ReviewFrontiers in bioengineering and biotechnology2022
Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection.
Review in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 53 citations in OpenAlex.
- Advances in Electrocardiogram-Based Non-Invasive Blood Glucose Monitoring Technology.Diabetes, obesity & metabolism · 2026Review
- Secure IoMT smartwatch-based blood glucose monitoring using multimodal activity and nutrition data with transfer learning.Scientific reports · 2026Article
- Hypoglycaemia and Cardiac Arrhythmias in Type 1 Diabetes Mellitus: A Mechanistic Review.Journal of personalized medicine · 2026Review
- Review
- Wearable biosensors for pediatric hospitals: a scoping review.Pediatric research · 2025Article
- A Deep Sparse Capsule Network for Non-Invasive Blood Glucose Level Estimation Using a PPG Sensor.Sensors (Basel, Switzerland) · 2025Article
- Anomaly detection in medical via multimodal foundation models.Frontiers in bioengineering and biotechnology · 2025Article
- Virtual Care Appointments and Experience Among Older Rural Patients with Chronic Conditions in New South Wales: An Analysis of Existing Survey Data.International journal of environmental research and public health · 2024Article
- AI-Based Noninvasive Blood Glucose Monitoring: Scoping Review.Journal of medical Internet research · 2024Article
- Strategies to Enrich Electrochemical Sensing Data with Analytical Relevance for Machine Learning Applications: A Focused Review.Sensors (Basel, Switzerland) · 2024Review
- Unraveling the dual threat: sarcopenia and insufficient physical activity in diabetes risk.Frontiers in endocrinology · 2024Article
- Non-Invasive Glucose Sensing Technologies and Products: A Comprehensive Review for Researchers and Clinicians.Sensors (Basel, Switzerland) · 2023Review
- Longitudinal Studies of Wearables in Patients with Diabetes: Key Issues and Solutions.Sensors (Basel, Switzerland) · 2023Article
- Hypoglycemia Detection Using Hand Tremors: Home Study of Patients With Type 1 Diabetes.JMIR diabetes · 2023Article
- A Focused Review on the Flexible Wearable Sensors for Sports: From Kinematics to Physiologies.Micromachines · 2022Review
- Wearable Technologies for Pediatric Patients with Surgical Infections-More than Counting Steps?Biosensors · 2022Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetes mellitus is characterized by elevated blood glucose levels, however patients with diabetes may also develop hypoglycemia due to treatment. There is an increasing demand for non-invasive blood glucose monitoring and trends detection amongst people with diabetes and healthy individuals, especially athletes. Wearable devices and non-invasive sensors for blood glucose monitoring have witnessed considerable advances. This review is an update on recent contributions utilizing novel sensing technologies over the past five years which include electrocardiogram, electromagnetic, bioimpedance, photoplethysmography, and acceleration measures as well as bodily fluid glucose sensors to monitor glucose and trend detection. We also review methods that use machine learning algorithms to predict blood glucose trends, especially for high risk events such as hypoglycemia. Convolutional and recurrent neural networks, support vector machines, and decision trees are examples of such machine learning algorithms. Finally, we address the key limitations and challenges of these studies and provide recommendations for future work.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.