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10.1007/s11517-025-03467-y http://scihub22266oqcxt.onion/10.1007/s11517-025-03467-y 41108473!ä!41108473 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\41108473.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Med+Biol+Eng+Comput 2025 ; ä (ä): ä Nephropedia Template TP {{tp|p=41108473|t=2025. Model based analytical approach for physical activity quantification in people with type 1 diabetes |pdf=|usr=}}{{41108473}} gab.com Text Model based analytical approach for physical activity quantification in people with type 1 diabetes JO: Med Biol Eng Comput http://www.kidney.de/pget.php?&tw=1&pmid=41108473 #FOAvip Physical activity (PA) represents a significant challenge in the management of type 1 diabetes (T1D), given its impact on glucose levels, which are influenced by various exercise characteristics, including duration, intensity, and type. The development of strategies that allow for the monitoring of these characteristics is crucial to improve glycemic control during exercise for both conventional therapies and automated insulin delivery systems. This paper presents a state-space model that further exploits the HR signal for the purpose of quantifying and distinguishing between aerobic and anaerobic PA. The model design is based on an analysis of the distinctive features of HR signal, including the mean HR value, the maximum HR, and the presence of pronounced fluctuations in HR. This method does not require any training and offers users interpretability and explainability. Furthermore, it enables intuitive tuning, a feature which is of particular importance in clinical settings. The model is validated using two clinical trials: the T1DEXI study, which is the largest real-world clinical trial including PA in people with T1D conducted to date, and a pilot clinical trial conducted by our research group in Argentina. The findings indicate the model has the capacity to quantify and differentiate between aerobic and resistance PA, which represent the two types of PA exhibiting the most significant and contrasting influence on glucose levels. Twit Text FOAVip Model based analytical approach for physical activity quantification in people with type 1 diabetes ????Med Biol Eng Comput http://www.kidney.de/pget.php?&tw=1&pmid=41108473 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=41108473 #FOAvip English Wikipedia <ref>{{Cite pmid|41108473}}</ref> Model based analytical approach for physical activity quantification in people with type 1 diabetes #MMPMID41108473 Da Rosa Jurao FL; Fushimi E; Garelli F Med Biol Eng Comput 2025[Oct]; ä (ä): ä PMID41108473show ga Physical activity (PA) represents a significant challenge in the management of type 1 diabetes (T1D), given its impact on glucose levels, which are influenced by various exercise characteristics, including duration, intensity, and type. The development of strategies that allow for the monitoring of these characteristics is crucial to improve glycemic control during exercise for both conventional therapies and automated insulin delivery systems. This paper presents a state-space model that further exploits the HR signal for the purpose of quantifying and distinguishing between aerobic and anaerobic PA. The model design is based on an analysis of the distinctive features of HR signal, including the mean HR value, the maximum HR, and the presence of pronounced fluctuations in HR. This method does not require any training and offers users interpretability and explainability. Furthermore, it enables intuitive tuning, a feature which is of particular importance in clinical settings. The model is validated using two clinical trials: the T1DEXI study, which is the largest real-world clinical trial including PA in people with T1D conducted to date, and a pilot clinical trial conducted by our research group in Argentina. The findings indicate the model has the capacity to quantify and differentiate between aerobic and resistance PA, which represent the two types of PA exhibiting the most significant and contrasting influence on glucose levels. äModel based analytical approach for physical activity quantification i(epmc).pdf DeepDyve Pubget Overpricing