ABSTRACT
The COVID-19 pandemic highlighted the importance of widespread testing for SARS-CoV-2, leading to the development of various new testing methods. However, traditional invasive sampling methods can be uncomfortable and even painful, creating barriers to testing accessibility. In this article, we explore how machine learning-enhanced biosensors can enable non-invasive sampling for SARS-CoV-2 testing, revolutionizing the way we detect and monitor the virus. By detecting and measuring specific biomarkers in body fluids or other samples, these biosensors can provide accurate and accessible testing options that do not require invasive procedures. We provide examples of how these biosensors can be used for non-invasive SARS-CoV-2 testing, such as saliva-based testing. We also discuss the potential impact of non-invasive testing on accessibility and accuracy of testing. Finally, we discuss potential limitations or biases associated with the machine learning algorithms used to improve the biosensors and explore future directions in the field of machine learning-enhanced biosensors for SARS-CoV-2 testing, considering their potential impact on global healthcare and disease control.
ABSTRACT
In pipeline production, there is a considerable distance between the moment when the operation principle of a biosensor will be verified in the laboratory until the moment when it can be used in real conditions. This distance is often covered by an optimization and packaging process. This article described the packaging and optimization of a SARS-CoV-2 biosensor, as well as the packaging of its electronic readout circuit. The biosensor was packed with a photosensitive tape, which forms a protective layer and is patterned in a way to form a well in the sensing area. The well is meant to limit the liquid diffusion, thereby reducing the measurement error. Subsequently, a connector between the biosensor and its readout circuit was designed and 3D-printed, ensuring the continuous and easy reading of the biosensor. In the last step, a three-dimensional case was designed and printed, thus protecting the circuit from any damage, and allowing its operation in real conditions.
Subject(s)
Biosensing Techniques , COVID-19 , Humans , SARS-CoV-2 , Biosensing Techniques/methods , ElectrodesABSTRACT
The COVID-19 pandemic remains a constant threat to human health, the economy, and social relations. Scientists around the world are constantly looking for new technological tools to deal with the pandemic. Such tools are the rapid virus detection tests, which are constantly evolving and optimizing. This paper presents a biosensor platform for the rapid detection of spike protein both in laboratory conditions and in swab samples from hospitalized patients. It is a continuation and improvement of our previous work and consists of a microcontroller-based readout circuit, which measures the capacitance change generated in an interdigitated electrode transducer by the presence either of sole spike protein or the presence of SARS-CoV-2 particles in swab samples. The circuit efficiency is calibrated by its correlation with the capacitance measurement of an LCR (inductance (L), capacitance (C), and resistance (R)) meter. The test result is made available in less than 2 min through the microcontroller's LCD (liquid-crystal display) screen, whereas at the same time, the collected data are sent wirelessly to a mobile application interface. The novelty of this research lies in the potential it offers for continuous and effective screening of SARS-CoV-2 patients, which is facilitated and enhanced, providing big data statistics of COVID-19 in terms of space and time. This device can be used by individuals for SARS-CoV-2 testing at home, by health professionals for patient monitoring, and by public health agencies for monitoring the spatio-temporal spread of the virus.
