Dataset Information

An ultra-low-cost smartphone octochannel spectrometer for mobile health diagnostics.

ABSTRACT: With the rapid development and proliferation of mobile devices with powerful computing power and the ability of integrating sensors into mobile devices, the potential impact of mobile health (mHealth) diagnostics on the public health is drawing researchers' attention. We developed a Smartphone Octo-channel Spectrometer (SOS) as a mHealth diagnostic tool. The SOS has nanoscale wavelength resolution, is self-illuminated from the smartphone itself, and is ultra-low cost (less than $20). A user interface controls the optical sensing parameters and precise alignment. After calibrating and testing the SOS by quantifying protein concentrations, we clinically validated the SOS by comparing the diagnostic performance of our device with that of a clinical spectrophotometer. About 180 serum samples from de-identified patients with 4 types of autoantibodies were blindly read the ELISA results. The accuracy of the SOS achieved 100% across the clinical reportable range compared with the FDA-approved instrument. Furthermore, the self-illuminated SOS only requires about half of the light intensity of the FDA-approved instrument to achieve clinical-level sensitivity. The low-energy-consumption and low-cost SOS enables point-of-care spectrophotometric sensing in low-resource areas, and can be integrated into point-of-care diagnostic systems for rapid multiplex readout and analysis at patient bedside or at home.

SUBMITTER: Wang LJ

PROVIDER: S-EPMC6382277 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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An ultra-low-cost smartphone octochannel spectrometer for mobile health diagnostics.

Wang Li-Ju LJ Naudé Nicole N Chang Yu-Chung YC Crivaro Anne A Kamoun Malek M Wang Ping P Li Lei L

Journal of biophotonics 20180429 8

With the rapid development and proliferation of mobile devices with powerful computing power and the ability of integrating sensors into mobile devices, the potential impact of mobile health (mHealth) diagnostics on the public health is drawing researchers' attention. We developed a Smartphone Octo-channel Spectrometer (SOS) as a mHealth diagnostic tool. The SOS has nanoscale wavelength resolution, is self-illuminated from the smartphone itself, and is ultra-low cost (less than $20). A user inte ...[more]

PMID: 29603674

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Project description:BackgroundSuccessful recruitment of participants to mobile health (mHealth) studies presents unique challenges over in-person studies. It is important to identify recruitment strategies that maximize the limited recruitment resources available to researchers.ObjectiveThe objective of this study was to describe a case study of a unique recruitment process used in a recent mHealth software app designed to increase smoking cessation among weight-concerned women smokers. The See Me Smoke-Free app was deployed to the Google Play Store (Alphabet, Inc., Google, LLC), where potential participants could download the app and enroll in the study. Users were invited in-app to participate in the study, with no in-person contact. The recruitment activities relied primarily on earned (free) and social media.MethodsTo determine the relationship between recruitment activities and participant enrollment, the researchers explored trends in earned and social media activity in relation to app installations, examined social media messaging in relation to reach or impressions, and described app users' self-reported referral source. The researchers collected and descriptively analyzed data regarding recruitment activities, social media audience, and app use during the 18-week recruitment period (March 30, 2015-July 31, 2015). Data were collected and aggregated from internal staff activity tracking documents and from Web-based data analytics software such as SumAll, Facebook Insights (Facebook, Inc.), and Google Analytics (Alphabet, Inc., Google, LLC).ResultsMedia coverage was documented across 75 publications and radio or television broadcasts, 35 of which were local, 39 national, and 1 international. The research team made 30 Facebook posts and 49 tweets, yielding 1821 reaches and 6336 impressions, respectively. From March 30, 2015 to July 31, 2015, 289 unique users downloaded the app, and 151 participants enrolled in the study.ConclusionsResearch identifying effective online recruitment methods for mHealth studies remains minimal, and findings are inconsistent. We demonstrated how earned media can be leveraged to recruit women to an mHealth smoking cessation trial at low cost. Using earned media and leveraging social media allowed us to enroll 3 times the number of participants that we anticipated enrolling. The cost of earned media resides in the staff time required to manage it, particularly the regular interaction with social media. We recommend communication and cooperation with university public affairs and social media offices, as well as affiliate programs in journalism and communications, so that earned media can be used as a recruitment strategy for mHealth behavior change interventions. However, press releases are not always picked up by the media and should not be considered as a stand-alone method of recruitment. Careful consideration of an intervention's broad appeal and how that translates into potential media interest is needed when including earned media as part of a comprehensive recruitment plan for mHealth research.

Project description:Introduction: Accurate and rapid diagnostics paired with effective tracking and tracing systems are key to halting the spread of infectious diseases, limiting the emergence of new variants and to monitor vaccine efficacy. The current gold standard test (RT-qPCR) for COVID-19 is highly accurate and sensitive, but is time-consuming, and requires expensive specialised, lab-based equipment. Methods: Herein, we report on the development of a SARS-CoV-2 (COVID-19) rapid and inexpensive diagnostic platform that relies on a reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay and a portable smart diagnostic device. Automated image acquisition and an Artificial Intelligence (AI) deep learning model embedded in the Virus Hunter 6 (VH6) device allow to remove any subjectivity in the interpretation of results. The VH6 device is also linked to a smartphone companion application that registers patients for swab collection and manages the entire process, thus ensuring tests are traced and data securely stored. Results: Our designed AI-implemented diagnostic platform recognises the nucleocapsid protein gene of SARS-CoV-2 with high analytical sensitivity and specificity. A total of 752 NHS patient samples, 367 confirmed positives for coronavirus disease (COVID-19) and 385 negatives, were used for the development and validation of the test and the AI-assisted platform. The smart diagnostic platform was then used to test 150 positive clinical samples covering a dynamic range of clinically meaningful viral loads and 250 negative samples. When compared to RT-qPCR, our AI-assisted diagnostics platform was shown to be reliable, highly specific (100%) and sensitive (98-100% depending on viral load) with a limit of detection of 1.4 copies of RNA per µL in 30 min. Using this data, our CE-IVD and MHRA approved test and associated diagnostic platform has been approved for medical use in the United Kingdom under the UK Health Security Agency's Medical Devices (Coronavirus Test Device Approvals, CTDA) Regulations 2022. Laboratory and in-silico data presented here also indicates that the VIDIIA diagnostic platform is able to detect the main variants of concern in the United Kingdom (September 2023). Discussion: This system could provide an efficient, time and cost-effective platform to diagnose SARS-CoV-2 and other infectious diseases in resource-limited settings.

Dataset Information

An ultra-low-cost smartphone octochannel spectrometer for mobile health diagnostics.

Publications

An ultra-low-cost smartphone octochannel spectrometer for mobile health diagnostics.

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