI A, FIORINI M, GALASSO L, TERRENI A. Dispositivi indossabili per la gestione del diabete. Biochimica Clinica 2025;49(4) View
  29. Shah S, Kaleem A, Huang C, Ali M. Enhancing healthcare efficiency through AI-driven hospital information systems: the roles of perceived value and digital leadership. Behaviour & Information Technology 2026;45(12):2947 View
  30. Lu Z, Zhou T, Hu C, Xu C, Zhang S, Zhang B. Noninvasive blood glucose level estimation using bioimpedance spectroscopy and machine learning: an integrated optimization approach. Medical Engineering & Physics 2026;147(2):025010 View
  31. Bilal A, Thabit H, Nutter P, Harper S. Temporal gradient analysis of blood glucose responses to non-standard physical activity: a free-living study in type 1 diabetes. Frontiers in Sports and Active Living 2026;8 View
  32. Melo P. Prediction Modeling: Basic Metabolic Panel. Advances in Bioscience and Biotechnology 2025;16(09):360 View
  33. Wen S, Li H, Sun X. A physiologically inspired dual-stream decoupled interaction fusion architecture for effective utilization of multimodal data in blood glucose prediction. Biomedical Signal Processing and Control 2026;120:110203 View
  34. Cui B, van Beijnum B, Tabak M, Wang Y. Sensor-Based Monitoring of Knee Osteoarthritis Symptoms in Free-Living Settings: A Scoping Review (Preprint). Journal of Medical Internet Research 2025 View
  35. Khan S, Shah S. When AI heals the healers: AI adoption and explainability drive service innovation and reduce emotional exhaustion. Journal of Health Organization and Management 2026:1 View
  36. Wu J, Chen B, Chan K, Liang M, Lyu Y, Yu P, Feng T, Xie F, Yu S, Zhang F, Yip T, Kang W. Harnessing artificial intelligence for pediatric health: Current trends and future opportunities. iScience 2026;29(6):115962 View
  37. Ahmad Razimi U, Yong Y, Mohd Ariffin N, Alkawaz M. AI-Powered Continuous Health Monitoring for Chronic Disease Management in Malaysia: Real-Time Risk Prediction Using Wearable Sensors and Digital Biomarkers. Journal of Informatics and Web Engineering 2026;5(2):361 View
  38. Bali B, Iliya Kwaha F. AI-Powered Wearable Devices for Real-Time Health Monitoring: Technologies, Challenges, and Emerging Trends. Journal of Engineering Advancements 2026;7(02):46 View
  39. Sood T, Kumar P, Jasrotia R, Suman , Kandwal A. Electromagnetic Metasurface-Enabled RF sensing for accurate Non-Invasive glucose Measurements: Recent advances review. Measurement 2026;290:122889 View

Books/Policy Documents

  1. Longo I, D’Antoni F, Petrosino L, Piemonte V, Merone M, Pecchia L. 9th European Medical and Biological Engineering Conference. View
  2. Patel D, Dey A. Digital Health. View
  3. Jayaraman S, Anithamary M, Murugesh K, Dinesh K. Exploring the Intricacies of Digital and Analog VLSI. View
  4. Bhimavarapu U. AI-Powered Systems for Healthcare Diagnostics and Treatment. View
  5. Manoj Babu P, Venkata Subbaiah P. Industry 5.0. View

Conference Proceedings

  1. Glumčević S, Mašetić Z, Viteškić B. 2023 46th MIPRO ICT and Electronics Convention (MIPRO). Closed-loop Artificial Pancreas Development: A Review View
  2. Yong C, Moi J. 2024 7th International Conference on Electronics, Communications, and Control Engineering (ICECC). Health Gadget – An IoT Handheld Sugar Level Detector View
  3. Baroud S. 2025 International Conference on Metaverse and Current Trends in Computing (ICMCTC). AI-Powered Multi-Agent System for Type 2 Diabetes Care: IoT, Federated Learning and Mobile Health Integration View
  4. Magdum A, Harpude P, Nehete P, Erande A, Wahane Y. 2025 9th International Conference on Computing, Communication, Control and Automation (ICCCBEA). Design of a Wearable Device for Real-Time Carbohydrate Intake Monitoring Using Machine Learning View
  5. A L, K A. 2025 7th International Conference on Innovative Data Communication Technologies and Application (ICIDCA). An IoT-Enabled Dual Feature Extraction Network for Breath-based Glucose Prediction using ARIMA and Depth-Wise Separable Transformer View
  6. Acharya D, Raj A, Leo L, Adamsab K. 2025 International Conference on Intelligent Systems and Pioneering Innovations in Robotics and Electric Mobility (INSPIRE). Smart AI-Integrated Wearable for Early Detection of Diabetic Foot Ulcers Using Sensors View
  7. Nandi S, Atal J, Rajak A, Anand A, Saha A, Raj A. 2026 Fifth International Conference on Power, Control and Computing Technologies (ICPC2T). IoT Driven Non Invasive Diagnostic System for Early Diabetes Risk Assessment in Personalized Healthcare View