Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review
Abstract
:1. Introduction
2. Glucose Dynamic during Sensor-Monitored Physical Exercise
3. Sensors Estimating Glucose Level Based on Physical Activity Signals
4. Integration of Sensors-Based Physiological Parameters with CGM Data
5. Integration of Sensors-Based Physiological Parameters with NI-CGM
6. Conclusions
Acknowledgments
Conflicts of Interest
Abbreviations
CGM | Continuous Glucose Monitoring |
ECG | Electrocardiogram |
HbA1c | Glycated hemoglobin |
HL7 | Health Level 7 |
HR | Heart Rate |
HRV | Heart Rate Variability |
ICT | Information and Communication Technology |
MGMS | Multisensor Glucose Monitoring System |
NI-CGM | Non-Invasive Continuous Glucose Monitoring |
PAMS | Physical Activity Monitoring System |
SWA | SenseWear® Pro Armband |
T1DM | Type 1 diabetes mellitus |
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General Purpose | Product | Company | Sensors | Specific Use in the Articles |
---|---|---|---|---|
Monitoring glucose dynamic during physical exercise | Physical Activity Monitoring System (PAMS) | Crossbow Technology, San Jose, CA, USA | -2 tri-axial accelerometers (CXL02LF3-R) | Evaluation of glucose dynamic during physical exercise [24,40] |
-4 inclinometers (CXTA02) | ||||
Physiological signals to estimate glucose level | BodyMedia SenseWear® Pro Armband | SWA; BodyMedia, Inc, Pittsburgh, PA, USA | -A 2-axis accelerometer | Direct estimation of glucose level based on multisensor data [41] |
-Heat-flux sensor | ||||
-Thermistors | ||||
-Galvanic skin response sensor | ||||
-ECG electrodes | ||||
Vital signals and CGM | Zephyr BioHarnessTM 3 | Zephyr Technology, Annapolis, MD, USA | -Heart rate -A 3-axis accelerometer | Integration of heart rate and accelerometer monitoring in the glucose level estimation algorithm [42] |
Integration of accelerometer monitoring in the glucose level estimation algorithm [43] | ||||
Sport Watch: Polar: model RS800CX | Polar®, Lake Success, NY, USA | -Heart rate | Integration of heart rate monitoring in the glucose level estimation algorithm [44] | |
Digital Holter monitor, SpiderView Plus | ELA Medical, Montrouge, France | -ECG monitor | Integration of heart rate variability in the glucose level estimation algorithm [45,46] | |
BodyMedia SenseWear® Pro3 Armband | SWA; BodyMedia, Inc, Pittsburgh, PA, USA | -A 2-axis accelerometer | Integration of energy expenditure and galvanic skin response in a glucose level estimation algorithm [47,48] | |
-Heat-flux sensor | ||||
-Thermistors | ||||
-Galvanic skin response sensor | ||||
-ECG electrodes | ||||
Physical activity and NI-CGM | Multisensor Glucose Monitoring System (MGMS) | Solianis Monitoring AG , Zurich, Switzerland | -Accelerometer | Integration of temperature, sweat and acceleration and position in the glucose level estimation algorithm [23,49,50,51] |
-Temperature sensor | ||||
-Humidity sensor | ||||
-Optical sensor | ||||
-Dielectric spectroscopy (for glucose monitoring) | ||||
SensiumVitals | Sensium Healthcare Ltd, London, UK | -Heart rate | Reliability of the cardiac and respiratory rates estimates [52] | |
-Respiratory rate | ||||
-Physical activity | ||||
-Blood pH | ||||
-Glucose level |
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Ding, S.; Schumacher, M. Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review. Sensors 2016, 16, 589. https://doi.org/10.3390/s16040589
Ding S, Schumacher M. Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review. Sensors. 2016; 16(4):589. https://doi.org/10.3390/s16040589
Chicago/Turabian StyleDing, Sandrine, and Michael Schumacher. 2016. "Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review" Sensors 16, no. 4: 589. https://doi.org/10.3390/s16040589
APA StyleDing, S., & Schumacher, M. (2016). Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review. Sensors, 16(4), 589. https://doi.org/10.3390/s16040589