Smart phone diagnostic

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Smartphone-based diagnostics for biosensing infectious human pathogens
Author links open overlay panelAditya Amrut Pawar a, Sanchita Bipin Patwardhan a, Sagar Barage a b, Rajesh Raut c, Jaya Lakkakula a b
, Arpita Roy d
, Rohit Sharma e, Jigisha Anand f
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https://doi.org/10.1016/j.pbiomolbio.2023.05.002
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Abstract
The widespread usage of smartphones has made accessing vast troves of data easier for everyone. Smartphones are powerful, handy, and easy to operate, making them a valuable tool for improving public health through diagnostics. When combined with other devices and sensors, smartphones have shown potential for detecting, visualizing, collecting, and transferring data, enabling rapid disease diagnosis. In resource-limited settings, the user-friendly operating system of smartphones allows them to function as a point-of-care platform for healthcare and disease diagnosis. Herein, we critically reviewed the smartphone-based biosensors for the diagnosis and detection of diseases caused by infectious human pathogens, such as deadly viruses, bacteria, and fungi. These biosensors use several analytical sensing methods, including microscopic imaging, instrumental interface, colorimetric, fluorescence, and electrochemical biosensors. We have discussed the diverse diagnosis strategies and analytical performances of smartphone-based detection systems in identifying infectious human pathogens, along with future perspectives.
Introduction
Conventional disease biosensing devices are often expensive, bulky, and robust, which limits their implementation in biomedical diagnosis, particularly in resource-constrained conditions. For example, the flow cytometer, a diagnostic tool used to monitor HIV/AIDS by detecting the CD4+ T-cell population, has several drawbacks, including tedious procedures, high cost, and large size (Pattanapanyasat and Thakar, 2005). Similarly, the polymerase chain reaction (PCR) technique has been widely used to detect human pathogens such as viruses, bacteria, and fungi, but it also has limitations, such as false-positive and false-negative results, costly setups, and monotonous protocols (Valones et al., 2009; Maurer, 2011; Drain et al., 2014; Yager et al., 2008). Moreover, such bulky instruments require professional personnel for efficient operations in hospitals, clinics, or diagnostic labs, making them less practical for use in low-income, remote, and resource-limited areas. To address these challenges, there is a growing demand for portable, cost-effective, and efficient biomedical devices with sensitive measurements and sensing capabilities.
A point-of-care (POC) diagnostics offers a rapid molecular diagnosis platform that can provide real-time, lab-quality results within minutes at the patient site. This method is portable, easy to operate, rapid, and reduces medical mishandling, providing accurate test results with small sample volumes and requiring no dedicated permanent area (Zarei, 2018; Chin et al., 2012). Recent technological advancements in smart materials, microfluidics, lab-on-a-chip (LOC) technology, and data analysis have significantly improved the performance of POC diagnostics, allowing for a wide range of applications on a miniaturized chip-scale platform (Huang et al., 2018). However, for practical applications of such small devices, various accessory devices are needed for effective detection, readout, data analytics, and result display. To address these challenges, researchers are developing smartphone-based analytical and diagnostic biosensors.
Smartphones have become an indispensable tool in modern life, revolutionizing communication, education, entertainment, shopping, banking, security, and healthcare. It is predicted that by 2021, 40% of the world's population will own a smartphone (Smartphones market – growth and trends, 2022–2027). The latest smartphones are portable and affordable, miniature computers with full operating systems, large data storage, fast multicore processors, ample battery capacity, audio and video capabilities, high-quality camera lenses, touch screens, wireless connectivity, and user-friendly interfaces (Kanchi et al., 2018). Data transfer methods such as Bluetooth, Wi-Fi, and 4G cellular data services have enabled the transmission of smartphone-analyzed data to clinical professionals, improving medical services in remote areas. Biosensors integrated with smartphones can detect pathogens in samples such as urine, blood, saliva, or nasal swabs. High-resolution cameras can capture images for pathogen detection. Moreover, smartphones can serve as a consultation platform for patients to consult remotely with doctors. The use of additional devices, such as microscopes and in-built mobile apps, can aid in the diagnosis of infectious pathogens.
Smartphones are equipped with intrinsic sensors, such as magnetometers, microphones, thermometers, optical sensors, and accelerometers, to sense different types of data for various applications, including direction, sound, temperature, image, and acceleration. Researchers have been focusing on using smartphones for medical diagnostics and detection, and have developed different accessory designs that can be attached intrinsically or extrinsically to smartphones for analytical biosensing for the detection of signals (Li et al., 2016). With the help of digital technologies, machine learning, and cloud computing, smartphone-based medical applications have the potential to revolutionize conventional healthcare diagnosis (Zeinhom et al., 2018). Compared to traditional detection and diagnosis techniques, smartphones offer several advantages, including the ability to measure unlike quantities using different integrated sensors, communicate wirelessly with other devices, and operate using simple methods (Murphy and King, 2016). Smartphones can be integrated with LOC and microfluidics to build bioanalytical and diagnostic systems. The efficacy of smartphone-based diagnostic and analytical biosensors has been demonstrated in diverse applications, such as screening for food toxins, environmental monitoring, and healthcare diagnostics (Mosa et al., 2012; Stemple et al., 2014; Cho et al., 2015; Im et al., 2015).
In this review, we present an overview of the recent advances in smartphone-based diagnostics and analytical methods for the detection of human pathogens including viruses, bacteria, and fungi. The focus is on the latest developments in smartphone-based detectors and instrumental interfaces, as well as on the various sensing techniques used for detecting human pathogens, such as colorimetric sensing, fluorescence sensing, and electrochemical sensing, which are illustrated in Fig. 1. We also discuss the current limitations and challenges associated with the development of smartphone-based diagnostics, followed by a brief discussion on future perspectives and possibilities.
Section snippets
Smartphone-based instrumental interface
The integration of analytical instruments with smartphones through interface devices such as bluetooth, Wi-Fi, and micro-USB ports is essential for maximizing the potential of smartphones in diagnostic applications (Table 1). With this setup, the smartphone can perform experimental measurements, and the results can be displayed on the smartphone screen. The commercial availability of fully integrated smartphone diagnostic systems makes it easier to develop and offers a promising solution for
Smartphone-based microscopic imaging
The use of microscopy in modern medicine offers a valuable tool for screening and diagnosing numerous fatal diseases. By implementing microscopy on smartphones, healthcare solutions can be improved in resource-limited and remote regions where infectious diseases are rampant. Smartphone microscopy has benefited from the use of low-cost, miniaturized microscopic components, such as low-power LEDs and high-quality camera lenses, which enable microscopes to produce high-resolution and high-quality
Smartphone-based colorimetric biosensors
Smartphone-based colorimetric biosensors refer to optical systems that utilize smartphones as detectors. These systems are capable of capturing colorimetric images for diagnostic tests, much like smartphone-based microscopes. Colorimetric tests are designed to detect changes in the intensity of light reflected or absorbed by reagent-analyte complexes. These changes are caused by structural shifts or plasmon resonance phenomena, both of which can alter the sample's optical properties.
Smartphone-based fluorescence biosensors
Fluorescent smartphone-based biosensors have been utilized in various applications for the identification of bacteria, viruses, DNA, and biomarkers, owing to their inherent sensitivity and non-invasiveness. The fluorescence dyes used in these biosensors aid in the accurate sensing and diagnosis of infectious pathogens, and fluorescence bioimaging further improves specificity and sensitivity for better detection. To achieve quantification of blood cells, bacteria, antigens, proteins and nucleic
Smartphone-based electrochemical biosensors
Smartphone-based electrochemical biosensors are diagnostic devices that use smartphones to identify infectious human pathogens and produce an electrochemical signal. The biosensors can detect pathogens, and the output is displayed on the smartphone's screen for better disease diagnosis and monitoring. Electrochemical analysis is highly specific and sensitive, making it a convenient tool for quantitatively detecting analytes such as proteins, metabolites, and nucleic acids. However, smartphones
Conclusion and future perspectives
Recent advancements in smartphone-based biosensors have provided low-cost, portable, and easy-to-operate diagnostic platforms for point-of-care (POC) applications in healthcare. Miniaturized technologies, nanotechnology, proteomics, genomics, and microfluidics, along with enormous developments in smartphone and internet technology, have enabled the production of effective diagnostic devices. Physical quantities can be easily measured on smartphone sensor apps on a large scale. Moreover,
Author statement
Conceptualization Aditya Amrut Pawar, Sanchita Bipin Patwardhan, Sagar Barage, Rajesh Raut, Jaya Lakkakula, Arpita Roy, Rohit Sharma, Methodology Aditya Amrut Pawar, Sanchita Bipin Patwardhan, Jaya Lakkakula, Arpita Roy, Formal analysis Sagar Barage, Rajesh Raut, Jaya Lakkakula, Arpita Roy, Rohit Sharma, Jigisha Anand, Data Curation Jaya Lakkakula, Arpita Roy, Writing - Original Draft Aditya Amrut Pawar, Sanchita Bipin Patwardhan, Jaya Lakkakula, Arpita Roy, Writing - Review & Editing Sagar
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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