A critical path to solving the SARS-CoV-2 pandemic, without further socioeconomic impact, is to stop its spread. For this to happen, pre- or asymptomatic individuals infected with the virus need to ...be detected and isolated opportunely. Unfortunately, there are no current ubiquitous (i.e., ultra-sensitive, cheap, and widely available) rapid testing tools capable of early detection of SARS-CoV-2 infections. In this article, we introduce an accurate, portable, and low-cost medical device and bio-nanosensing electrode dubbed SenSARS and its experimental validation. SenSARS' device measures the electrochemical impedance spectra of a disposable bio-modified screen-printed carbon-based working electrode (SPCE) to the changes in the concentration of SARS-CoV-2 antigen molecules ("S" spike proteins) contained within a sub-microliter fluid sample deposited on its surface. SenSARS offers real-time diagnostics and viral load tracking capabilities. Positive and negative control tests were performed in phosphate-buffered saline (PBS) at different concentrations (between 1 and 50 fg/mL) of SARS-CoV-2(S), Epstein-Barr virus (EBV) glycoprotein gp350, and Influenza H1N1 M1 recombinant viral proteins. We demonstrate that SenSARS is easy to use, with a portable and lightweight (< 200 g) instrument and disposable test electrodes (<U.S. <inline-formula> <tex-math notation="LaTeX">\ </tex-math></inline-formula>5), capable of fast diagnosis (~10 min), with high analytical sensitivity (low limits of detection, LOD = 1.065 fg/mL, and quantitation, LOQ = 3.6 fg/mL) and selectivity to SARS-CoV-2(S) antigens, even in the presence of structural proteins from the other pathogens tested. SenSARS provides a potential path to pervasive rapid diagnostics of SARS-CoV-2 in clinical, point-of-care, and home-care settings, and to breaking the transmission chain of this virus. Medical device compliance testing of SenSARS to EIC-60601 technical standards is underway.
Se desarrolló un sistema interacción humano-robot multimodal (gestos y voz) que permite a usuarios enseñarle tareas de clasificación de cubos por color a un robot. La evaluación del sistema fue ...realizada por siete usuarios de forma cuantitativa y cualitativa. En las pruebas cuantitativas se evaluó un total de 63 interacciones verbales, 252 interacciones gestuales, y 63 multimodales. El porcentaje de reconocimiento de las interacciones fue del 98.41% para los comandos de voz, 81.35 % para los gestuales, y 80.95% para las multimodales. Luego del aprendizaje, el robot fue capaz de realizar correctamente la tarea de clasificación de cubos por color en un 100%; siendo capaz de responder exitosamente ante condiciones iniciales (ubicaciones y cantidad de cubos) no enseñadas previamente. La evaluación cualitativa del sistema se realizó para conocer la percepción de los usuarios, arrojando resultados consistentes con los porcentajes de reconocimiento, favoreciendo la interacción verbal sobre la multimodal.
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