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Optimizing acoustic pressure fields in SAW microfluidic devices: A numerical st...
Amorim, Débora; Dinis, Hugo Daniel Costa; Minas, Graça; Sousa, Patrícia C.; Abreu, Carlos; Catarino, Susana OliveiraSurface acoustic wave-based microfluidic devices have gained substantial attention for their effectiveness in manipulating, detecting, and quantifying biological samples. These systems utilize interdigitated transducers deposited on piezoelectric substrates to generate acoustic fields within microchannels. This study presents a comparative analysis of acoustic pressure fields generated using different piezoelec...
A review of SAW-based micro- and nanoparticle manipulation in microfluidics
Amorim, Débora; Sousa, Patrícia C.; Abreu, Carlos; Catarino, Susana OliveiraSurface acoustic wave (SAW)-based microfluidics has emerged as a promising technology for precisely manipulating particles and cells at the micro- and nanoscales. Acoustofluidic devices offer advantages such as low energy consumption, high throughput, and label-free operation, making them suitable for particle manipulation tasks including pumping, mixing, sorting, and separation. In this review, we provide an o...
Personalized and context-aware decision support system for diabetes therapeutics
Amorim, Débora; Abreu, Carlos; Miranda, FranciscoPersonalized recommendations for diabetes therapy can be highly beneficial but complex to make and time-consuming for patients and healthcare professionals. Therefore, we propose a decision support system to help patients and healthcare professionals to make decisions to improve treatments based on the patient’s daily life data. The proposed solution allows the collection of patients’ data related to their glyc...
The importance of artificial intelligence in postprandial blood glucose predict...
Miranda, Francisco; Amorim, Débora; Ferreira, Luís; Abreu, CarlosMany works are using artificial intelligence to forecast postprandial blood glucose. However, the following questions arise: is it necessary to develop artificial intelligence techniques to predict blood glucose? How important is artificial intelligence for this purpose? This work gives some insights seeking the answer to these questions in the context of using postprandial blood glucose predictions to optimize...
Assessing carbohydrate counting accuracy: current limitations and future direct...
Amorim, Débora; Miranda, Francisco; Santos, Andreia; Graça, Luís C. C.; Rodrigues, João; Rocha, Mara; Pereira, Maria Aurora; Sousa, ClementinaDiabetes mellitus is a prevalent chronic autoimmune disease with a high impact on global health, affecting millions of adults and resulting in significant morbidity and mortality. Achieving optimal blood glucose levels is crucial for diabetes management to prevent acute and long-term complications. Carbohydrate counting (CC) is widely used by patients with type 1 diabetes to adjust prandial insulin bolus doses ...
Personalized and context-aware decision support system for diabetes therapeutics
Amorim, Débora; Abreu, Carlos; Miranda, FranciscoPersonalized recommendations for diabetes therapy can be highly beneficial but complex to make and time-consuming for patients and healthcare professionals. Therefore, we propose a decision support system to help patients and healthcare professionals to make decisions to improve treatments based on the patient’s daily life data. The proposed solution allows the collection of patients’ data related to their glyc...
The importance of artificial intelligence in postprandial blood glucose predict...
Miranda, Francisco; Amorim, Débora; Ferreira, Luís; Abreu, CarlosMany works are using artificial intelligence to forecast postprandial blood glucose. However, the following questions arise: is it necessary to develop artificial intelligence techniques to predict blood glucose? How important is artificial intelligence for this purpose? This work gives some insights seeking the answer to these questions in the context of using postprandial blood glucose predictions to optimize...
Assessing carbohydrate counting accuracy: current limitations and future direct...
Amorim, Débora; Miranda, Francisco; Santos, Andreia; Graça, Luís; Rodrigues, João; Rocha, Mara; Pereira, Maria Aurora; Sousa, ClementinaDiabetes mellitus is a prevalent chronic autoimmune disease with a high impact on global health, affecting millions of adults and resulting in significant morbidity and mortality. Achieving optimal blood glucose levels is crucial for diabetes management to prevent acute and long-term complications. Carbohydrate counting (CC) is widely used by patients with type 1 diabetes to adjust prandial insulin bolus doses ...
Assessing carbohydrate counting accuracy: Current limitations and future direct...
Amorim, Débora; Miranda, Francisco; Santos, Andreia; Graça, Luís; Rodrigues, João; Rocha, Mara; Pereira, Maria Aurora; Sousa, ClementinaDiabetes mellitus is a prevalent chronic autoimmune disease with a high impact on global health, affecting millions of adults and resulting in significant morbidity and mortality. Achieving optimal blood glucose levels is crucial for diabetes management to prevent acute and long-term complications. Carbohydrate counting (CC) is widely used by patients with type 1 diabetes to adjust prandial insulin bolus doses ...
In silico validation of personalized safe intervals for carbohydrate counting e...
Amorim, Débora; Miranda, Francisco; Abreu, CarlosFor patients with Type 1 diabetes mellitus (T1DM), accurate carbohydrate counting (CC) is essential for successful blood glucose regulation. Unfortunately, mistakes are common and may lead to an incorrect dosage of prandial insulin. In this work, we aim to demonstrate that each person has their own limits for CC errors, which can be computed using patient-specific data. To validate the proposed method, we teste...