Citas bibligráficas
Castillo, J., Apfata, N. (2024). Desarrollo de un equipo electrónico orientado a la detección de extracción de sangre en pacientes con capacidad de registro de datos temporales y monitoreo de llenado del tubo de venopunción [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/672264
Castillo, J., Apfata, N. Desarrollo de un equipo electrónico orientado a la detección de extracción de sangre en pacientes con capacidad de registro de datos temporales y monitoreo de llenado del tubo de venopunción [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2024. http://hdl.handle.net/10757/672264
@misc{renati/414340,
title = "Desarrollo de un equipo electrónico orientado a la detección de extracción de sangre en pacientes con capacidad de registro de datos temporales y monitoreo de llenado del tubo de venopunción",
author = "Apfata Huallpa, Nelson",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2024"
}
The proposed project introduces a portable electronic device aimed at enhancing the tracking and recording of blood samples in venipuncture tubes. The state of the art presents various solutions that come with inherent limitations. These limitations include the high cost of available equipment, a lack of widespread commercial availability, and limited functionality restricted to tracking only when samples pass through scanners. Additionally, these solutions fail to provide continuous visibility of the temporal and quantitative data associated with blood samples, confining the recording to specific points in the process. Venipuncture tubes used in blood extraction face challenges in terms of reliability and precision due to environmental factors, errors in venipuncture techniques, and inadequate storage conditions. The proposed project distinguishes itself through its innovative approach, preserving human involvement in sample collection. A developed portable electronic device resolves these limitations by enabling the storage of temporal and quantitative data with an accuracy of ± 10%. This precision is achieved through algorithms based on digital image processing techniques and convolutional neural networks. The results obtained demonstrate high accuracy in quantitative data and a maximum temporal precision of ± 3 seconds. These advancements signify significant progress in overcoming the mentioned limitations and delivering increased reliability, precision, and tracking in the recording of blood samples in venipuncture tubes.
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