Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.
Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.
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DOI：
10.3390/s17061361
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发表时间：
2017-06-12
期刊：
影响因子：
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通讯作者：
Vehi J
中科院分区：
文献类型：
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作者：
Biagi L;Ramkissoon CM;Facchinetti A;Leal Y;Vehi J
由于时间滞后、传感器漂移、校准误差和测量噪声，连续血糖监测仪（cgm）容易出现不准确。本研究的目的是推导第二代美敦力范式Veo Enlite （ENL）传感器的误差模型，并将其与Dexcom SEVEN PLUS （7P）、G4 PLATINUM （G4P）和advanced G4用于人工胰腺研究（G4AP）系统进行比较。一种增强的方法，以前采用的技术被用来剖析传感器误差成几个组成部分。使用的数据集包括10名1型糖尿病（T1D）患者的37次住院治疗，其中cgm平行佩戴，每15±5分钟分析一次血糖（BG）样本，ENL传感器的校准误差和传感器漂移最好用增益和偏移相关的线性关系来描述。模型估计的平均滞后时间为9.4±6.5 min。ENL传感器的总体平均绝对相对差（MARD）为11.68±5.07%，校准误差对ENL传感器总误差的贡献最大。这在7P、G4P和G4AP中也有报道。ENL传感器的误差模型将有助于测试基于cgm的应用，即使用这种传感器的人工胰腺的硅性能。
Continuous glucose monitors (CGMs) are prone to inaccuracy due to time lags, sensor drift, calibration errors, and measurement noise. The aim of this study is to derive the model of the error of the second generation Medtronic Paradigm Veo Enlite (ENL) sensor and compare it with the Dexcom SEVEN PLUS (7P), G4 PLATINUM (G4P), and advanced G4 for Artificial Pancreas studies (G4AP) systems. An enhanced methodology to a previously employed technique was utilized to dissect the sensor error into several components. The dataset used included 37 inpatient sessions in 10 subjects with type 1 diabetes (T1D), in which CGMs were worn in parallel and blood glucose (BG) samples were analyzed every 15 ± 5 min Calibration error and sensor drift of the ENL sensor was best described by a linear relationship related to the gain and offset. The mean time lag estimated by the model is 9.4 ± 6.5 min. The overall average mean absolute relative difference (MARD) of the ENL sensor was 11.68 ± 5.07% Calibration error had the highest contribution to total error in the ENL sensor. This was also reported in the 7P, G4P, and G4AP. The model of the ENL sensor error will be useful to test the in silico performance of CGM-based applications, i.e., the artificial pancreas, employing this kind of sensor.