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The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System.
J Diabetes Sci Technol. 2015 Jul; 9(4):865-72.JD

Abstract

BACKGROUND

We study here the influence of different patients and the influence of different devices with the same patients on the signals and modeling of data from measurements from a noninvasive Multisensor glucose monitoring system in patients with type 1 diabetes. The Multisensor includes several sensors for biophysical monitoring of skin and underlying tissue integrated on a single substrate.

METHOD

Two Multisensors were worn simultaneously, 1 on the upper left and 1 on the upper right arm by 4 patients during 16 study visits. Glucose was administered orally to induce 2 consecutive hyperglycemic excursions. For the analysis, global (valid for a population of patients), personal (tailored to a specific patient), and device-specific multiple linear regression models were derived.

RESULTS

We find that adjustments of the model to the patients improves the performance of the glucose estimation with an MARD of 17.8% for personalized model versus a MARD of 21.1% for the global model. At the same time the effect of the measurement side is negligible. The device can equally well measure on the left or right arm. We also see that devices are equal in the linear modeling. Thus hardware calibration of the sensors is seen to be sufficient to eliminate interdevice differences in the measured signals.

CONCLUSIONS

We demonstrate that the hardware of the 2 devices worn on the left and right arms are consistent yielding similar measured signals and thus glucose estimation results with a global model. The 2 devices also return similar values of glucose errors. These errors are mainly due to nonstationarities in the measured signals that are not solved by the linear model, thus suggesting for more sophisticated modeling approaches.

Authors+Show Affiliations

Biovotion AG, Zurich, Switzerland andreas.caduff@biovotion.com.Biovotion AG, Zurich, Switzerland.Biovotion AG, Zurich, Switzerland.Biovotion AG, Zurich, Switzerland.Department of Applied Physics, Hebrew University of Jerusalem, Jerusalem, Israel.Biovotion AG, Zurich, Switzerland.Clinic for Endocrinology and Diabetes, University Hospital Basel, Basel, Switzerland.Seminar for Statistics, ETH Zurich, Zurich, Switzerland.Biovotion AG, Zurich, Switzerland.

Pub Type(s)

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

Language

eng

PubMed ID

25910542

Citation

Caduff, Andreas, et al. "The Effect of a Global, Subject, and Device-Specific Model On a Noninvasive Glucose Monitoring Multisensor System." Journal of Diabetes Science and Technology, vol. 9, no. 4, 2015, pp. 865-72.
Caduff A, Zanon M, Mueller M, et al. The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System. J Diabetes Sci Technol. 2015;9(4):865-72.
Caduff, A., Zanon, M., Mueller, M., Zakharov, P., Feldman, Y., De Feo, O., Donath, M., Stahel, W. A., & Talary, M. S. (2015). The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System. Journal of Diabetes Science and Technology, 9(4), 865-72. https://doi.org/10.1177/1932296815579459
Caduff A, et al. The Effect of a Global, Subject, and Device-Specific Model On a Noninvasive Glucose Monitoring Multisensor System. J Diabetes Sci Technol. 2015;9(4):865-72. PubMed PMID: 25910542.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - The Effect of a Global, Subject, and Device-Specific Model on a Noninvasive Glucose Monitoring Multisensor System. AU - Caduff,Andreas, AU - Zanon,Mattia, AU - Mueller,Martin, AU - Zakharov,Pavel, AU - Feldman,Yuri, AU - De Feo,Oscar, AU - Donath,Marc, AU - Stahel,Werner A, AU - Talary,Mark S, Y1 - 2015/04/24/ PY - 2015/4/26/entrez PY - 2015/4/26/pubmed PY - 2016/5/18/medline KW - algorithm KW - diabetes KW - electromagnetic KW - optical KW - perturbations KW - wearable device SP - 865 EP - 72 JF - Journal of diabetes science and technology JO - J Diabetes Sci Technol VL - 9 IS - 4 N2 - BACKGROUND: We study here the influence of different patients and the influence of different devices with the same patients on the signals and modeling of data from measurements from a noninvasive Multisensor glucose monitoring system in patients with type 1 diabetes. The Multisensor includes several sensors for biophysical monitoring of skin and underlying tissue integrated on a single substrate. METHOD: Two Multisensors were worn simultaneously, 1 on the upper left and 1 on the upper right arm by 4 patients during 16 study visits. Glucose was administered orally to induce 2 consecutive hyperglycemic excursions. For the analysis, global (valid for a population of patients), personal (tailored to a specific patient), and device-specific multiple linear regression models were derived. RESULTS: We find that adjustments of the model to the patients improves the performance of the glucose estimation with an MARD of 17.8% for personalized model versus a MARD of 21.1% for the global model. At the same time the effect of the measurement side is negligible. The device can equally well measure on the left or right arm. We also see that devices are equal in the linear modeling. Thus hardware calibration of the sensors is seen to be sufficient to eliminate interdevice differences in the measured signals. CONCLUSIONS: We demonstrate that the hardware of the 2 devices worn on the left and right arms are consistent yielding similar measured signals and thus glucose estimation results with a global model. The 2 devices also return similar values of glucose errors. These errors are mainly due to nonstationarities in the measured signals that are not solved by the linear model, thus suggesting for more sophisticated modeling approaches. SN - 1932-2968 UR - https://www.unboundmedicine.com/medline/citation/25910542/The_Effect_of_a_Global_Subject_and_Device_Specific_Model_on_a_Noninvasive_Glucose_Monitoring_Multisensor_System_ L2 - https://journals.sagepub.com/doi/10.1177/1932296815579459?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub=pubmed DB - PRIME DP - Unbound Medicine ER -