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Image Search Results
Journal: JMIR mHealth and uHealth
Article Title: Mobile Health Use by Older Individuals at Risk of Cardiovascular Disease and Type 2 Diabetes Mellitus in an Australian Cohort: Cross-sectional Survey Study
doi: 10.2196/37343
Figure Lengend Snippet: Demographic characteristics of all participants and various subgroups.
Article Snippet: A report by the
Techniques: Activity Assay
Journal: International Journal of Environmental Research and Public Health
Article Title: Accuracy of a Smartphone Application Measuring Snoring in Adults—How Smart Is It Actually?
doi: 10.3390/ijerph18147326
Figure Lengend Snippet: Cross table for calculation of sensitivity, specificity, positive and negative prediction values, prevalence and accuracy.
Article Snippet: Therefore, the purpose of the present study was to assess the accuracy of recorded snoring using the free version of the
Techniques:
Journal: International Journal of Environmental Research and Public Health
Article Title: Accuracy of a Smartphone Application Measuring Snoring in Adults—How Smart Is It Actually?
doi: 10.3390/ijerph18147326
Figure Lengend Snippet: Individual percentage of snoring (%) measured by the SnoreLab app (SL) and polygraphy (PG) given for all 19 volunteers.
Article Snippet: Therefore, the purpose of the present study was to assess the accuracy of recorded snoring using the free version of the
Techniques:
Journal: International Journal of Environmental Research and Public Health
Article Title: Accuracy of a Smartphone Application Measuring Snoring in Adults—How Smart Is It Actually?
doi: 10.3390/ijerph18147326
Figure Lengend Snippet: Median, minimal and maximal values as well as means and standard deviations of measurements derived by the SnoreLab app and polygraphy.
Article Snippet: Therefore, the purpose of the present study was to assess the accuracy of recorded snoring using the free version of the
Techniques: Derivative Assay
Journal: International Journal of Environmental Research and Public Health
Article Title: Accuracy of a Smartphone Application Measuring Snoring in Adults—How Smart Is It Actually?
doi: 10.3390/ijerph18147326
Figure Lengend Snippet: Prevalence, sensitivity, specificity, positive predictive value, negative predictive value and accuracy of snoring detection by the SnoreLab app relative to polygraphy (used as gold standard). Snoring was classified as present if the different threshold levels of total snoring per night were exceeded. Values are given in percentage (%).
Article Snippet: Therefore, the purpose of the present study was to assess the accuracy of recorded snoring using the free version of the
Techniques:
Journal: International Journal of Environmental Research and Public Health
Article Title: Accuracy of a Smartphone Application Measuring Snoring in Adults—How Smart Is It Actually?
doi: 10.3390/ijerph18147326
Figure Lengend Snippet: Bland–Altman plots for comparison of total snoring ratio measured by polygraphy with ( A ) total snoring ratio and ( B ) loud + epic snoring ratio measured by the SnoreLab app ( B ). Red line: mean difference of both methods; black line: optimal agreement between the methods; green lines: 95% limits of agreement.
Article Snippet: Therefore, the purpose of the present study was to assess the accuracy of recorded snoring using the free version of the
Techniques: Comparison
Journal: International Journal of Environmental Research and Public Health
Article Title: Accuracy of a Smartphone Application Measuring Snoring in Adults—How Smart Is It Actually?
doi: 10.3390/ijerph18147326
Figure Lengend Snippet: Spearman-Rho correlation coefficients (r) for the different scores obtained by the SnoreLab app (SL) and polygraphy (PG).
Article Snippet: Therefore, the purpose of the present study was to assess the accuracy of recorded snoring using the free version of the
Techniques: