Smartphone Interface Research Articles

A Multi-Channel Urine Sensing Detection System Based on Creatinine, Uric Acid, and pH.

Urine analysis represents a crucial diagnostic technique employed in clinical laboratories. Creatinine and uric acid in urine are essential biomarkers in the human body and are widely utilized in clinical analysis. Research has demonstrated a correlation between the normal physiological concentrations of creatinine and uric acid in urine and an increased risk of hypertension, cardiovascular diseases, and kidney disease. Furthermore, the pH of urine indicates the body's metabolic processes and homeostatic balance. In this study, an integrated multi-channel electrochemical sensing system was developed, combining electrochemical analysis techniques, microelectronic design, and nanomaterials. The architecture of an intelligent medical detection system and the production of an interactive interface for smartphones were accomplished. Initially, multi-channel selective electrodes were designed for creatinine, uric acid, and pH detection. The detection range was 10 nM to 100 μM for creatinine, 100 μM to 500 μM for uric acid, and 4 to 9 for pH. Furthermore, interference experiments were also conducted to verify the specificity of the sensors. Subsequently, multi-channel double-sided sensing electrodes and function-integrated hardware were designed, with the standard equations of target analytes stored in the system's read-only memory. Moreover, a WeChat mini-program platform was developed for smartphone interaction, enabling off-body detection and real-time display of target analytes through smartphones. Finally, the aforementioned electrochemical detection electrodes were integrated with the smart sensing system and wirelessly interfaced with smartphones, allowing for intelligent real-time detection in primary healthcare and individual household settings.

A Breathable and Strain‐Insensitive Multi‐Layered E‐Skin Patch for Digital Healthcare Wearables

AbstractIn this study, a breathable and strain‐insensitive multi‐layered electronic skin (e‐skin) capable of real‐time detection and distinction of electrocardiogram (ECG) signals, temperature, and skin hydration is developed. Leveraging a scalable benchtop method, sensing elements are transferred onto porous and hydrophobic substrates, followed by multi‐layer stacking to enable multimodal sensing. The sensing elements, a combination of carbon nanotube and nanoporous carbon (CNT@NPC) ink, are applied using strain‐insensitive patterned masks, then spray‐coated with styrene–ethylene–butylene–styrene (SEBS) to create a hierarchical porous network through phase separation. The CNT@NPC networks exhibit an improvement in strain insensitivity with active sensing capabilities due to their adaptable molecular tuning capacity and exceptional electrical conductivity. The porous SEBS substrate offers strong bonding with CNT@NPC attributed to the π–π interactions and high kinetic energy dispersion from spray coating allowing effective transfer. This unique design facilitates breathability, and miniaturization that minimizes the interference between different sensing modalities, ensuring accurate and reliable data acquisition. The breathability (3.49 mg cm−2 h−1) and the non‐smearing nature of the multi‐layered e‐skin enables simultaneous monitoring of temperature (0.198% °C−1), skin hydration (relative humidity = 0.77% %−1), and ECG (26 ± 1 dB) with continuous data transmission to a remote smartphone interface.

Exploring Smartphone User Interface Experience-Sharing Behavior: Design Perception and Motivation-Driven Mechanisms through the SOR Model

This study investigates user experience (UX) sharing behaviors in the context of smartphone user interface (UI) design, emphasizing their significance for UI enhancement and effective marketing strategies. Grounded in the Stimulus–Organism–Response (SOR) framework, we examine how design perception attributes—perceived usability, novelty, enjoyment, and brand image—influence UX sharing, with a spotlight on the mediating role of individual motivation. A quantitative analysis (N = 472), Structural Equation Modeling (SEM), and mediation analysis were conducted. Our findings confirm that these components can positively impact UX sharing by bolstering personal expectations and self-efficacy in knowledge sharing, with perceived usability being an exception as it unexpectedly showed a negative association with sharing frequency. Moreover, perceived brand image and individual self-expectancy and self-efficacy enhance sharing outcomes. This research enriches our understanding of the strategic importance of user interface (UI) design in the context of smartphones, furnishing empirical grounding for devising sustainable UI design strategies and productive marketing tactics. Consequently, it bears considerable relevance to both theoretical insights and practical applications.

Development of surface droplet evaporation-based sensing platform for screening lipase inhibitors

The development of new types of sensing platforms with excellent performance is always appealing. In this report, we demonstrate a low-cost and user-friendly sensing platform based on drying of the aqueous droplet on the surface. The principle relies on the transduction of the surfactant concentration into the area of the dried droplet on the surface. The screening of a lipase inhibitor is demonstrated as an example. When triacylglycerols (GT) and lipase are mixed, the aqueous droplet produces a large dried area on the surface. This phenomenon is attributed to the production of sodium oleate due to the enzymatic digestion of GT by lipase. It results in reduction of the surface tension and causes wetting and spreading of the droplet, leaving a large dried area on the surface. However, in the presence of orlistat, a lipase inhibitor, a small dried area is obtained due to the inhibition of lipase activity by orlistat. Using this method, the lipase inhibitor can be readily and effectively screened. Compared to previous studies, this method is simple, rapid, low-cost and avoids the use of labelled molecules and complex instrumentation, with an IC50 value of 0.59 ± 0.09 μM for orlistat. In addition, it also works well with a portable microscope and a smartphone interface for data analysis. Overall, this study provides a new method for rapid and cost-effective screening of lipase inhibitors.

Connected Robotics for Intelligent Surveillance: An IOT Approach

Abstract: The robot employs the HTTP Communication protocol, enabling users to access live video streaming from the OV2640 camera through a standard web browser. The web interface includes intuitive directional buttons for seamless control, allowing users to command the robot to move left, right, forward, and backward. The locomotion of the robot is achieved through two DC motors integrated with a Robot chassis and an L293D motor driver module. This paper presents the development and implementation of an innovative IoT-based Surveillance Robot designed for remote control, utilizing a Wi-Fi module and a smartphone interface. The portable espionage robot integrates cutting-edge technology, featuring an AI Thinker ESP32-CAM module with an ESP32-S processor, an OV2640 camera, motor drivers, and a robust chassis with two moving wheels. The ESP32-CAM allows the capture and storage of images on a microSD card, facilitating efficient data management. The real-time video feed is transmitted wirelessly to the user's smartphone over a Wi-Fi infrastructure, providing a livestreaming experience. This wireless surveillance robot finds applications in various scenarios such as war fields, disaster management, and beyond, showcasing its versatility in remote monitoring and reconnaissance tasks.

Smartphone-Integrated resorcinarene macrocycle capped silver nanoparticles (RMF-AgNPs) probe for enhanced La(III) detection in diverse environments

The demand for precise and responsive detection of Lanthanum (La(III)) is critical in key areas such as environmental monitoring, biomedical research, and industrial processes, underscoring the need for advanced sensor technologies. This research reports an efficient and cost-effective preparation of resorcinarene macrocycle framework (RMF) capped silver nanoparticles (RMF-AgNPs). These nanoparticles were then applied as a novel sensor for La(III), demonstrating dual functionality: they act as a colorimetric sensor and a paper-based probe. Unique in its class, the sensor excels in detecting La(III) at ultra-low concentrations, unaffected by other ions, and undergoes a significant color transition from yellow to grey in response to La(III) presence. This change is linked to the localized surface plasmon resonance (LSPR) absorbance alteration. Extensive analytical methods like FTIR, XPS, AFM, FESEM, DLS, Zeta potential, and UV–Vis spectroscopy confirmed that the sensor operates by aggregating nanoparticles induced by La(III). Adding to its practicality, we incorporated a smartphone interface with the paper-based sensor, enhancing its utility for on-the-spot, real-time detection. The sensor's efficacy was validated across various samples, including soil, rock, urine, drinking water, and industrial effluent, showing its versatility. With detection limits of 15 nM (colorimetric) and 280 nM (paper-based), and linear dynamic ranges from 0.05 to 100 µM and 0.5–100 µM respectively, this sensor marks a significant advancement, effectively bridging lab-based detection with field application needs.

Drone-mounted remote-controlled arm for monitoring and precision spraying coconut rhinoceros beetle infestations

This paper presents a low-cost (locally-assembled) drone system with a sprayer arm and a remote control for monitoring and precisely applying pesticides to coconut trees infested by the Rhinoceros Beetle. A modified RGB IP camera continuously monitors potential coconut beetle infestation points, capturing real-time spray images, and displaying the results through a smartphone interface. The system provides real-time monitoring, allowing immediate remote control of the spray operation from the ground upon detecting beetle infestations. The drone-mounted sprayer arm is controlled in response to the ground-based signals, to accurately extend or contract while effectively dispensing spray chemicals onto the target areas at the upper canopy of coconut trees. In our tests using Nam-Hom coconut trees, which averaged a height of 10.4 m, the system operated at a speed of 1.25 km/h, achieving a spraying flow rate of 0.333 l/h and a working capacity of 0.352 ha/h. The controlled spraying setup emits a solid jet, ensuring precision and effective atomization of chemicals within a distance range of 1.0 to 4.0 m from the target. The spray quality attributes (droplet size, pattern, and coverage) were not significantly affected by the wind speed. The system could potentially reduce labor costs, chemical usage, and health risks associated with pesticide application.

Portable Hydrogel Kits Made with Bimetallic Nanozymes for Point-of-Care Testing of Perfluorooctanesulfonate.

Perfluorooctanesulfonate (PFOS), an emerging organic contaminant, necessitates robust on-site detection strategies to safeguard human health and ecological balance. This study introduces a novel point-of-care testing (POCT) platform, combining a hydrogel kit with nanozymes and smartphone technology, for the highly sensitive detection of PFOS. The strategy utilizes copper-substituted cobalt-based Prussian blue analogue nanoboxes (CuCo-PBA NBs), which exhibit intricate hollow structures and remarkable peroxidase-like catalytic activity, efficiently catalyzing the oxidation of chromogenic substrates with hydrogen peroxide (H2O2). Density functional theory calculations elucidate the adsorption dynamics of H2O2 on CuCo-PBA NBs, identifying the factors that improve the catalytic efficiency. The colorimetric POCT platform, integrating the hydrogel kit with a smartphone interface, demonstrates practical utility and achieves a detection limit of 1.43 × 10-8 mol L-1 for PFOS. This research not only presents a new nanozyme design for PFOS detection in diverse matrices, such as lake water, whole blood, urine, and milk, but also paves the way for developing a portable and efficient POCT platform for a variety of emerging contaminants.

Loopholes in the Indian Banking System concerning Non-Performing Assets (NPAs) – A Case Study of “Axis Bank and HDFC Bank”

This paper presents the development and implementation of an innovative IoT-based Surveillance Robot designed for remote control, utilizing a Wi-Fi module and a smartphone interface. The portable espionage robot integrates cutting-edge technology, featuring an AI Thinker ESP32-CAM module with an ESP32-S processor, an OV2640 camera, motor drivers, and a robust chassis with two moving wheels. The ESP32-CAM allows the capture and storage of images on a microSD card, facilitating efficient data management. The robot employs the HTTP Communication protocol, enabling users to access live video streaming from the OV2640 camera through a standard web browser. The web interface includes intuitive directional buttons for seamless control, allowing users to command the robot to move left, right, forward, and backward. The locomotion of the robot is achieved through two DC motors integrated with a Robot chassis and an L293D motor driver module. The real-time video feed is transmitted wirelessly to the user's smartphone over a Wi-Fi infrastructure, providing a live- streaming experience. This wireless surveillance robot finds applications in various scenarios such as war fields, disaster management, and beyond, showcasing its versatility in remote monitoring and reconnaissance tasks. Keywords: IoT, Surveillance Robot, Wireless Control, ESP32- CAM, HTTP Communication, Video Streaming, Smartphone Control, Disaster Management, Robotics, Remote Monitoring, Reconnaissance.

Smartphone-Facilitated In-Situ Hearing Aid Audiometry for Community-Based Hearing Testing.

Hearing loss prevalence is increasing, with an estimated 2.5 billion people affected globally by 2050. Scalable service delivery models using innovative technologies and task-shifting are World Health Organization priorities to improve access to hearing care, particularly in low- and middle-income countries. Smartphone-facilitated audiometry in the community using hearing aids covered by noise-attenuating ear cups ("in-situ") could support more accessible hearing care when provided by less trained individuals such as community health workers (CHWs). This study aimed to determine the validity of this method for potential hearing aid fitting. Study objectives included determining the maximum permissible ambient noise level (MPANL), inter-device reliability, clinical threshold accuracy, reliability, and performance in real-world settings. Experiment 1: 15 normal-hearing adult participants were evaluated to determine MPANLs for circumaural Peltor 3M earcups covering Lexie Lumen hearing aids with smartphone-facilitated in-situ audiometry. MPANLs were calculated by measuring the difference in attenuation between thresholds obtained with standard headphones and in-situ hearing aids. Experiment 2: Pure-tone frequency and intensity output of 14 same-model Lexie Lumen hearing aids were measured to determine inter-device reliability. Pure-tone stimuli were measured and analyzed to determine sound pressure levels in decibels and pure-tone frequency when connected to a test box 2cc coupler. Experiment 3: 85 adult participants were tested in a sound booth to determine the accuracy of automated in-situ pure-tone audiometry (PTA) compared to clinical PTA (500, 1000, 2000, 3000, 4000, 6000 Hz) facilitated by an audiologist. The first 39 participants were tested twice to determine test-retest reliability. Experiment 4: In a community setting, 144 adult participants were tested with automated in-situ audiometry facilitated by CHWs using a smartphone app. These participants were subsequently tested with automated mobile PTA (500, 1000, 2000, 4000 Hz). An additional 44 participants were tested twice to determine test-retest reliability. Experiment 1: MPANLs of the Peltor 3M earcup-covered hearing aids were higher than standard headphones across all frequencies, ranging from 24 to 47.3 dB SPL. Experiment 2: Inter-device performance reliability was high, with all inter-device differences across all intensities and frequencies less than 3 dB. Frequency output was consistent and differed less than 0.7% between devices. Experiments 3 and 4: 85.2% and 83.3% of automated in-situ audiometry thresholds were within 10 dB of thresholds obtained in the sound booth and in a community setting, respectively. Acceptable test-retest intraclass correlation coefficient (ICC) was evident across all thresholds obtained in a sound booth (ICC = 0.85 to 0.93) and in a community setting (ICC = 0.83 to 0.97). Smartphone-facilitated in-situ audiometry allows for reliable and valid community-based testing. A simple smartphone user interface and automated in-situ audiometry allow CHWs with minimal training to facilitate the testing. With the additional capability to program hearing aids via the smartphone after the initial test, this approach would have the potential to support widespread access to personalized hearing aid fittings facilitated by CHWs in low- and middle-income countries. This approach also supports self-fitting options based on in-situ thresholds, enabling testing and fitting via over the counter hearing aids.

INVESTIGATING USER PREFERENCES FOR SMARTPHONE ICON DESIGN: A KANO MODEL ANALYSIS

In the ever-evolving realm of smartphone interface design, understanding user preferences is paramount. This study endeavors to comprehensively scrutinize such preferences utilizing the Kano model. Engaging 100 participants, the research assessed perceptions regarding 14 design attributes, employing a Likert scale for evaluations. Primary findings elucidated that attributes like recognizability, usability, personalization, and display effect hold paramount importance. However, an intriguing observation was a suggested potential variance across age demographics, which, upon further introspection, remained inconclusive in this research. This denotes an avenue necessitating future exploration. Designers, while conceptualizing smartphone interfaces, are advised to prioritize these identified attributes, possibly complementing age-specific needs, to ensure heightened user satisfaction. Ultimately, this research highlights the Kano model's robustness and its invaluable contribution to the domain of smartphone interface design research.

Compact Point-of-Care Device for Self-Administered HIV Viral Load Tests from Whole Blood.

Human immunodeficiency virus (HIV) is a significant problem to consider as it can lead to acquired immune deficiency syndrome (AIDS). Fortunately, AIDS is manageable through antiretroviral therapy (ART). However, frequent viral load monitoring is needed to monitor the effectiveness of the therapy. The current reverse transcription-polymerase chain reaction (RT-PCR) viral load monitoring is highly effective, but is challenged by being resource-intensive and inaccessible, and its turnaround time does not meet demand. An unmet need exists for an affordable, rapid, and user-friendly point-of-care device that could revolutionize and ensure therapeutic effectiveness, particularly in resource-limited settings. In this work, we explored a point-of-care HIV viral load device to address this need. This device can perform streamlined plasma separation, viral RNA extraction, and real-time reverse transcription loop-mediated isothermal amplification (RT-LAMP) semiquantitative testing in an ultracompact device. We developed an absorption-based membrane plasma separation method suitable for finger-prick blood samples, achieving an efficiency of 80%. We also designed a syringe-based RNA extraction method for on-site plasma processing with a viral recovery efficiency of 86%. We created a portable device with a smartphone interface for real-time semiquantitative RT-LAMP, which is useful for monitoring viral load. The device uses lyophilized reagents, processed with our lyophilization method, which remain stable for 16 weeks. The device can accurately categorize viral load into low, medium, and high categories with 95% accuracy. We believe this point-of-care HIV self-test device, offering convenience and long-term storage, could aid patients in home-based ART treatment monitoring.

SyncLabeling: A Synchronized Audio Segmentation Interface for Mobile Devices

Manual audio segmentation is a time-consuming process, especially when there is more than one sound playing simultaneously that needs to be segmented and annotated (e.g., target and background sounds). In conventional audio annotation interfaces, users need to repeatedly pause and replay the audio to complete an overlap segmentation task, which is very inefficient. In this paper, we propose "SyncLabeling," a synchronized audio segmentation interface for smartphones that allows users to segment and annotate two overlapping sounds in a single audio stream at a time using a game-like labeling interface on mobile devices. We conducted a user study to compare the proposed SyncLabeling interface with a conventional audio annotation interface on four types of audio segmentation tasks. The results showed that the proposed interface is much more efficient than the conventional interface (2.4× faster) under comparable annotation accuracy in most tasks. In addition, more than half of the participants enjoyed using the proposed SyncLabeling interface and showed willingness to use it.

Using a digital health intervention "INTERCEPT" to improve secondary prevention in coronary heart disease (CHD) patients: protocol for a mixed methods non-randomised feasibility study.

Background: Digital health interventions (DHIs) are increasingly used for the secondary prevention of cardiovascular disease (CVD). The aim of this study is to determine the feasibility of "INTERCEPT", a co-designed DHI developed to improve secondary prevention in hospitalised coronary heart disease patients (CHD). Methods: This non-randomised feasibility study will be conducted using a mixed methods process evaluation with a sample of 40 patients in an acute hospital setting. Informed by behaviour change theory, the Intercept application (I-App) integrates a smartphone interface, health care professional portal, a fitness wearable and a blood pressure monitor. I-App is designed to support and motivate patients to set goals, self-monitor lifestyle and medical risk factors, and manage their medications, with the health care professional portal enabling monitoring and communication with patients. Using convenience sampling, eligible patients will be recruited in two phases, a pre-implementation phase and an implementation phase. During the pre-implementation phase participants will not immediately receive the I-App but will be invited to receive the I-App at 3 months follow-up. This will enable early learning about the processes of recruitment and conducting the assessment prior to full scale deployment of the I-App. During the implementation phase, participants will be invited to download the I-App to their smartphone prior to hospital discharge. Qualitative interviews will be conducted among a subset of patients and health care professionals to gain a greater insight into their experience of using the I-App. Primary outcomes will be assessed at baseline and 3-month follow-up. Using pre-defined feasibility criteria, including recruitment, retention and engagement rates, together with data on intervention acceptability, will determine the appropriateness of progressing to a definitive trial. Discussion: This study will provide important insights to help inform the feasibility of conducting a definitive trial of "INTERCEPT" among coronary heart disease patients in a critical health care setting.

Smartphone-powered portable chemiresistive sensing system for label free detection of lead ions in water

Lead (Pb) is a toxic heavy metal that can contaminate water sources and cause serious health problems. Detecting Pb in water is essential for protecting public health and the environment. However, the current state of technology heavily depends upon traditional bench-top equipment for detecting toxic heavy metal ions dissolved in water. In this paper we report a portable, label-free chemiresistive sensor for the selective detection of Pb ions dissolved in water. Lithography patterned micro-ineterdigitated electrodes (µIDEs) modified with Graphene oxide (GO) is used as the transducing agent to capture the sensor’s electrical response on a portable readout platform with a smartphone interface. Graphene oxide functionalized with environment friendly oligosaccharide β- Cyclodextrin acts as the sensing material. The sensor’s electrical properties undergo variation in the presence of Pb ions, hence serving as a parameter for successfully detecting the targeted heavy metal ion. The designed sensor is highly selective towards Pb ions, even in the presence of other heavy metal ions, with the lowest detection concentration being 100 pico Molar (pM). The smartphone-powered portable readout circuit, along with the sensor, makes the entire system energy-efficient and cost-effective, providing a quick analysis of the sensor output. Further, an ML algorithm is used to enhance the data analysis and assist the classification based on sensor response.

Study on the Smart phone Interface Design to Improve Usability -Focused on Jakob Nielsen's Usability Heuristics-

Study on the Smart phone Interface Design to Improve Usability -Focused on Jakob Nielsen's Usability Heuristics-

A Real-Time Data Monitoring Framework for Predictive Maintenance Based on the Internet of Things

The Internet of Things (IoT) is a platform that manages daily life tasks to establish an interaction between things and humans. One of its applications, the smart office that uses the Internet to monitor electrical appliances and sensor data using an automation system, is presented in this study. Some of the limitations of the existing office automation system are an unfriendly user interface, lack of IoT technology, high cost, or restricted range of wireless transmission. Therefore, this paper presents the design and fabrication of an IoT-based office automation system with a user-friendly smartphone interface. Also, real-time data monitoring is conducted for the predictive maintenance of sensor nodes. This model uses an Arduino Mega 2560 Rev3 microcontroller connected to different appliances and sensors. The data collected from different sensors and appliances are sent to the cloud and accessible to the user on their smartphone despite their location. A sensor fault prediction model based on a machine learning algorithm is proposed in this paper, where the k-nearest neighbors model achieved better performance with 99.63% accuracy, 99.59% F1-score, and 99.67% recall. The performance of both models, i.e., k-nearest neighbors and naive Bayes, was evaluated using different performance metrics such as precision, recall, F1-score, and accuracy. It is a reliable, continuous, and stable automation system that provides safety and convenience to smart office employees and improves their work efficiency while saving resources.

Simultaneous quantitative detection of hematocrit and hemoglobin from whole blood using a multiplexed paper sensor with a smartphone interface.

We report a highly accurate single-step label-free testing technology for simultaneous and independent hematocrit (Hct) and hemoglobin (Hb) level detection from a drop of whole blood by employing a disposable paper strip sensor interfaced with a portable impedimetric device. The paper strip is fabricated by in situ automated printing of a customized electrode template on the non-glossy side of a commercially available photo paper substrate followed by graphite deposition. The integrated platform device technology additionally includes a compact detection cum readout unit comprising a high precision impedance converter system that combines an on-board frequency generator with an analog-to-digital converter evaluation board, collectively interfaced with a central processor, calibration circuit, and smartphone. Employing a dispensed blood sample volume of 25 μL, the device is shown to have a sensitivity of 92 Ω/Hct and 287 Ω/Hb at an optimal frequency of 57 kHz. The respective linear response regimes appear to be wide enough to cover physiologically relevant limits, with excellent stability and reproducibility. Validation with clinical samples reveals limits of detection of Hct and Hb levels as low as 4.66% and 1.89 g dL-1, respectively, which are beyond the quantitative capability of commonly used affordable point of care test kits. The envisaged paradigm of rapid, robust, highly accurate, energy-efficient, simple, user-friendly, multiplex portable detection, obviating any possible ambiguities in interpretation due to common artefacts of colorimetric detection technologies such as optical interference with the image analytical procedure due to the inherent redness of blood samples and background illumination, renders this ideal for deployment in resource-limited settings.

A wireless smartphone-based “tap-and-detect” formaldehyde sensor with disposable nano-palladium grafted laser-induced graphene (nanoPd@LIG) electrodes

We developed a fully integrated smart sensing device for on-site testing of food to detect trace formaldehyde (FA). A nano-palladium grafted laser-induced graphene (nanoPd@LIG) composite was synthesized by one-step laser irradiation of a Pd2+-chitosan-polyimide precursor. The composite was synthesized in the form of a three-electrode sensor on a polymer substrate. The electrochemical properties and morphology of the fabricated composite were characterized and the electrochemical kinetics of FA oxidation at the nanoPd@LIG electrode were investigated. The nanoPd@LIG electrode was combined with a smart electrochemical sensing (SES) device to determine FA electrochemically. The proposed SES device uses near field communication (NFC) to receive power and transfer data between a smartphone interface and a battery-free sensor. The proposed FA sensor exhibited a linear detection range from 0.01 to 4.0 mM, a limit of detection of 6.4 μM, good reproducibility (RSDs between 2.0 and 10.1%) and good anti-interference properties for FA detection. The proposed system was used to detect FA in real food samples and the results correlated well with the results from a commercial potentiostat and a spectrophotometric analysis.

Internet of medical things-enabled CRISPR diagnostics for rapid detection of SARS-CoV-2 variants of concern.

Previous studies have highlighted CRISPR-based nucleic acid detection as rapid and sensitive diagnostic methods for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we reported an optimized CRISPR-Cas12a diagnostic platform for the safe and rapid detection of SARS-CoV-2 variants of concern (VOCs). This platform, which was referred to as CALIBURN-v2, could complete the diagnosis on extracted RNA samples within 25 min in a closed-lid reaction mode and had 100-fold increase in detection sensitivity in comparison with previous platforms. Most importantly, by integrating a portable device and smartphone user interface, CALIBURN-v2 allowed for cloud server-based data collection and management, thus transforming the point-of-care testing (POCT) platform to internet of medical things (IoMT) applications. It was found that IoMT-enabled CALIBURN-v2 could achieve 95.56% (172 out of 180) sensitivity for SARS-CoV-2 wild type and 94.38% (84 out of 89) overall sensitivity for SARS-CoV-2 variants including Delta and Omicron strains. Therefore, our study provides a feasible approach for IoMT-enabled CRISPR diagnostics for the detection of SARS-CoV-2 VOCs.