
La citometría de flujo convencional requiere dilución de muestras, lo que limita su aplicación en entornos point-of-care integrados. Este trabajo presenta el marco teórico para un módulo de Citometría Colectiva Kubelka-Munk (CKM), diseñado como un subsistema de caracterización óptica para medios biológicos densos sin separación celular. El instrumento propuesto implementa una arquitectura de detección dual (transmitancia 0◦ y reflectancia difusa 90◦) con emisores multiespectrales (405 nm, 530 nm y 650 nm) para extraer simultáneamente información química (coeficiente de absorción K) y física (coeficiente de dispersión S). La señal óptica teórica se procesa mediante una red neuronal convolucional 1D desplegable en microcontroladores ESP32-S3, permitiendo la clasificación en tiempo real de estados patológicos como lisis celular, infección parasitaria y agregación tumoral. Se detalla el modelo matemático de interacción luz-materia en medios turbios, la arquitectura hardware propuesta y el protocolo de validación futuro. Este enfoque establece un paradigma para un módulo de diagnóstico hematológico de bajo costo, integrable en sistemas de screening masivo y medicina tropical.
Conventional flow cytometry requires sample dilution and single-cell analysis, limiting its application in point-of-care environments. This paper presents the theoretical framework for a Kubelka-Munk Collective Cytometry (CKM) module, designed as an optical characterization subsystem for dense biological media without cell separation. The proposed instrument implements a dual detection architecture (transmittance 0◦ and diffuse reflectance 90◦) with multi-spectral emitters (405 nm, 530 nm and 650 nm) to simultaneously extract chemical information (absorption coefficient K) and physical information (scattering coefficient S). The theoretical optical signal is processed via a 1D convolutional neural network deployable on ESP32-S3 microcontrollers, enabling real-time classification of pathological states such as cell lysis, parasitic infection, and tumor aggregation. The mathematical model of light-matter interaction in turbid media, the proposed hardware architecture, and the future validation protocol are detailed. This approach establishes a paradigm for a low-cost hematological diagnostic module, integrable into massive screening systems and tropical medicine.
TinyML, ESP32-S3, Collective cytometry, Point-of-care module, Mie scattering, Dense biological media, Diffuse reflectance, Adaptive spectroscopy
TinyML, ESP32-S3, Collective cytometry, Point-of-care module, Mie scattering, Dense biological media, Diffuse reflectance, Adaptive spectroscopy
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