First Experiences With a Wearable Multisensor in an Outpatient Glucose Monitoring Study, Part I: The Users' View

Area of Science:

• Biomedical Engineering
• Endocrinology

Background:

• Noninvasive continuous glucose monitoring (CGM) using wearable Multisensor devices offers valuable glucose trend data for diabetes management.
• Previous studies demonstrated efficacy in controlled and semi-controlled environments.

Purpose of the Study:

• To evaluate the Multisensor device's performance in real-world, uncontrolled in-clinic and outpatient settings.
• To assess the feasibility of noninvasive glucose trend estimation in type 1 diabetes patients.

Main Methods:

• A long-term study collected Multisensor and reference glucose data from 20 type 1 diabetes subjects over 1072 days.
• An online-compatible algorithm processed Multisensor data for noninvasive glucose trend estimation.
• Patients maintained digital logs, performed daily data transfers, and provided frequent self-monitoring of blood glucose (SMBG) values.

Main Results:

• The Multisensor successfully indicated glucose trends in 90% of cases, with accuracy within one level of discrepancy.
• The system demonstrated the ability to detect rapid glucose increases or general increases in 9 out of 10 instances.
• The algorithm and Multisensor tracked glucose trends across all patients, irrespective of uncontrolled conditions.

Conclusions:

• The wearable Multisensor, coupled with the algorithmic routine, effectively tracks glucose trends in type 1 diabetes patients, even in uncontrolled settings.
• Patient training is crucial for optimal performance; reducing patient workload through automation is a key future direction.
• The glucose trend indication feature is highly appreciated by patients, justifying the use of wearable technology.