ReviewSensors (Basel, Switzerland)2016
Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review.
Review in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04946188 (Non-invasive Monitoring to Translate the Biometric Data of Participants With Diabetes Into Blood Glucose Levels), which is not on this map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Non-invasive Monitoring to Translate the Biometric Data of Participants With Diabetes Into Blood Glucose Levels
Who cites it
18 citing papers in PubMed.
- The Impact of a Multidimensional Physical Activity Intervention on Glycemic Control in Type 1 Diabetes: A Preliminary Study.Journal of functional morphology and kinesiology · 2025Article
- A Nanotechnology-Based Approach to Biosensor Application in Current Diabetes Management Practices.Nanomaterials (Basel, Switzerland) · 2023Review
- Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection.Frontiers in bioengineering and biotechnology · 2022Review
- Review of Wearable Sensor-Based Health Monitoring Glove Devices for Rheumatoid Arthritis.Sensors (Basel, Switzerland) · 2021Review
- Determining Physical Activity Characteristics from Wristband Data for Use in Automated Insulin Delivery Systems.IEEE sensors journal · 2020Article
- Positive and Negative Evidence Accumulation Clustering for Sensor Fusion: An Application to Heartbeat Clustering.Sensors (Basel, Switzerland) · 2019Article
- Enhanced Accuracy of Continuous Glucose Monitoring during Exercise through Physical Activity Tracking Integration.Sensors (Basel, Switzerland) · 2019Article
- 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 (Basel, Switzerland) · 2019Article
- Applications of stem cells and bioprinting for potential treatment of diabetes.World journal of stem cells · 2019Review
- Different Types of Physical Activity and Metabolic Control in People With Type 1 Diabetes Mellitus.Frontiers in physiology · 2019Article
- Continuous Movement Monitoring of Daily Living Activities for Prevention of Diabetic Foot Ulcer: A Review of Literature.International journal of preventive medicine · 2019Review
- The Promise and Perils of Wearable Physiological Sensors for Diabetes Management.Journal of diabetes science and technology · 2018Article
- First Experiences With a Wearable Multisensor in an Outpatient Glucose Monitoring Study, Part I: The Users' View.Journal of diabetes science and technology · 2018Article
- Variables to Be Monitored via Biomedical Sensors for Complete Type 1 Diabetes Mellitus Management: An Extension of the "On-Board" Concept.Journal of diabetes research · 2018Review
- Flash glucose monitoring system may benefit children and adolescents with type 1 diabetes during fasting at Ramadan.Saudi medical journal · 2017Article
- Use of Wearable Sensors and Biometric Variables in an Artificial Pancreas System.Sensors (Basel, Switzerland) · 2017Article
- Recent Progress in Electrochemical Biosensors for Glycoproteins.Sensors (Basel, Switzerland) · 2016Review
- A Human Serum-Based Enzyme-Free Continuous Glucose Monitoring Technique Using a Needle-Type Bio-Layer Interference Sensor.Sensors (Basel, Switzerland) · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic individuals need to tightly control their blood glucose concentration. Several methods have been developed for this purpose, such as the finger-prick or continuous glucose monitoring systems (CGMs). However, these methods present the disadvantage of being invasive. Moreover, CGMs have limited accuracy, notably to detect hypoglycemia. It is also known that physical exercise, and even daily activity, disrupt glucose dynamics and can generate problems with blood glucose regulation during and after exercise. In order to deal with these challenges, devices for monitoring patients' physical activity are currently under development. This review focuses on non-invasive sensors using physiological parameters related to physical exercise that were used to improve glucose monitoring in type 1 diabetes (T1DM) patients. These devices are promising for diabetes management. Indeed they permit to estimate glucose concentration either based solely on physical activity parameters or in conjunction with CGM or non-invasive CGM (NI-CGM) systems. In these last cases, the vital signals are used to modulate glucose estimations provided by the CGM and NI-CGM devices. Finally, this review indicates possible limitations of these new biosensors and outlines directions for future technologic developments.
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What OpenQuestion holds
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.