Biosensors for Personal Mobile Health: A System Architecture Perspective

Exploring Biosensors' Scientific Production and Research Patterns: A Bibliometric Analysis

More sustainable biosensor production is growing in importance, allowing for the development of technological solutions for several industries, such as those in the health, chemical, and food sectors. Tracking the latest advancements in biosensors' scientific production is fundamental to determining the opportunities for the future of the biosensing field. This article aims to map scientific production in the biosensors field by running a bibliometric analysis of journal articles registered in the Web of Science database under biosensor-related vital concepts. The key concepts were selected by researchers and biosensor technology developers working on the BioAssembler Horizon project. The findings lead to identifying the scientific and technological knowledge base on biosensing devices and tracking the main scientific organisations developing this technology throughout the COVID-19 period (2019-2023). The institutional origin of the publications characterised the global distribution of related knowledge competencies and research partnerships. These results are discussed, shedding light on the scientific, economic, political, and structural factors that contribute to the formation of a scientific knowledge-based focus on the performance and design of these sensors. Moreover, the lack of scientific ties between the three axes of organisations producing expertise in this area (China, USA, and Russia) points towards the need to find synergies through new mechanisms of co-authorship and collaboration.

Flexible and Stretchable Light-Emitting Diodes and Photodetectors for Human-Centric Optoelectronics

Optoelectronic devices with unconventional form factors, such as flexible and stretchable light-emitting or photoresponsive devices, are core elements for the next-generation human-centric optoelectronics. For instance, these deformable devices can be utilized as closely fitted wearable sensors to acquire precise biosignals that are subsequently uploaded to the cloud for immediate examination and diagnosis, and also can be used for vision systems for human-interactive robotics. Their inception was propelled by breakthroughs in novel optoelectronic material technologies and device blueprinting methodologies, endowing flexibility and mechanical resilience to conventional rigid optoelectronic devices. This paper reviews the advancements in such soft optoelectronic device technologies, honing in on various materials, manufacturing techniques, and device design strategies. We will first highlight the general approaches for flexible and stretchable device fabrication, including the appropriate material selection for the substrate, electrodes, and insulation layers. We will then focus on the materials for flexible and stretchable light-emitting diodes, their device integration strategies, and representative application examples. Next, we will move on to the materials for flexible and stretchable photodetectors, highlighting the state-of-the-art materials and device fabrication methods, followed by their representative application examples. At the end, a brief summary will be given, and the potential challenges for further development of functional devices will be discussed as a conclusion.

PCR-Free Innovative Strategies for SARS-CoV-2 Detection

The pandemic outbreak caused by SARS-CoV-2 coronavirus brought a crucial issue in public health causing up to now more than 600 million infected people and 6.5 million deaths. Conventional diagnostic methods are based on quantitative reverse transcription polymerase chain reaction (RT-qPCR assay) and immuno-detection (ELISA assay). However, despite these techniques have the advantages of being standardized and consolidated, they keep some main limitations in terms of accuracy (immunoassays), time/cost consumption of analysis, the need for qualified personnel, and lab constrain (molecular assays). There is crucial the need to develop new diagnostic approaches for accurate, fast and portable viral detection and quantification. Among these, PCR-free biosensors represent the most appealing solution since they can allow molecular detection without the complexity of the PCR. This will enable the possibility to be integrated in portable and low-cost systems for massive and decentralized screening of SARS-CoV-2 in a point-of-care (PoC) format, pointing to achieve a performant identification and control of infection. In this review, the most recent approaches for the SARS-CoV-2 PCR-free detection are reported, describing both the instrumental and methodological features, and highlighting their suitability for a PoC application.

Smartphone-based platforms implementing microfluidic detection with image-based artificial intelligence

The frequent outbreak of global infectious diseases has prompted the development of rapid and effective diagnostic tools for the early screening of potential patients in point-of-care testing scenarios. With advances in mobile computing power and microfluidic technology, the smartphone-based mobile health platform has drawn significant attention from researchers developing point-of-care testing devices that integrate microfluidic optical detection with artificial intelligence analysis. In this article, we summarize recent progress in these mobile health platforms, including the aspects of microfluidic chips, imaging modalities, supporting components, and the development of software algorithms. We document the application of mobile health platforms in terms of the detection objects, including molecules, viruses, cells, and parasites. Finally, we discuss the prospects for future development of mobile health platforms.

Lessons from COVID-19 for improving diagnostic access in future pandemics

Throughout the COVID-19 pandemic, we have witnessed the critical and expanding roles of testing. Despite the development of over a thousand brand of tests - with some close to fulfilling the 4As (accuracy, access, affordability, and actionability via quick time to result) of an ideal diagnostic test - gaps persisted in developing tests to fit public health needs, and in providing equitable access. Here, we review how the use cases for testing evolved over the course of the COVID-19 pandemic, with associated engineering challenges (and potential lessons) at each phase for test developers. We summarise lessons learnt from the recent epidemic and propose four areas for future cooperative effort among test developers, government regulators and policy makers, public health experts, and the public: 1) develop new models for public sector funding and research and development; 2) increase testing capacity by investing in adaptable open-platform technologies at every level of the healthcare system; 3) build data connectivity infrastructures to support a connected diagnostic system as a backbone for surveillance; and 4) facilitate the rapid translation of innovation into use through a coordinated framework for regulatory approval and policy development.

Wearable artificial intelligence biosensor networks

The demand for high-quality healthcare and well-being services is remarkably increasing due to the ageing global population and modern lifestyles. Recently, the integration of wearables and artificial intelligence (AI) has attracted extensive academic and technological attention for its powerful high-dimensional data processing of wearable biosensing networks. This work reviews the recent developments in AI-assisted wearable biosensing devices in disease diagnostics and fatigue monitoring demonstrating the trend towards personalised medicine with highly efficient, cost-effective, and accurate point-of-care diagnosis by finding hidden patterns in biosensing data and detecting abnormalities. The reliability of adaptive learning and synthetic data and data privacy still need further investigation to realise personalised medicine in the next decade. Due to the worldwide popularity of smartphones, they have been utilised for sensor readout, wireless data transfer, data processing and storage, result display, and cloud server communication leading to the development of smartphone-based biosensing systems. The recent advances have demonstrated a promising future for the healthcare system because of the increasing data processing power, transfer efficiency and storage capacity and diversifying functionalities.

Interdigitated Organic Sensor in Multimodal Facemask's Barrier Integrity and Wearer's Respiration Monitoring

Facemasks are used as a personal protective equipment in medical services. They became compulsory during the recent COVID-19 pandemic at large. Their barrier effectiveness during various daily activities over time has been the subject of much debate. We propose the fabrication of an organic sensor to monitor the integrity of surgical masks to ensure individuals' health and safety during their use. Inkjet printing of an interdigitated conducting polymer-based sensor on the inner layer of the mask proved to be an efficient and direct fabrication process to rapidly reach the end user. The sensor's integration happens without hampering the mask functionality and preserving its original air permeability. Its resistive response to humidity accumulation allows it to monitor the mask's wetting in use, providing a quantified way to track its barrier integrity and assist in its management. Additionally, it detects the user's respiration rate as a capacitive response to the exhaled humidity, essential in identifying breathing difficulties or a sign of an infection. Respiration evaluations during daily activities show outstanding performance in relation to unspecific motion artifacts and breathing resolution. This e-mask yields an integrated solution for home-based individual monitoring and an advanced protective equipment for healthcare professionals.

A Sensor-Based Perspective in Early-Stage Parkinson's Disease: Current State and the Need for Machine Learning Processes

Parkinson's disease (PD) is a progressive neurodegenerative disorder associated with dysfunction of dopaminergic neurons in the brain, lack of dopamine and the formation of abnormal Lewy body protein particles. PD is an idiopathic disease of the nervous system, characterized by motor and nonmotor manifestations without a discrete onset of symptoms until a substantial loss of neurons has already occurred, enabling early diagnosis very challenging. Sensor-based platforms have gained much attention in clinical practice screening various biological signals simultaneously and allowing researchers to quickly receive a huge number of biomarkers for diagnostic and prognostic purposes. The integration of machine learning into medical systems provides the potential for optimization of data collection, disease prediction through classification of symptoms and can strongly support data-driven clinical decisions. This work attempts to examine some of the facts and current situation of sensor-based approaches in PD diagnosis and discusses ensemble techniques using sensor-based data for developing machine learning models for personalized risk prediction. Additionally, a biosensing platform combined with clinical data processing and appropriate software is proposed in order to implement a complete diagnostic system for PD monitoring.

COVID-19 challenges: From SARS-CoV-2 infection to effective point-of-care diagnosis by electrochemical biosensing platforms

In January 2020, the World Health Organization (WHO) identified a new zoonotic virus, SARS-CoV-2, responsible for causing the COVID-19 (coronavirus disease 2019). Since then, there has been a collaborative trend between the scientific community and industry. Multidisciplinary research networks try to understand the whole SARS-CoV-2 pathophysiology and its relationship with the different grades of severity presented by COVID-19. The scientific community has gathered all the data in the quickly developed vaccines that offer a protective effect for all variants of the virus and promote new diagnostic alternatives able to have a high standard of efficiency, added to shorter response analysis time and portability. The industry enters in the context of accelerating the path taken by science until obtaining the final product. In this review, we show the principal diagnostic methods developed during the COVID-19 pandemic. However, when we observe the diagnostic tools section of an efficient infection outbreak containment report and the features required for such tools, we could observe a highlight of electrochemical biosensing platforms. Such devices present a high standard of analytical performance, are low-cost tools, easy to handle and interpret, and can be used in the most remote and low-resource regions. Therefore, probably, they are the ideal point-of-care diagnostic tools for pandemic scenarios.

Point-of-care diagnostics: recent developments in a pandemic age

In this review, we provide an overview of developments in point-of-care (POC) diagnostics during the COVID-19 pandemic. We review these advances within the framework of a holistic POC ecosystem, focusing on points of interest - both technological and non-technological - to POC researchers and test developers. Technologically, we review design choices in assay chemistry, microfluidics, and instrumentation towards nucleic acid and protein detection for severe acute respiratory coronavirus 2 (SARS-CoV-2), and away from the lab bench, developments that supported the unprecedented rapid development, scale up, and deployment of POC devices. We describe common features in the POC technologies that obtained Emergency Use Authorization (EUA) for nucleic acid, antigen, and antibody tests, and how these tests fit into four distinct POC use cases. We conclude with implications for future pandemics, infectious disease monitoring, and digital health.

Lab-on-a-Chip Devices for Point-of-Care Medical Diagnostics

The recent coronavirus (COVID-19) pandemic has underscored the need to move from traditional lab-centralized diagnostics to point-of-care (PoC) settings. Lab-on-a-chip (LoC) platforms facilitate the translation to PoC settings via the miniaturization, portability, integration, and automation of multiple assay functions onto a single chip. For this purpose, paper-based assays and microfluidic platforms are currently being extensively studied, and much focus is being directed towards simplifying their design while simultaneously improving multiplexing and automation capabilities. Signal amplification strategies are being applied to improve the performance of assays with respect to both sensitivity and selectivity, while smartphones are being integrated to expand the analytical power of the technology and promote its accessibility. In this chapter, we review the main technologies in the field of LoC platforms for PoC medical diagnostics and survey recent approaches for improving these assays.