Blood Glucose Monitoring
Conditions
Keywords
Non-invasive monitoring, Photoplethysmography (PPG), Machine learning, Medical devices, glucose
Brief summary
The goal of this observational study is to evaluate the performance of a novel, non-invasive sensor device based on zirconium oxide photodetector designed to monitor key physiological parameters: blood glucose levels, heart rate, and blood oxygen saturation. The study focuses on adult hospital patients aged 18 to 75, of all sexes, who are undergoing routine monitoring and treatment unrelated to the investigational device. The main questions this study aims to answer are: To what extent do the signals obtained from the newly developed device correlate with standard hospital-based methods for measuring blood glucose, heart rate, and blood oxygen saturation? Is the device feasible, safe, and accurate for use in a real-world clinical setting? How stable and reproducible are the sensor signals across a demographically diverse patient population? Can advanced data analysis methods, such as machine learning techniques, be used effectively to interpret the device's output and provide accurate estimates of glucose concentration? What is the user perception of comfort, safety, and practicality when the device is used in a routine hospital environment? This study will not assign any interventions to participants; it is purely observational. The novel device is non-invasive, and its use will not interfere with standard clinical care. Measurements will be taken passively or concurrently with routine care procedures. Participants will: Continue to receive standard clinical care, including conventional monitoring of glucose, heart rate, and oxygen saturation. Undergo additional measurements using the investigational device, which will be placed non-invasively on the skin (finger). Answer a short usability questionnaire assessing their experience with the device, including any discomfort, perceived safety, or ease of use. Data obtained from the device will be compared with routine clinical data from standard hospital devices (e.g., glucometers, pulse oximeters) to evaluate accuracy and reliability. No pharmacological, radiological, or invasive procedures will be involved.
Interventions
None listed
Sponsors
T. Marciniak Lower Silesian Specialist Hospital in Wrocław
Wrocław University of Science and Technology
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No
Inclusion criteria
* Adults aged 18-75 years * Able to provide informed consent
Exclusion criteria
* Skin diseases or injuries on the fingers (e.g., psoriasis, open wounds, burns) * Tattoos on the fingers * Severe peripheral circulation disorders * Pregnancy * Presence of active implantable medical devices (e.g., pacemakers)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Evaluation of a Non-Invasive Device for Measuring Blood Glucose, Heart Rate, and Oxygen Saturation | 8 months | To evaluate the correlation between the signals obtained from the newly developed non-invasive device and standard hospital-based methods for measuring blood glucose levels, heart rate, and blood oxygen saturation. The primary aim is to assess the feasibility, signal stability, and potential accuracy of the investigational device in a clinical setting. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| User-friendliness and Practical Usability of the Device in Routine Hospital Procedures | 8 months | Usability of the device will be assessed using a standardized questionnaire (e.g., System Usability Scale, SUS) completed by clinical staff after performing routine procedures with the device. Additional measures will include the average time (in minutes) required to complete the procedure and the number of use-related errors observed per procedure, recorded by a trained observer. |
| Variability of Device Readings Across a Demographically Diverse Adult Population | 8 months | The device's output readings-heart rate (beats per minute), oxygen saturation (%SpO₂), and glucose levels (mg/dL)-will be collected from adult participants aged 18-75, balanced by sex. For each physiological parameter, variability will be assessed using standard deviation and coefficient of variation across repeated measurements. Device readings will be compared to reference standard measurements performed during the patients' routine hospital stay (e.g., laboratory tests) to evaluate consistency. |
| Applying Machine Learning to Interpret Non-Invasive PPG Signals for Glucose Estimation | 12 months | To apply and evaluate machine learning techniques for the interpretation of non-invasive PPG signals, in order to estimate glucose levels and benchmark the performance of the sensor platform |
Countries
Poland
Outcome results
None listed