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First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View.
J Diabetes Sci Technol. 2018 05; 12(3):554-561.JD

Abstract

BACKGROUND

Extensive past work showed that noninvasive continuous glucose monitoring with a wearable multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions.

METHOD

To test previous findings also in uncontrolled conditions, a long term at home study has been organized to collect multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking multisensor data to glucose applied to estimate glucose levels noninvasively.

RESULTS

The algorithm used here calculates glucose values from sensor data and adds a constant obtained by a daily calibration. It provides point inaccuracy measured by a MARD of 35.4 mg/dL on test data. This is higher than current state-of-the-art minimally invasive devices, but still 86.9% of glucose rate points fall within the zone AR+BR.

CONCLUSIONS

The multisensor device and the algorithmic routine used earlier in controlled conditions tracks glucose changes also in uncontrolled conditions, although with lower accuracy. The examination of learning curves suggests that obtaining more data would not improve the results. Therefore, further efforts would focus on the development of more complex algorithmic routines able to compensate for environmental and physiological confounders better.

Authors+Show Affiliations

1 Biovotion AG, Biovotion AG, Zurich, Switzerland.1 Biovotion AG, Biovotion AG, Zurich, Switzerland.1 Biovotion AG, Biovotion AG, Zurich, Switzerland.1 Biovotion AG, Biovotion AG, Zurich, Switzerland.2 Clinic for Endocrinology and Diabetes, University Hospital Basel, Basel, Switzerland.3 Seminar for Statistics, ETH Zurich, Zurich, Switzerland.1 Biovotion AG, Biovotion AG, Zurich, Switzerland.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

29145749

Citation

Zanon, Mattia, et al. "First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: the Investigators' View." Journal of Diabetes Science and Technology, vol. 12, no. 3, 2018, pp. 554-561.
Zanon M, Mueller M, Zakharov P, et al. First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View. J Diabetes Sci Technol. 2018;12(3):554-561.
Zanon, M., Mueller, M., Zakharov, P., Talary, M. S., Donath, M., Stahel, W. A., & Caduff, A. (2018). First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View. Journal of Diabetes Science and Technology, 12(3), 554-561. https://doi.org/10.1177/1932296817740591
Zanon M, et al. First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: the Investigators' View. J Diabetes Sci Technol. 2018;12(3):554-561. PubMed PMID: 29145749.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View. AU - Zanon,Mattia, AU - Mueller,Martin, AU - Zakharov,Pavel, AU - Talary,Mark S, AU - Donath,Marc, AU - Stahel,Werner A, AU - Caduff,Andreas, Y1 - 2017/11/16/ PY - 2017/11/18/pubmed PY - 2019/6/14/medline PY - 2017/11/18/entrez KW - T1DM KW - algorithm KW - diabetes KW - dielectric spectroscopy KW - multisensor SP - 554 EP - 561 JF - Journal of diabetes science and technology JO - J Diabetes Sci Technol VL - 12 IS - 3 N2 - BACKGROUND: Extensive past work showed that noninvasive continuous glucose monitoring with a wearable multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions. METHOD: To test previous findings also in uncontrolled conditions, a long term at home study has been organized to collect multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking multisensor data to glucose applied to estimate glucose levels noninvasively. RESULTS: The algorithm used here calculates glucose values from sensor data and adds a constant obtained by a daily calibration. It provides point inaccuracy measured by a MARD of 35.4 mg/dL on test data. This is higher than current state-of-the-art minimally invasive devices, but still 86.9% of glucose rate points fall within the zone AR+BR. CONCLUSIONS: The multisensor device and the algorithmic routine used earlier in controlled conditions tracks glucose changes also in uncontrolled conditions, although with lower accuracy. The examination of learning curves suggests that obtaining more data would not improve the results. Therefore, further efforts would focus on the development of more complex algorithmic routines able to compensate for environmental and physiological confounders better. SN - 1932-2968 UR - https://www.unboundmedicine.com/medline/citation/29145749/First_Experiences_With_a_Wearable_Multisensor_Device_in_a_Noninvasive_Continuous_Glucose_Monitoring_Study_at_Home_Part_II:_The_Investigators'_View_ L2 - https://journals.sagepub.com/doi/10.1177/1932296817740591?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub=pubmed DB - PRIME DP - Unbound Medicine ER -