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glucose data analysis toolbox  (MathWorks Inc)
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MathWorks Inc glucose data analysis toolbox
Figure 1. On the top, the processing pipeline that can be implemented with AGATA thanks to its functionalities. On the bottom left, the home screen of AGATA’s standalone version, which allows to easily access specific interfaces to either analyze a single/multiple <t>glucose</t> profiles or compare two groups of glucose profiles. On the bottom right, as representative use case, the dedicated GUI that allows to analyze a single glucose profile. Abbreviations: AGATA, Automated Glucose <t>dATa</t> <t>Analysis;</t> GUI, graphical user interface.
Glucose Data Analysis Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Figure 1. On the top, the processing pipeline that can be implemented with AGATA thanks to its functionalities. On the bottom left, the home screen of AGATA’s standalone version, which allows to easily access specific interfaces to either analyze a single/multiple glucose profiles or compare two groups of glucose profiles. On the bottom right, as representative use case, the dedicated GUI that allows to analyze a single glucose profile. Abbreviations: AGATA, Automated Glucose dATa Analysis; GUI, graphical user interface.

Journal: Journal of diabetes science and technology

Article Title: AGATA: A Toolbox for Automated Glucose Data Analysis.

doi: 10.1177/19322968221147570

Figure Lengend Snippet: Figure 1. On the top, the processing pipeline that can be implemented with AGATA thanks to its functionalities. On the bottom left, the home screen of AGATA’s standalone version, which allows to easily access specific interfaces to either analyze a single/multiple glucose profiles or compare two groups of glucose profiles. On the bottom right, as representative use case, the dedicated GUI that allows to analyze a single glucose profile. Abbreviations: AGATA, Automated Glucose dATa Analysis; GUI, graphical user interface.

Article Snippet: For this reason, to provide the diabetes technology community a unified tool, here we present Automated Glucose dATa Analysis (AGATA), an automated glucose data analysis toolbox developed in MATLAB/Octave.

Techniques:

Figure 2. Detailed visualization of a week of CGM data extracted from a representative subject (Ohio544) obtained using AGATA’s utilities. Panel (a) (plot I) shows with a black solid line the CGM trace and highlights the hyperglycemic events with yellow areas, the hypoglycemic events with red areas, and the missing portion of data with shaded red areas. It also marks the target glycemic range with a shaded gray shaded area delimited by two green dashed lines. Panel (b) (plot II) shows with a black solid line the CGM trace and highlights, with superimposed dots, aggregated glucose values in hyperglycemia (in yellow), hypoglycemia (in red), and target (in green). It also highlights missing portion of data with shaded red areas and marks the target glycemic range with a shaded gray area delimited by two green dashed lines. Panel (c) (plot VII) shows with a black solid line the CGM rate of change. It also highlights positive values with a gray shaded area and the missing portion of data with red shaded areas. Abbreviations: CGM, continuous glucose monitoring; AGATA, Automated Glucose dATa Analysis.

Journal: Journal of diabetes science and technology

Article Title: AGATA: A Toolbox for Automated Glucose Data Analysis.

doi: 10.1177/19322968221147570

Figure Lengend Snippet: Figure 2. Detailed visualization of a week of CGM data extracted from a representative subject (Ohio544) obtained using AGATA’s utilities. Panel (a) (plot I) shows with a black solid line the CGM trace and highlights the hyperglycemic events with yellow areas, the hypoglycemic events with red areas, and the missing portion of data with shaded red areas. It also marks the target glycemic range with a shaded gray shaded area delimited by two green dashed lines. Panel (b) (plot II) shows with a black solid line the CGM trace and highlights, with superimposed dots, aggregated glucose values in hyperglycemia (in yellow), hypoglycemia (in red), and target (in green). It also highlights missing portion of data with shaded red areas and marks the target glycemic range with a shaded gray area delimited by two green dashed lines. Panel (c) (plot VII) shows with a black solid line the CGM rate of change. It also highlights positive values with a gray shaded area and the missing portion of data with red shaded areas. Abbreviations: CGM, continuous glucose monitoring; AGATA, Automated Glucose dATa Analysis.

Article Snippet: For this reason, to provide the diabetes technology community a unified tool, here we present Automated Glucose dATa Analysis (AGATA), an automated glucose data analysis toolbox developed in MATLAB/Octave.

Techniques:

Figure 3. Summary visualization of a week of CGM data extracted from a retrospective subject (Ohio544) obtained using AGATA’s utilities. Panel (a) (plot III) shows the daily glucose profile distribution resulting from the combination of every single daily profile. The median daily profile is represented with a black bold line, while the shaded dark blue and the shaded light blue areas highlight the 25th to 75th and the 5th to 95th percentiles, respectively. Panel (b) (plot IV) shows the distribution of CGM rate of change as an histogram (in blue) and the respective fitted Gaussian distribution (in red). Panel (c) (plot V) shows the CVGA plot. Panel (d) (plot VI) shows the GRI plot. Abbreviations: CGM, continuous glucose monitoring; AGATA, Automated Glucose dATa Analysis; CVGA, control variability glucose analysis; GRI, glycemic risk index; BG, blood glucose.

Journal: Journal of diabetes science and technology

Article Title: AGATA: A Toolbox for Automated Glucose Data Analysis.

doi: 10.1177/19322968221147570

Figure Lengend Snippet: Figure 3. Summary visualization of a week of CGM data extracted from a retrospective subject (Ohio544) obtained using AGATA’s utilities. Panel (a) (plot III) shows the daily glucose profile distribution resulting from the combination of every single daily profile. The median daily profile is represented with a black bold line, while the shaded dark blue and the shaded light blue areas highlight the 25th to 75th and the 5th to 95th percentiles, respectively. Panel (b) (plot IV) shows the distribution of CGM rate of change as an histogram (in blue) and the respective fitted Gaussian distribution (in red). Panel (c) (plot V) shows the CVGA plot. Panel (d) (plot VI) shows the GRI plot. Abbreviations: CGM, continuous glucose monitoring; AGATA, Automated Glucose dATa Analysis; CVGA, control variability glucose analysis; GRI, glycemic risk index; BG, blood glucose.

Article Snippet: For this reason, to provide the diabetes technology community a unified tool, here we present Automated Glucose dATa Analysis (AGATA), an automated glucose data analysis toolbox developed in MATLAB/Octave.

Techniques: Control

Figure 5. Comparison between CGM data of two representative subjects (Ohio544 and Ohio596) obtained using AGATA’s utilities. Panel (a) (plot III) compares the daily glucose profile distributions highlighted in blue for Ohio544 and in red for Ohio596, in terms of median, 25th to 75th percentile, and 5th to 95th percentile. Panels (b and c) compare the CVGA and GRI of the two subjects where data of Ohio544 and Ohio596 are reported as black circles and gray diamonds, respectively. Abbreviations: CGM, continuous glucose monitoring; AGATA, Automated Glucose dATa Analysis; CVGA, control variability glucose analysis; GRI, glycemic risk index; BG, blood glucose.

Journal: Journal of diabetes science and technology

Article Title: AGATA: A Toolbox for Automated Glucose Data Analysis.

doi: 10.1177/19322968221147570

Figure Lengend Snippet: Figure 5. Comparison between CGM data of two representative subjects (Ohio544 and Ohio596) obtained using AGATA’s utilities. Panel (a) (plot III) compares the daily glucose profile distributions highlighted in blue for Ohio544 and in red for Ohio596, in terms of median, 25th to 75th percentile, and 5th to 95th percentile. Panels (b and c) compare the CVGA and GRI of the two subjects where data of Ohio544 and Ohio596 are reported as black circles and gray diamonds, respectively. Abbreviations: CGM, continuous glucose monitoring; AGATA, Automated Glucose dATa Analysis; CVGA, control variability glucose analysis; GRI, glycemic risk index; BG, blood glucose.

Article Snippet: For this reason, to provide the diabetes technology community a unified tool, here we present Automated Glucose dATa Analysis (AGATA), an automated glucose data analysis toolbox developed in MATLAB/Octave.

Techniques: Comparison, Control